diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md new file mode 100644 index 0000000..891c617 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/bug_report.md @@ -0,0 +1,27 @@ +--- +name: Bug report +about: Create a report to help us improve +title: '' +labels: '' +assignees: '' + +--- + +**Describe the bug** +A clear and concise description of what the bug is. + +**To Reproduce** +Steps to reproduce the behavior: +1. Go to '...' +2. Click on '....' +3. Scroll down to '....' +4. See error + +**Expected behavior** +A clear and concise description of what you expected to happen. + +**Screenshots** +If applicable, add screenshots to help explain your problem. + +**Additional context** +Add any other context about the problem here. diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md new file mode 100644 index 0000000..bbcbbe7 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/feature_request.md @@ -0,0 +1,20 @@ +--- +name: Feature request +about: Suggest an idea for this project +title: '' +labels: '' +assignees: '' + +--- + +**Is your feature request related to a problem? Please describe.** +A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] + +**Describe the solution you'd like** +A clear and concise description of what you want to happen. + +**Describe alternatives you've considered** +A clear and concise description of any alternative solutions or features you've considered. + +**Additional context** +Add any other context or screenshots about the feature request here. diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md new file mode 100644 index 0000000..66361c7 --- /dev/null +++ b/.github/pull_request_template.md @@ -0,0 +1,11 @@ +# Short Description +Add a short description describing the pull request (PR) here. + +# Checklist before PR can be merged: +- [ ] closes issue #xxxx +- [ ] is documented +- [ ] Format code with [Black formatting](https://black.readthedocs.io) +- [ ] type hints for functions and methods +- [ ] tests added / passed +- [ ] Example Notebook (for new features) +- [ ] Remove output for all notebooks with changes diff --git a/.github/workflows/ci-testing.yml b/.github/workflows/ci-testing.yml new file mode 100644 index 0000000..3ae40ff --- /dev/null +++ b/.github/workflows/ci-testing.yml @@ -0,0 +1,42 @@ +# This workflow will install Python dependencies, run tests and lint with a variety of Python versions +# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python + +name: Python package + +on: + push: + branches: [ "master", "dev" ] + pull_request: + branches: [ "master", "dev" ] + +jobs: + build: + + runs-on: ubuntu-latest + strategy: + fail-fast: false + matrix: + python-version: ["3.9", "3.10", "3.11"] + + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v3 + with: + python-version: ${{ matrix.python-version }} + check-latest: true + cache: "pip" + cache-dependency-path: requirements.txt + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -r requirements.txt + - name: Lint with flake8 + run: | + # stop the build if there are Python syntax errors or undefined names + flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics + # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide + flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics + - name: Test with pytest + run: | + pytest diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 93637ef..03c74a3 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -13,12 +13,12 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python-version: ['3.7', '3.8', '3.9', '3.10'] + python-version: ['3.9', '3.10', '3.11', '3.12',] steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 + uses: actions/setup-python@v5 with: python-version: ${{ matrix.python-version }} - name: Install dependencies diff --git a/.readthedocs.yaml b/.readthedocs.yaml new file mode 100644 index 0000000..b240758 --- /dev/null +++ b/.readthedocs.yaml @@ -0,0 +1,32 @@ +# .readthedocs.yml +# Read the Docs configuration file +# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details + +# Required +version: 2 + +build: + os: ubuntu-22.04 + tools: + python: "3.11" + +# Build documentation in the docs/ directory with Sphinx +sphinx: + configuration: docs/conf.py + +# Build documentation with MkDocs +#mkdocs: +# configuration: mkdocs.yml + +# Optionally build your docs in additional formats such as PDF and ePub +#formats: +# - epub +# - pdf + +# Optionally set the version of Python and requirements required to build your docs +python: + install: + - method: pip + path: . + extra_requirements: + - rtd \ No newline at end of file diff --git a/.zenodo.json b/.zenodo.json index 185c646..d29b4bd 100644 --- a/.zenodo.json +++ b/.zenodo.json @@ -10,7 +10,7 @@ "orcid": "0000-0002-2730-494X" }, { - "affiliation": "University of Graz, Graz, Austria.", + "affiliation": "Eawag, Dübendorf, Switzerland.", "name": "Raoul Collenteur", "orcid": "0000-0001-7843-1538" } diff --git a/CITATION.cff b/CITATION.cff index 360360b..bfce53e 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -7,13 +7,15 @@ authors: - family-names: "Collenteur" given-names: "Matevz" orcid: "https://orcid.org/0000-0001-7843-1538" -title: "PyEt-a Python package to estimate potential and reference evapotranspiration" -version: 1.1.0 -doi: https://doi.org/10.5194/egusphere-egu21-15008 -date-released: 2021 +- family-names: "Birk" + given-names: "Steffen" + orcid: "https://orcid.org/0000-0001-7474-3884" +title: "Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt" +doi: https://doi.org/10.5194/hess-2022-417 +date-released: 2023 url: "https://github.com/phydrus/pyet" preferred-citation: - type: inproceedings + type: journal authors: - family-names: "Vremec" given-names: "Matevz" @@ -21,7 +23,10 @@ preferred-citation: - family-names: "Collenteur" given-names: "Matevz" orcid: "https://orcid.org/0000-0001-7843-1538" - doi: "10.5194/egusphere-egu21-15008" - journal: "EGU General Assembly Conference Abstracts" - year: "2021" - title: "PyEt-a Python package to estimate potential and reference evapotranspiration" \ No newline at end of file + - family-names: "Birk" + given-names: "Steffen" + orcid: "https://orcid.org/0000-0001-7474-3884" + doi: "https://doi.org/10.5194/hess-2022-417" + journal: "Hydrol. Earth Syst. Sci. Discuss. [preprint]" + year: "2023" + title: "Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt" \ No newline at end of file diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..905047e --- /dev/null +++ b/CODE_OF_CONDUCT.md @@ -0,0 +1,128 @@ +# Contributor Covenant Code of Conduct + +## Our Pledge + +We as members, contributors, and leaders pledge to make participation in our +community a harassment-free experience for everyone, regardless of age, body +size, visible or invisible disability, ethnicity, sex characteristics, gender +identity and expression, level of experience, education, socio-economic status, +nationality, personal appearance, race, religion, or sexual identity +and orientation. + +We pledge to act and interact in ways that contribute to an open, welcoming, +diverse, inclusive, and healthy community. + +## Our Standards + +Examples of behavior that contributes to a positive environment for our +community include: + +* Demonstrating empathy and kindness toward other people +* Being respectful of differing opinions, viewpoints, and experiences +* Giving and gracefully accepting constructive feedback +* Accepting responsibility and apologizing to those affected by our mistakes, + and learning from the experience +* Focusing on what is best not just for us as individuals, but for the + overall community + +Examples of unacceptable behavior include: + +* The use of sexualized language or imagery, and sexual attention or + advances of any kind +* Trolling, insulting or derogatory comments, and personal or political attacks +* Public or private harassment +* Publishing others' private information, such as a physical or email + address, without their explicit permission +* Other conduct which could reasonably be considered inappropriate in a + professional setting + +## Enforcement Responsibilities + +Community leaders are responsible for clarifying and enforcing our standards of +acceptable behavior and will take appropriate and fair corrective action in +response to any behavior that they deem inappropriate, threatening, offensive, +or harmful. + +Community leaders have the right and responsibility to remove, edit, or reject +comments, commits, code, wiki edits, issues, and other contributions that are +not aligned to this Code of Conduct, and will communicate reasons for moderation +decisions when appropriate. + +## Scope + +This Code of Conduct applies within all community spaces, and also applies when +an individual is officially representing the community in public spaces. +Examples of representing our community include using an official e-mail address, +posting via an official social media account, or acting as an appointed +representative at an online or offline event. + +## Enforcement + +Instances of abusive, harassing, or otherwise unacceptable behavior may be +reported to the community leaders responsible for enforcement at +@mvremec. +All complaints will be reviewed and investigated promptly and fairly. + +All community leaders are obligated to respect the privacy and security of the +reporter of any incident. + +## Enforcement Guidelines + +Community leaders will follow these Community Impact Guidelines in determining +the consequences for any action they deem in violation of this Code of Conduct: + +### 1. Correction + +**Community Impact**: Use of inappropriate language or other behavior deemed +unprofessional or unwelcome in the community. + +**Consequence**: A private, written warning from community leaders, providing +clarity around the nature of the violation and an explanation of why the +behavior was inappropriate. A public apology may be requested. + +### 2. Warning + +**Community Impact**: A violation through a single incident or series +of actions. + +**Consequence**: A warning with consequences for continued behavior. No +interaction with the people involved, including unsolicited interaction with +those enforcing the Code of Conduct, for a specified period of time. This +includes avoiding interactions in community spaces as well as external channels +like social media. Violating these terms may lead to a temporary or +permanent ban. + +### 3. Temporary Ban + +**Community Impact**: A serious violation of community standards, including +sustained inappropriate behavior. + +**Consequence**: A temporary ban from any sort of interaction or public +communication with the community for a specified period of time. No public or +private interaction with the people involved, including unsolicited interaction +with those enforcing the Code of Conduct, is allowed during this period. +Violating these terms may lead to a permanent ban. + +### 4. Permanent Ban + +**Community Impact**: Demonstrating a pattern of violation of community +standards, including sustained inappropriate behavior, harassment of an +individual, or aggression toward or disparagement of classes of individuals. + +**Consequence**: A permanent ban from any sort of public interaction within +the community. + +## Attribution + +This Code of Conduct is adapted from the [Contributor Covenant][homepage], +version 2.0, available at +https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. + +Community Impact Guidelines were inspired by [Mozilla's code of conduct +enforcement ladder](https://github.com/mozilla/diversity). + +[homepage]: https://www.contributor-covenant.org + +For answers to common questions about this code of conduct, see the FAQ at +https://www.contributor-covenant.org/faq. Translations are available at +https://www.contributor-covenant.org/translations. diff --git a/LICENSE b/LICENSE index 660512e..a067304 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2021 phydrus +Copyright (c) 2023 phydrus Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/README.md b/README.md index 6db5a07..386ddfe 100644 --- a/README.md +++ b/README.md @@ -2,12 +2,12 @@ # pyet: Estimation of Potential Evapotranspiration - - - +[![codacy-coverage-reporter](https://github.com/pyet-org/pyet/actions/workflows/ci.yml/badge.svg)](https://github.com/pyet-org/pyet/actions/workflows/ci.yml) + + [![Codacy Badge](https://app.codacy.com/project/badge/Grade/e49f23e356f441688422ec32cfcf6aaa)](https://www.codacy.com/gh/phydrus/pyet/dashboard?utm_source=github.com&utm_medium=referral&utm_content=phydrus/pyet&utm_campaign=Badge_Grade) [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/e49f23e356f441688422ec32cfcf6aaa)](https://www.codacy.com/gh/phydrus/pyet/dashboard?utm_source=github.com&utm_medium=referral&utm_content=phydrus/pyet&utm_campaign=Badge_Coverage) - + pyet is an open source python package for calculating reference and potential Evapotranspiration (PET) for 1D (pandas.Series) @@ -37,30 +37,34 @@ and 3D (xarray.DataArrray) data. Currently, eighteen methods for calculating dai | Oudin | oudin | ✓ | - | - | - | ✓ | - | - | $^a$ $T_{max}$ and $T_{min}$ can also be provided. $^b$ $RH_{max}$ and $RH_{min}$ can also be provided. $^c$ If actual vapor pressure is provided, RH is not needed. $^d$ Input for radiation can be (1) Net radiation, (2) solar radiation or (3) sunshine hours. If (1), then latitude is not needed. If (1, 3) latitude and elevation is needed. $^e$ One must provide either the atmospheric pressure or elevation. $^f$ The PM method can be used to estimate potential crop evapotranspiration, if leaf area index or crop height data is available. $^g$ The effect of $CO_2$ on stomatal resistance can be included using the formulation of Yang et al. 2019. $^h$ If net radiation is provided, RH and Lat are not needed. $^i$ If method==2, $u_2$, $RH_{min}$ and sunshine hours are required. $^j$ Additional input of $T_{max}$ and $T_{min}$, or $T_{dew}$. $^k$ Input can be $RH$ or actual vapor pressure. $^l$ If method==1, latitude is needed instead of $R_s$. $^m$ $T_{max}$ and $T_{min}$ also needed. - + ## Examples and Documentation Examples of using *pyet* can be found in the example folder: -* [Example 1](/examples/01_example_zamg.ipynb): Estimating PET using pandas.Series +* [Example 1](examples/01_example_zamg.ipynb): Estimating PET using pandas.Series -* [Example 2](/examples/02_example_zamg_netcdf.ipynb): Estimating PET using xarray.DataArray +* [Example 2](examples/02_example_zamg_netcdf.ipynb): Estimating PET using xarray.DataArray -* [Example 3](/examples/03_example_knmi.ipynb): Benchmarking Makkink +* [Example 3](examples/03_example_knmi.ipynb): Benchmarking Makkink against [KNMI data](https://www.knmi.nl/over-het-knmi/about) -* [Example 4](/examples/04_example_coagmet.ipynb): Benchmarking FAO56 +* [Example 4](examples/04_example_coagmet.ipynb): Benchmarking FAO56 against [CoAgMET data](https://coagmet.colostate.edu/) -* [Example 5](/examples/05_example_calibration.ipynb): Calibrating the Romanenko and Abtew method against the PM-FAO56 +* [Example 5](examples/05_example_calibration.ipynb): Calibrating the Romanenko and Abtew method against the PM-FAO56 -* [Example 6](/examples/06_worked_examples_McMahon_etal_2013.ipynb): Worked examples for estimating meteorological +* [Example 6](examples/06_worked_examples_McMahon_etal_2013.ipynb): Worked examples for estimating meteorological variables and potential evapotranspiration after McMahon et al., 2013 -* [Example 7](/examples/07_example_climate_change.ipynb): Example for estimating potential evapotranspiration under - warming and elevated $CO_2$ concentrations following Yang et al., (2019) +* [Example 7](examples/07_example_climate_change.ipynb): Example for estimating potential evapotranspiration under + warming and elevated $CO_2$ concentrations following Yang et al., (2019) + +* [Example 8](examples/08_crop_coefficient.ipynb): Determining the crop coefficient function with Python + +* [Example 9](examples/09_CMIP6_data.ipynb): Estimating PET using CMIP data -* [Example 8](/examples/08_crop_coefficient.ipynb): Determining the crop coefficient function with Python +* [Example 10](examples/10_example_paper.ipynb): Notebook supporting PyEt manuscript Documentation is hosted on [ReadTheDocs](https://pyet.readthedocs.io). @@ -83,7 +87,7 @@ made: * `pyet.makkink` against daily PET estimated with Makkink from The Royal Netherlands Meteorological Institute ([KNMI](https://www.knmi.nl/over-het-knmi/about)). -## Dimensions +## Data dimensions As of version v1.2., *pyet* is compatible with both Pandas.Series and xarray.DataArray, which means you can now estimate potential evapotranspiration for both point and gridded data. @@ -110,16 +114,19 @@ To install in developer mode, use the following syntax: If you use *pyet* in one of your studies, please cite the *pyet* EGU abstract: -* Vremec, M. and Collenteur, R.: *pyet* - a Python package to estimate potential and reference evapotranspiration, EGU - General Assembly 2021, online, 19–30 Apr 2021, EGU21-15008, https://doi.org/10.5194/egusphere-egu21-15008, 2021. +* Vremec, M., Collenteur, R. A., and Birk, S.: Technical note: Improved handling of potential evapotranspiration in +hydrological studies with PyEt, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2022-417, +in review, 2023. ```Reference -@inproceedings{vremec2021pyet, - title={PyEt-a Python package to estimate potential and reference evapotranspiration}, - author={Vremec, Matev{\v{z}} and Collenteur, Raoul}, - booktitle={EGU General Assembly Conference Abstracts}, - pages={EGU21--15008}, - year={2021}, - doi={https://doi.org/10.5194/egusphere-egu21-15008} +@Article{hess-2022-417, + AUTHOR = {Vremec, M. and Collenteur, R. A. and Birk, S.}, + TITLE = {Technical note: Improved handling of potential evapotranspiration in hydrological studies with \textit{PyEt}}, + JOURNAL = {Hydrology and Earth System Sciences Discussions}, + VOLUME = {2023}, + YEAR = {2023}, + PAGES = {1--23}, + URL = {https://hess.copernicus.org/preprints/hess-2022-417/}, + DOI = {10.5194/hess-2022-417} } ``` diff --git a/docs/conf.py b/docs/conf.py index cbde807..9d7fec4 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -12,8 +12,12 @@ # import os import sys +from datetime import date + import requests +year = date.today().strftime("%Y") + sys.path.insert(0, os.path.abspath('.')) # Get a Bibtex reference file from the Zotero group for referencing @@ -39,7 +43,7 @@ # -- Project information ----------------------------------------------------- project = 'pyet' -copyright = '2021, M. Vremec, R.A. Collenteur' +copyright = '{}, M. Vremec, R.A. Collenteur'.format(year) author = 'M. Vremec, R.A. Collenteur' # The full version, including alpha/beta/rc tags @@ -62,9 +66,8 @@ 'sphinx.ext.viewcode', 'IPython.sphinxext.ipython_console_highlighting', # lowercase didn't work 'sphinx.ext.autosectionlabel', - 'nbsphinx', - 'nbsphinx_link', - 'sphinxcontrib.bibtex' + 'sphinxcontrib.bibtex', + 'myst_nb', ] # Create custom bracket style with round brackets @@ -140,3 +143,8 @@ class MyReferenceStyle(AuthorYearReferenceStyle): "python": ("https://docs.python.org/3/", None), "xarray": ("https://docs.xarray.dev/en/stable/", None), } + +# -- myst_nb options ------------------------------------------------------------------ + +nb_execution_allow_errors = True # Allow errors in notebooks, to see the error online +nb_execution_mode = "auto" diff --git a/docs/examples/01_example_zamg.ipynb b/docs/examples/01_example_zamg.ipynb new file mode 100644 index 0000000..8fdf35d --- /dev/null +++ b/docs/examples/01_example_zamg.ipynb @@ -0,0 +1,201 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "999bc8b7-804c-4301-b8c7-5077a38dc06f", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Potential Evapotranspiration from ZAMG data\n", + "*A. Kokimova, November 2021, University of Graz*\n", + "\n", + "Data source: ZAMG - https://data.hub.zamg.ac.at\n", + "\n", + "What is done:\n", + "\n", + "- load the station data from ZAMG\n", + "- estimate potential evapotranspiration\n", + "- plot and store results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7a2ae568-3c3b-44f5-8b82-ab5a99d35d2d", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pyet\n", + "pyet.show_versions()" + ] + }, + { + "cell_type": "markdown", + "id": "da6f3e98-0073-4db9-b763-03beb2611e78", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Loading daily data from ZAMG (Messstationen Tagesdaten)\n", + "\n", + "station: Graz Universität 16412\n", + "\n", + "Selected variables:\n", + "- globalstrahlung (global radiation), J/cm2 needs to be in MJ/m3d, ZAMG abbreviation - strahl\n", + "- arithmetische windgeschwindigkeit (wind speed), m/s, ZAMG abbreviation - vv\n", + "- relative feuchte (relative humidity), %, ZAMG abbreviation - rel\n", + "- lufttemparatur (air temperature) in 2 m, C, ZAMG abbreviation - t\n", + "- lufttemperatur (air temperature) max in 2 m, C, ZAMG abbreviation - tmax\n", + "- lufttemperatur (air temperature) min in 2 m, C, ZAMG abbreviation - tmin\n", + "- latitute and elevation of a station" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "236434b2-3c33-4772-93ec-de0cb7317209", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "#read data\n", + "data_16412 = pd.read_csv('data/example_1/klima_daily.csv', index_col=1, parse_dates=True)\n", + "data_16412" + ] + }, + { + "cell_type": "markdown", + "id": "22ebf3bc-6b9a-4f81-a455-7ca1b51879dd", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Calculate PET for Graz Universität - 16412" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bc5ba933-22c2-4c5b-9ca6-43a4bcdad344", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", + "\n", + "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", + " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", + "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", + "\n", + "lat = 47.077778*np.pi/180 # Latitude of the meteorological station, converting from degrees to radians\n", + "elevation = 367 # meters above sea-level\n", + "\n", + "# Estimate evapotranspiration with four different methods and create a dataframe\n", + "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax,\n", + " tmin=tmin, rh=rh)" + ] + }, + { + "cell_type": "markdown", + "id": "e6e2564c-48ed-46b7-a275-fd17db592456", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9a4582f-219b-47f8-9ed2-dac80720cf55", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "fig, axs = plt.subplots(figsize=(13,4), ncols=2)\n", + "pet_df.plot(ax=axs[0])\n", + "pet_df.cumsum().plot(ax=axs[1], legend=False)\n", + "\n", + "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=12)\n", + "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", + "axs[0].legend(ncol=6, loc=[0,1.])\n", + "for i in (0,1):\n", + " axs[i].set_xlabel(\"Date\", fontsize=12)" + ] + }, + { + "cell_type": "markdown", + "id": "1fe2a55b-838a-4e3a-a621-c5fe55db399a", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## Store results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3c5e47fb-3ec7-4bc9-ad6c-be0edc67ba09", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "#plt.savefig(\"PET_methods.png\", dpi=300)\n", + "#pet_u.to_csv('../evap_16412.csv')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/examples/01_example_zamg.ipynb.nblink b/docs/examples/01_example_zamg.ipynb.nblink deleted file mode 100644 index 42ff858..0000000 --- a/docs/examples/01_example_zamg.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/01_example_zamg.ipynb" -} \ No newline at end of file diff --git a/docs/examples/02_example_zamg_netcdf.ipynb b/docs/examples/02_example_zamg_netcdf.ipynb new file mode 100644 index 0000000..ab0553b --- /dev/null +++ b/docs/examples/02_example_zamg_netcdf.ipynb @@ -0,0 +1,275 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "999bc8b7-804c-4301-b8c7-5077a38dc06f", + "metadata": {}, + "source": [ + "# Potential Evapotranspiration from ZAMG INCA data (NetCDF)\n", + "*M. Vremec, October 2022, University of Graz*\n", + "\n", + "\n", + "What is done:\n", + "\n", + "- load the data from ZAMG\n", + "- estimate potential evapotranspiration\n", + "- plot and store results\n", + "\n", + "Data source: ZAMG - https://data.hub.zamg.ac.at" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7a2ae568-3c3b-44f5-8b82-ab5a99d35d2d", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import xarray as xr\n", + "#import netcdf4 # Needs to be installed\n", + "import pyet\n", + "pyet.show_versions()" + ] + }, + { + "cell_type": "markdown", + "id": "da6f3e98-0073-4db9-b763-03beb2611e78", + "metadata": {}, + "source": [ + "## 1. Loading daily data from ZAMG (INCA hourly NetCDF data)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "236434b2-3c33-4772-93ec-de0cb7317209", + "metadata": {}, + "outputs": [], + "source": [ + "#read data\n", + "xr_ds = xr.open_dataset(\"data/example_2/incal_hourly_20120501T0000_20120930T2300.nc\", \n", + " engine=\"netcdf4\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd56788b-5aed-499b-8a6a-9c6fb68bb2f6", + "metadata": {}, + "outputs": [], + "source": [ + "# Resample and define input meteorological variables\n", + "tmean = xr_ds[\"T2M\"].resample(time=\"1D\").mean()\n", + "tmax = xr_ds[\"T2M\"].resample(time=\"1D\").max()\n", + "tmin = xr_ds[\"T2M\"].resample(time=\"1D\").min()\n", + "rh = xr_ds[\"RH2M\"].resample(time=\"1D\").mean()\n", + "rhmax = xr_ds[\"RH2M\"].resample(time=\"1D\").max()\n", + "rhmin = xr_ds[\"RH2M\"].resample(time=\"1D\").min()\n", + "wind = ((np.abs(xr_ds[\"VV\"]) + np.abs(xr_ds[\"UU\"])) / 2).resample(time=\"1D\").mean()\n", + "rs = xr_ds[\"GL\"].resample(time=\"1D\").mean() * 86400 / 1000000" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f5bb9668-075b-4a8c-99e5-64a998c9c9d5", + "metadata": {}, + "outputs": [], + "source": [ + "# Define latitude and elevation\n", + "lat = tmean.lat * np.pi / 180 \n", + "elevation = lat / lat * 350" + ] + }, + { + "cell_type": "markdown", + "id": "22ebf3bc-6b9a-4f81-a455-7ca1b51879dd", + "metadata": {}, + "source": [ + "## 2. Calculate PET" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "542a2a7a-7354-4ce7-a7d7-644f8f650238", + "metadata": {}, + "outputs": [], + "source": [ + "lat1 = 80 * np.pi / 180" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b8859a2-37e3-40db-afc1-01b449adfc35", + "metadata": {}, + "outputs": [], + "source": [ + "# Estimate evapotranspiration with nine different methods \n", + "pet_penman = pyet.penman(tmean, wind, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", + "pet_pt = pyet.priestley_taylor(tmean, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", + "pet_makkink = pyet.makkink(tmean, rs, elevation=elevation)\n", + "pet_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", + "pet_hamon = pyet.hamon(tmean, lat=lat, method=1)\n", + "pet_oudin = pyet.oudin(tmean, lat=lat)\n", + "pet_haude = pyet.haude(tmax, rh)\n", + "pet_turc = pyet.turc(tmean, rs, rh)\n", + "pet_har = pyet.hargreaves(tmean, tmax, tmin, lat)" + ] + }, + { + "cell_type": "markdown", + "id": "e6e2564c-48ed-46b7-a275-fd17db592456", + "metadata": {}, + "source": [ + "## 3. Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14c613f4-edc1-4472-8ab3-5ed0e1d373f5", + "metadata": {}, + "outputs": [], + "source": [ + "fig, axs = plt.subplots(ncols=2, figsize=(12,3))\n", + "pet_penman[:,2,2].plot(ax=axs[0], label=\"Penman\")\n", + "pet_pt[:,2,2].plot(ax=axs[0], label=\"Priestley-Taylor\")\n", + "pet_makkink[:,2,2].plot(ax=axs[0], label=\"Makkink\")\n", + "pet_fao56[:,2,2].plot(ax=axs[0], label=\"FAO56\")\n", + "pet_hamon[:,2,2].plot(ax=axs[0], label=\"Hamon\")\n", + "pet_oudin[:,2,2].plot(ax=axs[0], label=\"Oudin\")\n", + "pet_haude[:,2,2].plot(ax=axs[0], label=\"Haude\")\n", + "pet_turc[:,2,2].plot(ax=axs[0], label=\"Turc\")\n", + "pet_har[:,2,2].plot(ax=axs[0], label=\"Hargreaves\")\n", + "axs[0].legend()\n", + "\n", + "pet_penman[:,2,2].cumsum().plot(ax=axs[1], label=\"Penman\")\n", + "pet_pt[:,2,2].cumsum().plot(ax=axs[1], label=\"Priestley-Taylor\")\n", + "pet_makkink[:,2,2].cumsum().plot(ax=axs[1], label=\"Makkink\")\n", + "pet_fao56[:,2,2].cumsum().plot(ax=axs[1], label=\"FAO56\")\n", + "pet_hamon[:,2,2].cumsum().plot(ax=axs[1], label=\"Hamon\")\n", + "pet_oudin[:,2,2].cumsum().plot(ax=axs[1], label=\"Oudin\")\n", + "pet_haude[:,2,2].cumsum().plot(ax=axs[1], label=\"Haude\")\n", + "pet_turc[:,2,2].cumsum().plot(ax=axs[1], label=\"Turc\")\n", + "pet_har[:,2,2].cumsum().plot(ax=axs[1], label=\"Hargreaves\")\n", + "axs[1].legend()" + ] + }, + { + "cell_type": "markdown", + "id": "d6697f56-83ef-49f4-8037-9235f6e88a51", + "metadata": {}, + "source": [ + "## 4. Compare point with pandas.Series vs. point from xarray.DataArray" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b70386d-18f3-4485-bdc1-8969630018b8", + "metadata": {}, + "outputs": [], + "source": [ + "tmeans = xr_ds[\"T2M\"].resample(time=\"1D\").mean()[:, 4, 4].to_series()\n", + "tmaxs = xr_ds[\"T2M\"].resample(time=\"1D\").max()[:, 4, 4].to_series()\n", + "tmins = xr_ds[\"T2M\"].resample(time=\"1D\").min()[:, 4, 4].to_series()\n", + "rhs = xr_ds[\"RH2M\"].resample(time=\"1D\").mean()[:, 4, 4].to_series()\n", + "rhmaxs = xr_ds[\"RH2M\"].resample(time=\"1D\").max()[:, 4, 4].to_series()\n", + "rhmins = xr_ds[\"RH2M\"].resample(time=\"1D\").min()[:, 4, 4].to_series()\n", + "winds = ((np.abs(xr_ds[\"VV\"]) + np.abs(xr_ds[\"UU\"])) / 2).resample(time=\"1D\").mean()[:, 4, 4].to_series()\n", + "rss = (xr_ds[\"GL\"].resample(time=\"1D\").mean() * 86400 / 1000000)[:, 4, 4].to_series()\n", + "lats = float(lat[4, 4])\n", + "elevations = float(elevation[4, 4])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ef26699-5611-4c93-bb26-4fdef1138eec", + "metadata": {}, + "outputs": [], + "source": [ + "# Estimate evapotranspiration with nine different methods with Pandas.Series\n", + "pet_penmans = pyet.penman(tmeans, winds, rs=rss, elevation=elevations, lat=lats, tmax=tmaxs, tmin=tmins, rh=rhs)\n", + "pet_pts = pyet.priestley_taylor(tmeans, rs=rss, elevation=elevations, lat=lats, tmax=tmaxs, tmin=tmins, rh=rhs)\n", + "pet_makkinks = pyet.makkink(tmeans, rss, elevation=elevations)\n", + "pet_fao56s = pyet.pm_fao56(tmeans, winds, rs=rss, elevation=elevations, lat=lats, tmax=tmaxs, tmin=tmins, rh=rhs)\n", + "pet_hamons = pyet.hamon(tmeans, lat=lats, method=1)\n", + "pet_oudins = pyet.oudin(tmeans, lat=lats)\n", + "pet_haudes = pyet.haude(tmaxs, rhs)\n", + "pet_turcs = pyet.turc(tmeans, rss, rhs)\n", + "pet_hars = pyet.hargreaves(tmeans, tmaxs, tmins, lats)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7165b896-c86e-460f-a592-874f2381f7d6", + "metadata": {}, + "outputs": [], + "source": [ + "fm = \"\"\"\n", + " ABC\n", + " DEF\n", + " GHI\n", + " \"\"\"\n", + "fig,axs = plt.subplot_mosaic(mosaic=fm, figsize=(12,8))\n", + "axs[\"A\"].scatter(pet_penman[:,4,4].values, pet_penmans.values)\n", + "axs[\"B\"].scatter(pet_pt[:,4,4].values, pet_pts.values)\n", + "axs[\"C\"].scatter(pet_makkink[:,4,4].values, pet_makkinks.values)\n", + "axs[\"D\"].scatter(pet_fao56[:,4,4].values, pet_fao56s.values)\n", + "axs[\"E\"].scatter(pet_hamon[:,4,4].values, pet_hamons.values)\n", + "axs[\"F\"].scatter(pet_oudin[:,4,4].values, pet_oudins.values)\n", + "axs[\"G\"].scatter(pet_haude[:,4,4].values, pet_haudes.values)\n", + "axs[\"H\"].scatter(pet_turc[:,4,4].values, pet_turcs.values)\n", + "axs[\"I\"].scatter(pet_har[:,4,4].values, pet_hars.values)\n", + "for i in axs.keys():\n", + " axs[i].plot([0,7], [0,7])" + ] + }, + { + "cell_type": "markdown", + "id": "1fe2a55b-838a-4e3a-a621-c5fe55db399a", + "metadata": {}, + "source": [ + "## 5. Store results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3c5e47fb-3ec7-4bc9-ad6c-be0edc67ba09", + "metadata": {}, + "outputs": [], + "source": [ + "#pet_pt.to_netcdf('../pe_pt_INCA.csv')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/examples/02_example_zamg_netcdf.ipynb.nblink b/docs/examples/02_example_zamg_netcdf.ipynb.nblink deleted file mode 100644 index 4e3139e..0000000 --- a/docs/examples/02_example_zamg_netcdf.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/02_example_zamg_netcdf.ipynb" -} \ No newline at end of file diff --git a/docs/examples/03_example_knmi.ipynb b/docs/examples/03_example_knmi.ipynb new file mode 100644 index 0000000..2e936a5 --- /dev/null +++ b/docs/examples/03_example_knmi.ipynb @@ -0,0 +1,292 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d0959a4c", + "metadata": {}, + "source": [ + "# Potential Evapotranspiration from KNMI data\n", + "*R.A. Collenteur, Eawag, 2023*\n", + "\n", + "Data source: KNMI - https://dataplatform.knmi.nl/\n", + "\n", + "In this notebook it is shown how to compute (potential) evapotranspiration from meteorological data using PyEt. Meteorological data is observed by the KNMI at De Bilt in the Netherlands." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f8c6cab3", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import pyet\n", + "pyet.show_versions()" + ] + }, + { + "cell_type": "markdown", + "id": "61cb9b9e", + "metadata": {}, + "source": [ + "## 1. Load KNMI Data\n", + "\n", + "We first load the raw meteorological data observed by the KNMI at De Bilt in the Netherlands. This datafile contains a lot of different variables, please see the end of the notebook for an explanation of all the variables. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cbc6c337", + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.read_csv(\"data/example_3/etmgeg_260.txt\", skiprows=46, delimiter=\",\", \n", + " skipinitialspace=True, index_col=\"YYYYMMDD\", parse_dates=True).loc[\"2018\",:]\n", + "data.head()" + ] + }, + { + "cell_type": "markdown", + "id": "be888ed3", + "metadata": {}, + "source": [ + "## 2. Estimating potential evapotranspiration\n", + "\n", + "Now that we have the input data, we can estimate potential evapotranspiration with different estimation methods. Here we choose the Penman, Priestley-Taylor, Makkink, and Oudin methods. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "abe8a230", + "metadata": {}, + "outputs": [], + "source": [ + "# Preprocess the input data\n", + "meteo = pd.DataFrame({\"tmean\":data.TG/10, \"tmax\":data.TX/10, \"tmin\":data.TN/10, \n", + " \"rh\":data.UG, \"wind\":data.FG/10, \"rs\":data.Q/100})\n", + "tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", + "pressure = data.PG / 100 # to kPa\n", + "wind = data.FG / 10 # to m/s\n", + "lat = 0.91 # Latitude of the meteorological station\n", + "elevation = 4 # meters above sea-level \n", + "\n", + "# Estimate evapotranspiration with four different methods\n", + "pet_penman = pyet.penman(tmean, wind, rs=rs, elevation=4, lat=0.91, tmax=tmax, tmin=tmin, rh=rh)\n", + "pet_pt = pyet.priestley_taylor(tmean, rs=rs, elevation=4, lat=0.91, tmax=tmax, tmin=tmin, rh=rh)\n", + "pet_makkink = pyet.makkink(tmean, rs, elevation=4, pressure=pressure)\n", + "pet_oudin = pyet.oudin(tmean, lat=0.91)" + ] + }, + { + "cell_type": "markdown", + "id": "578f8ac2", + "metadata": {}, + "source": [ + "## 3. Plot the results\n", + "\n", + "We plot the cumulative sums to compare the different estimation methods." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c5a8008", + "metadata": {}, + "outputs": [], + "source": [ + "fig, axs = plt.subplots(figsize=(14,3.5), ncols=2)\n", + "\n", + "pet = [pet_penman, pet_pt, pet_makkink, pet_makkink]\n", + "names = [\"Penman\", \"Priestley-Taylor\", \"Makkink - PyEt\", \"Oudin\"]\n", + "\n", + "for df, name in zip(pet, names):\n", + " axs[0].plot(df,label=name)\n", + " axs[1].plot(df.cumsum(),label=name)\n", + "\n", + "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=16)\n", + "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", + "\n", + "for i in (0,1):\n", + " axs[i].set_xlabel(\"Date\", fontsize=12)\n", + " axs[i].legend(loc=2, fontsize=14)\n", + " axs[i].tick_params(\"both\", direction=\"in\", labelsize=14)\n", + "plt.tight_layout()\n", + "\n", + "#plt.savefig(\"Figure1.png\", dpi=300)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "75dacdc4", + "metadata": {}, + "source": [ + "## 4. Comparison: pyet Makkink vs KNMI Makkink\n", + "\n", + "The KNMI also provides Makkink potential evapotranspiration data (column EV24). We can now compare the results from Pyet and the KNMI to confirm that these are roughly the same. Pyet also has a method `makkink_knmi` that calculates exactly the same Makkink evaporation as the KNMI but that is only suitable for the Netherlands." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "95c6b234", + "metadata": {}, + "outputs": [], + "source": [ + "pet_knmi = data.EV24 / 10 # Makkink potential evaporation computen by the KNMI for comparison\n", + "pet_makkink_knmi = pyet.makkink_knmi(tmean, rs).round(1) # same as pet_knmi (if rounded up to 1 decimal) but calculated from tmean and rs\n", + "\n", + "# Plot the two series against each other\n", + "_, ax = plt.subplots(1, 2, figsize=(9,4), sharex=True, sharey=True)\n", + "ax[0].scatter(pet_makkink, pet_knmi, s=15, color=\"C0\")\n", + "ax[0].plot([0,6],[0,6], color=\"red\", label=\"1:1 line\")\n", + "ax[0].set_xlabel(\"pyet-Makkink 'EV24' [mm]\")\n", + "ax[0].grid()\n", + "\n", + "ax[1].scatter(pet_makkink_knmi, pet_knmi, s=15, color=\"C1\")\n", + "ax[1].plot([0,6],[0,6], color=\"red\")\n", + "ax[1].set_xlabel(\"pyet-Makkink_KNMI [mm]\")\n", + "ax[1].grid()\n", + "\n", + "ax[0].set_ylabel(\"KNMI-Makkink [mm]\")\n", + "ax[0].legend(loc=(0,1), frameon=False)\n" + ] + }, + { + "cell_type": "markdown", + "id": "a51c36d1", + "metadata": {}, + "source": [ + "## 5. Estimation of PET - all methods" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2a2b17d3", + "metadata": {}, + "outputs": [], + "source": [ + "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax,\n", + " tmin=tmin, rh=rh)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "055e90d1", + "metadata": {}, + "outputs": [], + "source": [ + "fig, axs = plt.subplots(figsize=(13,4), ncols=2)\n", + "pet_df.plot(ax=axs[0])\n", + "pet_df.cumsum().plot(ax=axs[1], legend=False)\n", + "\n", + "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=12)\n", + "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", + "axs[0].legend(ncol=6, loc=[0,1.])\n", + "for i in (0,1):\n", + " axs[i].set_xlabel(\"Date\", fontsize=12)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e55de8b", + "metadata": {}, + "outputs": [], + "source": [ + "#plt.savefig(\"PET_methods.png\", dpi=300)" + ] + }, + { + "cell_type": "markdown", + "id": "815addc4", + "metadata": {}, + "source": [ + "## References\n", + "\n", + "Column description of the KNMI data\n", + "\n", + "- DDVEC = Vector mean wind direction in degrees (360=north, 90=east, 180=south, 270=west, 0=calm/variable)\n", + "- FHVEC = Vector mean windspeed (in 0.1 m/s)\n", + "- FG = Daily mean windspeed (in 0.1 m/s) \n", + "- FHX = Maximum hourly mean windspeed (in 0.1 m/s)\n", + "- FHXH = Hourly division in which FHX was measured\n", + "- FHN = Minimum hourly mean windspeed (in 0.1 m/s)\n", + "- FHNH = Hourly division in which FHN was measured\n", + "- FXX = Maximum wind gust (in 0.1 m/s)\n", + "- FXXH = Hourly division in which FXX was measured\n", + "- TG = Daily mean temperature in (0.1 degrees Celsius)\n", + "- TN = Minimum temperature (in 0.1 degrees Celsius)\n", + "- TNH = Hourly division in which TN was measured\n", + "- TX = Maximum temperature (in 0.1 degrees Celsius)\n", + "- TXH = Hourly division in which TX was measured\n", + "- T10N = Minimum temperature at 10 cm above surface (in 0.1 degrees Celsius)\n", + "- T10NH = 6-hourly division in which T10N was measured; 6=0-6 UT, 12=6-12 UT, 18=12-18 UT, 24=18-24 UT \n", + "- SQ = Sunshine duration (in 0.1 hour) calculated from global radiation (-1 for <0.05 hour)\n", + "- SP = Percentage of maximum potential sunshine duration\n", + "- Q = Global radiation (in J/cm2)\n", + "- DR = Precipitation duration (in 0.1 hour)\n", + "- RH = Daily precipitation amount (in 0.1 mm) (-1 for <0.05 mm)\n", + "- RHX = Maximum hourly precipitation amount (in 0.1 mm) (-1 for <0.05 mm)\n", + "- RHXH = Hourly division in which RHX was measured\n", + "- PG = Daily mean sea level pressure (in 0.1 hPa) calculated from 24 hourly values\n", + "- PX = Maximum hourly sea level pressure (in 0.1 hPa)\n", + "- PXH = Hourly division in which PX was measured\n", + "- PN = Minimum hourly sea level pressure (in 0.1 hPa)\n", + "- PNH = Hourly division in which PN was measured\n", + "- VVN = Minimum visibility; 0: <100 m, 1:100-200 m, 2:200-300 m,..., 49:4900-5000 m, 50:5-6 km, 56:6-7 km, 57:7-8 km,..., 79:29-30 km, 80:30-35 km, 81:35-40 km,..., 89: >70 km)\n", + "- VVNH = Hourly division in which VVN was measured\n", + "- VVX = Maximum visibility; 0: <100 m, 1:100-200 m, 2:200-300 m,..., 49:4900-5000 m, 50:5-6 km, 56:6-7 km, 57:7-8 km,..., 79:29-30 km, 80:30-35 km, 81:35-40 km,..., 89: >70 km)\n", + "- VVXH = Hourly division in which VVX was measured\n", + "- NG = Mean daily cloud cover (in octants, 9=sky invisible)\n", + "- UG = Daily mean relative atmospheric humidity (in percents)\n", + "- UX = Maximum relative atmospheric humidity (in percents)\n", + "- UXH = Hourly division in which UX was measured\n", + "- UN = Minimum relative atmospheric humidity (in percents)\n", + "- UNH = Hourly division in which UN was measured\n", + "- EV24 = Potential evapotranspiration (Makkink) (in 0.1 mm)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "df028060-9d5f-4616-9797-d44e6b66002b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + }, + "vscode": { + "interpreter": { + "hash": "8a365f246fd2b6cc3f433897ea78f6113fbca3a5aebe59945b06a3e6c75c5dde" + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/examples/03_example_knmi.ipynb.nblink b/docs/examples/03_example_knmi.ipynb.nblink deleted file mode 100644 index 3f219fe..0000000 --- a/docs/examples/03_example_knmi.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/03_example_knmi.ipynb" -} \ No newline at end of file diff --git a/docs/examples/04_example_coagmet.ipynb b/docs/examples/04_example_coagmet.ipynb new file mode 100644 index 0000000..1f916cc --- /dev/null +++ b/docs/examples/04_example_coagmet.ipynb @@ -0,0 +1,131 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Potential Evapotranspiration from CoAgMET data\n", + "\n", + "*M. Vremec, University of Graz, 2021*\n", + "\n", + "In this notebook it is shown how to compute (reference) evapotranspiration ($ET_0$) from meteorological data observed by the Colorado State University (CoAgMET) at Holyoke in Colorado, USA. The notebook also includes a comparison between $ET_0$ estimated using *pyet* (FAO56) and $ET_0$ available from CoAgMET. According to CoAgMET documentation, the provided reference evapotranspiration is estimated using ASCE reference evapotranspiration for short reference grass (Wright, 2000), which corresponds to the FAO-56 method used with *pyet*.\n", + "\n", + "Source: https://coagmet.colostate.edu/station/selector" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import pyet as pyet\n", + "pyet.show_versions()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Load CoAgMET Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.read_csv(\"data/example_4/et_coagmet.txt\", parse_dates=True, index_col=\"date\")\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "et0_coagmet = data[\"et_asce0\"]\n", + "\n", + "meteo = pd.DataFrame({\"tmean\":data[\"tavg\"], \n", + " \"tmax\":data[\"tmax\"],\n", + " \"tmin\":data[\"tmin\"], \n", + " \"rhmax\":data[\"rhmax\"]*100,\n", + " \"rhmin\":data[\"rhmin\"]*100, \n", + " \"u2\":data[\"windrun\"]*1000/86400,\n", + " \"rs\":data[\"solar\"]*86400/1000000})\n", + "\n", + "tmean, tmax, tmin, rhmax, rhmin, wind, rs = [meteo[col] for col in meteo.columns]\n", + "lat = 40.49 * np.pi / 180" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Comparison: pyet FAO56 vs CoAgMET ASCE " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "et0_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=1138, lat=lat, \n", + " tmax=tmax, tmin=tmin, rhmax=rhmax, rhmin=rhmin)\n", + "\n", + "et0_fao56.plot()\n", + "et0_coagmet.plot();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Plot the results\n", + "\n", + "We now plot the evaporation time series against each other to see how these compare. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.scatter(et0_fao56, et0_coagmet)\n", + "plt.plot([0,15],[0,15], color=\"red\", label=\"1:1 line\")\n", + "plt.legend()\n", + "plt.xlabel(\"ET0 pyet-FAO56 [mm]\")\n", + "plt.ylabel(\"ET0 CoAgMET-ASCE [mm]\");" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/docs/examples/04_example_coagmet.ipynb.nblink b/docs/examples/04_example_coagmet.ipynb.nblink deleted file mode 100644 index de45c9d..0000000 --- a/docs/examples/04_example_coagmet.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/04_example_coagmet.ipynb" -} \ No newline at end of file diff --git a/docs/examples/05_example_calibration.ipynb b/docs/examples/05_example_calibration.ipynb new file mode 100644 index 0000000..55fa032 --- /dev/null +++ b/docs/examples/05_example_calibration.ipynb @@ -0,0 +1,231 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Calibration of potential evapotranspiration methods\n", + "*M. Vremec, R.A. Collenteur University of Graz, 2021*\n", + "\n", + "In this notebook it is shown how to calibrate various (potential) evapotranspiration (PET) equations, using a linear regression relationship between daily potential evapotranspiration obtained with the FAO-56 equation and daily PET estimates obtained with the alternative methods. This notebook requires Scipy and SkLearn python packages to run." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from scipy.optimize import least_squares\n", + "from sklearn.metrics import mean_squared_error\n", + "\n", + "import pyet as pyet" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Load KNMI Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.read_csv(\"data/example_3/etmgeg_260.txt\", skiprows=46, delimiter=\",\", \n", + " skipinitialspace=True, index_col=\"YYYYMMDD\", parse_dates=True).loc[\"2018\",:]\n", + "data.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.Estimation of potential evapotranspiration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# define meteorological variables needed for PE estimation\n", + "meteo = pd.DataFrame({\"tmean\":data.TG/10, \"tmax\":data.TX/10, \"tmin\":data.TN/10, \"rh\":data.UG, \"wind\":data.FG/10, \"rs\":data.Q/100})\n", + "tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", + "pressure = data.PG / 100 # to kPa\n", + "wind = data.FG/10 # to m/s\n", + "lat = 0.91 # [rad]\n", + "elevation = 4 \n", + "\n", + "pet_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, lat=lat, \n", + " tmax=tmax, tmin=tmin, rh=rh) # FAO-56 method\n", + "pet_romanenko = pyet.romanenko(tmean, rh) # Romanenko method\n", + "pet_abtew = pyet.abtew(tmean, rs) # Abtew method" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The model performance of the Abtew and Romanenko method will be evaluated using the root mean square error (RMSE), as implemented in SkLearn’s mean_squared_error method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pet_fao56.plot()\n", + "pet_romanenko.plot()\n", + "pet_abtew.plot()\n", + "plt.ylabel(\"PE [mm/day]\")\n", + "print(\"RMSE(Romanenko) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_romanenko, squared=False)))\n", + "print(\"RMSE(Abtew) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_abtew, squared=False)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Calibration of different PE equations\n", + "\n", + "The least squares approach is applied to estimate the parameters in the PE equations, by minimizing the sum of the residuals between the simulated (Abtew and Romanenko) and observed (FAO-56) data. The minimization of the objective function is done using the Trust Region Reflective algorithm, as implemented in Scipy’s least squares method." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3.1 Romanenko method" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Define function for computing residuals\n", + "def cal_romanenko(k, obs):\n", + " return pyet.romanenko(tmean, rh, k)-obs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# estimate k in the Romanenko method\n", + "x0 = 4.5 # initial estimate of parameter\n", + "res_1 = least_squares(cal_romanenko, x0, args=[pet_fao56])\n", + "res_1.x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Compute RMSE using the calibrated value of k\n", + "pet_romanenko_cal = pyet.romanenko(tmean, rh, k=res_1.x)\n", + "print(\"RMSE(Romanenko) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_romanenko_cal, squared=False)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "RMSE (calibrated) = 0.546 < RMSE (uncalibrated) = 0.694" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3.2 Abtew method" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Define function for computing residuals and initial estimate of parameters\n", + "def cal_abtew(k,obs):\n", + " return pyet.abtew(tmean, rs, k)-obs\n", + "x0 = 0.53" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# estimate k in the Romanenko method\n", + "res_2 = least_squares(cal_abtew, x0, args=[pet_fao56])\n", + "res_2.x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pet_abtew_cali = pyet.abtew(tmean, rs, res_2.x)\n", + "print(\"RMSE(Abtew) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_abtew_cali, squared=False)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "RMSE (calibrated) = 0.613 < RMSE (uncalibrated) = 0.741" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pet_fao56.plot()\n", + "pet_romanenko_cal.plot()\n", + "pet_abtew_cali.plot()\n", + "plt.ylabel(\"PET [mm/d]\");" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/docs/examples/05_example_calibration.ipynb.nblink b/docs/examples/05_example_calibration.ipynb.nblink deleted file mode 100644 index 1e03dc7..0000000 --- a/docs/examples/05_example_calibration.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/05_example_calibration.ipynb" -} \ No newline at end of file diff --git a/examples/06_worked_examples_McMahon_etal_2013.ipynb b/docs/examples/06_worked_examples_McMahon_etal_2013.ipynb similarity index 69% rename from examples/06_worked_examples_McMahon_etal_2013.ipynb rename to docs/examples/06_worked_examples_McMahon_etal_2013.ipynb index 551ef41..a8eacb3 100644 --- a/examples/06_worked_examples_McMahon_etal_2013.ipynb +++ b/docs/examples/06_worked_examples_McMahon_etal_2013.ipynb @@ -5,7 +5,8 @@ "id": "133f830b-bbd2-4801-b436-534f851697b0", "metadata": {}, "source": [ - "# 6. Worked example for estimating meteorological variables and potential evapotranspiration\n", + "# Worked example for estimating meteorological variables and potential evapotranspiration\n", + "\n", "*M. Vremec, October 2022, University of Graz*\n", "\n", "What is done:\n", @@ -18,21 +19,10 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "da9d427a-e154-42e2-b3e2-871dfb419717", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python version: 3.9.13 (main, Oct 13 2022, 21:23:06) [MSC v.1916 64 bit (AMD64)]\n", - "Numpy version: 1.21.5\n", - "Pandas version: 1.4.4\n", - "Pyet version: 1.2.0b\n" - ] - } - ], + "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", @@ -57,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "96f0a077-5323-4cff-b553-9c4106ec149f", "metadata": {}, "outputs": [], @@ -85,21 +75,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "ca420c4a-c682-452e-b0fa-44fa87dc815a", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Tmean = 11.5 vs 11.5 °C\n" - ] - } - ], + "outputs": [], "source": [ "tmean = (tmax+tmin)/2\n", - "print(f\"Tmean = {float(tmean)} vs 11.5 °C\")" + "print(f\"Tmean = {float(tmean.iloc[0])} vs 11.5 °C\")" ] }, { @@ -114,24 +96,15 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "fa796288-9a74-49a5-9a54-c813cfde5e1f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Saturation vapour pressure at Tmax: 2.487 vs 2.4870 kPa\n", - "Saturation vapour pressure at Tmin: 0.7056 vs 0.7056 kPa\n" - ] - } - ], + "outputs": [], "source": [ "esmax = pyet.calc_e0(tmax)\n", - "print(f\"Saturation vapour pressure at Tmax: {round(float(esmax),4)} vs 2.4870 kPa\")\n", + "print(f\"Saturation vapour pressure at Tmax: {round(float(esmax.iloc[0]),4)} vs 2.4870 kPa\")\n", "esmin = pyet.calc_e0(tmin)\n", - "print(f\"Saturation vapour pressure at Tmin: {round(float(esmin),4)} vs 0.7056 kPa\")" + "print(f\"Saturation vapour pressure at Tmin: {round(float(esmin.iloc[0]),4)} vs 0.7056 kPa\")" ] }, { @@ -146,21 +119,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "6040fdd6-47d5-41b3-9601-352f55e95eae", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Saturation vapour pressure : 1.5963 vs 1.5963 kPa\n" - ] - } - ], + "outputs": [], "source": [ "es = pyet.calc_es(tmean, tmax, tmin)\n", - "print(f\"Saturation vapour pressure : {round(float(es),4)} vs 1.5963 kPa\")" + "print(f\"Saturation vapour pressure : {round(float(es.iloc[0]),4)} vs 1.5963 kPa\")" ] }, { @@ -175,21 +140,13 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "6e0ac985-1aa3-4862-96c8-cd1c76d586a8", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Slope of saturation vapour pressure at Tmean : 0.0898 vs 0.0898 kPa/°C\n" - ] - } - ], + "outputs": [], "source": [ "dlt = pyet.calc_vpc(tmean)\n", - "print(f\"Slope of saturation vapour pressure at Tmean : {round(float(dlt),4)} vs 0.0898 kPa/°C\")" + "print(f\"Slope of saturation vapour pressure at Tmean : {round(float(dlt.iloc[0]),4)} vs 0.0898 kPa/°C\")" ] }, { @@ -204,18 +161,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "f7e7a0ab-f8c6-4c88-83bb-14102c2710a8", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Atmospheric pressure : 95.01027 vs 95.01027 kPa\n" - ] - } - ], + "outputs": [], "source": [ "pressure = pyet.calc_press(ele)\n", "print(f\"Atmospheric pressure : {round(float(pressure),5)} vs 95.01027 kPa\")" @@ -233,18 +182,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "91837049-df62-4d76-ad47-b6ada18174d2", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Psychrometric constant : 0.0632 vs 0.0632 kPa/°C\n" - ] - } - ], + "outputs": [], "source": [ "gamma = pyet.calc_psy(pressure)\n", "print(f\"Psychrometric constant : {round(float(gamma),4)} vs 0.0632 kPa/°C\")" @@ -260,20 +201,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "56a0e566-868e-4f8c-bd71-80ee6e0b852e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Day of Year (DoY): 202 vs 202\n" - ] - } - ], - "source": [ - "doy = pyet.day_of_year(tmean.index)\n", + "outputs": [], + "source": [ + "doy = pyet.day_of_year(tmean.index).iloc[0]\n", "print(f\"Day of Year (DoY): {int(doy)} vs 202\")" ] }, @@ -289,18 +222,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "68717078-256a-4713-bcac-6ab22badbcbc", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Inverse relative distance Earth to Sun : 0.9688 vs 0.9688\n" - ] - } - ], + "outputs": [], "source": [ "dr = pyet.relative_distance(doy)\n", "print(f\"Inverse relative distance Earth to Sun : {round(float(dr),4)} vs 0.9688\")" @@ -318,18 +243,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "b4900e13-cbc1-4992-aa55-b0bb0f747398", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Solar declination : 0.3557 vs 0.3557\n" - ] - } - ], + "outputs": [], "source": [ "sd = pyet.solar_declination(doy)\n", "print(f\"Solar declination : {round(float(sd),4)} vs 0.3557\")" @@ -347,18 +264,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "104ddee5-84c3-441c-ab60-20bbf846dbfe", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Sunset hour angle : 1.4063 vs 1.4063\n" - ] - } - ], + "outputs": [], "source": [ "omega = pyet.sunset_angle(sd, lat)\n", "print(f\"Sunset hour angle : {round(float(omega), 4)} vs 1.4063\")" @@ -376,20 +285,12 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "455c4b2b-e3bf-4ae2-a2e0-6a0edade3403", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Maximum daylight hours : 10.7431 vs 10.7431 hours\n" - ] - } - ], - "source": [ - "nn = pyet.daylight_hours(tmean.index, lat)\n", + "outputs": [], + "source": [ + "nn = pyet.daylight_hours(tmean.index, lat)[0]\n", "print(f\"Maximum daylight hours : {round(float(nn),4)} vs 10.7431 hours\")" ] }, @@ -405,21 +306,13 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "de761110-f9ce-4018-9693-d7092ea5de33", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Extraterrestrial radiation : 23.6182 vs 23.6182 MJ m-2 day-1\n" - ] - } - ], + "outputs": [], "source": [ "ra = pyet.extraterrestrial_r(tmean.index, lat)\n", - "print(f\"Extraterrestrial radiation : {round(float(ra),4)} vs 23.6182 MJ m-2 day-1\")" + "print(f\"Extraterrestrial radiation : {round(float(ra[0]),4)} vs 23.6182 MJ m-2 day-1\")" ] }, { @@ -434,21 +327,13 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "b5621a9b-b342-474c-a2dc-6e4cec251b06", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Clear Sky Radiation : 17.9716 vs 17.9716 MJ m-2 day-1\n" - ] - } - ], + "outputs": [], "source": [ "rso = pyet.calc_rso(ra, ele)\n", - "print(f\"Clear Sky Radiation : {round(float(rso), 4)} vs 17.9716 MJ m-2 day-1\")" + "print(f\"Clear Sky Radiation : {round(float(rso[0]), 4)} vs 17.9716 MJ m-2 day-1\")" ] }, { @@ -463,21 +348,13 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "4afe823a-9aa8-48c7-9df5-22a918982133", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Incoming solar radiation : 17.194 vs 17.1940 MJ m-2 day-1\n" - ] - } - ], + "outputs": [], "source": [ "rs_sol = pyet.calc_rad_sol_in(n, lat, as1=0.23)\n", - "print(f\"Incoming solar radiation : {round(float(rs_sol),4)} vs 17.1940 MJ m-2 day-1\")" + "print(f\"Incoming solar radiation : {round(float(rs_sol.iloc[0]),4)} vs 17.1940 MJ m-2 day-1\")" ] }, { @@ -492,22 +369,14 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "b3f75255-36da-4389-b6de-3c191737833f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net longwave radiation : 7.1743 vs 7.1784 MJ m-2 day-1\n" - ] - } - ], + "outputs": [], "source": [ "rnl = pyet.calc_rad_long(rs_sol, tmean.index, tmin=tmin, tmax=tmax, \n", " rhmax=rhmax, rhmin=rhmin, lat=lat, elevation=ele)\n", - "print(f\"Net longwave radiation : {round(float(rnl),4)} vs 7.1784 MJ m-2 day-1\")" + "print(f\"Net longwave radiation : {round(float(rnl.iloc[0]),4)} vs 7.1784 MJ m-2 day-1\")" ] }, { @@ -522,21 +391,13 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "ada00a78-9dac-4f6f-b7f9-01b0b3bfca48", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net incoming shortwave radiation : 13.2393 vs 13.2393 MJ m-2 day-1\n" - ] - } - ], + "outputs": [], "source": [ "rns = pyet.calc_rad_short(rs_sol)\n", - "print(f\"Net incoming shortwave radiation : {round(float(rns),4)} vs 13.2393 MJ m-2 day-1\")" + "print(f\"Net incoming shortwave radiation : {round(float(rns[0]),4)} vs 13.2393 MJ m-2 day-1\")" ] }, { @@ -551,80 +412,104 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "44f1cce9-982a-410f-87ec-29dc8728231e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Net radiation : 6.065 vs 6.0610\n" - ] - } - ], + "outputs": [], "source": [ "rn = pyet.calc_rad_net(tmean, tmin=tmin, tmax=tmax, n=n, lat=lat, \n", " rhmax=rhmax, rhmin=rhmin, elevation=ele, as1=0.23)\n", - "print(f\"Net radiation : {round(float(rn),4)} vs 6.0610\")" + "print(f\"Net radiation : {round(float(rn.iloc[0]),4)} vs 6.0610\")" ] }, { "cell_type": "markdown", - "id": "01f29572-4ddb-40d8-8b59-2c83802817f9", + "id": "3a931ea9-331d-4991-bc20-7d76ba409dfc", "metadata": {}, "source": [ - "## Worked example 2: Estimate daily evapotranspiration" + "## Worked example 3: Estimate daily open-water evaporation using Penman equation (S19.40-45)" ] }, { "cell_type": "markdown", - "id": "3e762676-7686-46fe-b546-19195c291fd7", + "id": "da25a041-5174-48c4-9fd5-44bab34a2cc2", "metadata": {}, "source": [ - "### Worked example 9: Estimate daily reference crop evapotranspiration for short grass using the FAO-56 Reference Crop procedure (S19.46)" + "**NOTE**\n", + "In the next examples, the computed potential evapotranspiration from pyet will be correct for the lambda calculation. WHy? In pyet, lambda (Latent Heat of Vaporization) is computed based on mean temperature, while in MacMahon et al. 2013 it is constant at 2.45." ] }, { "cell_type": "code", - "execution_count": 20, - "id": "032494f4-610b-4c27-a799-83f53ab18c39", + "execution_count": null, + "id": "25d60f42-914b-41a6-a28b-ec21f81ebb7b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FAO-56 : 2.0785 vs 2.0775 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ - "pm_fao56 = pyet.pm_fao56(tmean, rn=rn, wind=wind, tmax=tmax, tmin=tmin, \n", - " lat=lat, elevation=ele,\n", - " rhmin=rhmin, rhmax=rhmax, n=n)\n", - "print(f\"FAO-56 : {round(float(pm_fao56.values),4)} vs 2.0775 mm day-1\")" + "lambda0 = 2.45 \n", + "lambda1 = pyet.calc_lambda(tmean)\n", + "lambda_cor = lambda1 / lambda0" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bc226692-b6a2-4507-9885-0a3137d41827", + "metadata": {}, + "outputs": [], + "source": [ + "# We have to divide the coefficient from McMahon et al. 2013 as PyEts Penman equation uses an unit conversion factor Ku\n", + "aw = 1.313 \n", + "bw = 1.381 \n", + "penman = pyet.penman(tmean, wind=wind, tmax=tmax, tmin=tmin, lat=lat, elevation=ele,\n", + " rhmin=rhmin, rhmax=rhmax, aw=aw, bw=bw, albedo=0.08, n=n)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7de26805-add5-40ff-bac2-a5729e0e1e30", + "metadata": {}, + "outputs": [], + "source": [ + "print(f\"Penman-openwater : {round(float(penman.iloc[0] / lambda_cor.iloc[0]),4)} vs 2.9797 mm day-1\")" ] }, { "cell_type": "markdown", - "id": "25e378b7-3890-4b2e-973b-818795057c46", + "id": "10b8308a-6377-443a-8378-e4b65364ffd0", "metadata": {}, "source": [ - "**NOTE**\n", - "In the next examples, the computed potential evapotranspiration from pyet will be correct for the lambda calculation. WHy? In pyet, lambda (Latent Heat of Vaporization) is computed based on mean temperature, while in MacMahon et al. 2013 it is constant at 2.45." + "**Note**: there is is a small difference between the two values because lambda corr. only applies for the Radiation part." + ] + }, + { + "cell_type": "markdown", + "id": "01f29572-4ddb-40d8-8b59-2c83802817f9", + "metadata": {}, + "source": [ + "## Worked example 4: Estimate daily evapotranspiration" + ] + }, + { + "cell_type": "markdown", + "id": "3e762676-7686-46fe-b546-19195c291fd7", + "metadata": {}, + "source": [ + "### Worked example 9: Estimate daily reference crop evapotranspiration for short grass using the FAO-56 Reference Crop procedure (S19.46)" ] }, { "cell_type": "code", - "execution_count": 21, - "id": "5a5b0ea3-33df-405c-93c3-48cc53e7f6b7", + "execution_count": null, + "id": "032494f4-610b-4c27-a799-83f53ab18c39", "metadata": {}, "outputs": [], "source": [ - "lambda0 = 2.45 \n", - "lambda1 = pyet.calc_lambda(tmean)\n", - "lambda_cor = lambda1 / lambda0" + "pm_fao56 = pyet.pm_fao56(tmean, rn=rn, wind=wind, tmax=tmax, tmin=tmin, \n", + " lat=lat, elevation=ele,\n", + " rhmin=rhmin, rhmax=rhmax, n=n)\n", + "print(f\"FAO-56 : {round(float(pm_fao56.values[0]),4)} vs 2.0775 mm day-1\")" ] }, { @@ -637,21 +522,13 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "5e112281-5248-4f86-bfcf-81bd9fbd4ee7", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Makkink : 2.3933 vs 2.3928 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ "pet_makkink = pyet.makkink(tmean, rs_sol, elevation=ele, k=0.61)\n", - "print(f\"Makkink : {round(float(pet_makkink.values*lambda_cor)-0.12,4)} vs 2.3928 mm day-1\")" + "print(f\"Makkink : {round(float(pet_makkink.values[0]*lambda_cor.iloc[0])-0.12,4)} vs 2.3928 mm day-1\")" ] }, { @@ -664,21 +541,13 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "6ec757d4-c7b4-424c-962b-3dbf3700f372", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Blaney-Criddle : 3.1426 vs 3.1426 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ "pet_bc = pyet.blaney_criddle(tmean, lat, wind=wind, n=n, rhmin=rhmin, py=0.2436, method=2)\n", - "print(f\"Blaney-Criddle : {round(float(pet_bc),4)} vs 3.1426 mm day-1\")" + "print(f\"Blaney-Criddle : {round(float(pet_bc.iloc[0]),4)} vs 3.1426 mm day-1\")" ] }, { @@ -691,22 +560,14 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "id": "af03b1ac-1151-4509-8720-bddb6f0f7807", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Turc : 2.6785 vs 2.6727 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ "rhmean = (rhmax + rhmin) / 2\n", - "pet_turc = pyet.turc(tmean, rs_sol, rhmean, k=0.32)\n", - "print(f\"Turc : {round(float(pet_turc.values),4)} vs 2.6727 mm day-1\")" + "pet_turc = pyet.turc(tmean, rs_sol, rhmean)\n", + "print(f\"Turc : {round(float(pet_turc.values[0]),4)} vs 2.6727 mm day-1\")" ] }, { @@ -719,21 +580,13 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "id": "0563400e-a8fc-461f-8bb2-aa2fe751f430", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hargreaves-Samani : 4.1129 vs 4.1129 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ "pet_har = pyet.hargreaves(tmean, tmax, tmin, lat, method=1)\n", - "print(f\"Hargreaves-Samani : {round(float(pet_har.values*lambda_cor),4)} vs 4.1129 mm day-1\")" + "print(f\"Hargreaves-Samani : {round(float(pet_har.values[0]*lambda_cor.iloc[0]),4)} vs 4.1129 mm day-1\")" ] }, { @@ -746,22 +599,14 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "id": "95940f3a-c073-4275-8706-8241e7fa475b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Priestley-Taylor : 2.6087 vs 2.6083 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ "rn = 8.6401\n", "pet_pt = pyet.priestley_taylor(tmean, rn=rn, elevation=ele, alpha=1.26)\n", - "print(f\"Priestley-Taylor : {round(float(pet_pt.values*lambda_cor),4)} vs 2.6083 mm day-1\")" + "print(f\"Priestley-Taylor : {round(float(pet_pt.values[0]*lambda_cor.iloc[0]),4)} vs 2.6083 mm day-1\")" ] }, { @@ -782,25 +627,17 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "id": "a4d1c5b7-ebdb-4e2e-b2fb-7aeddcc86ca8", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Blaney-Criddle : 3.9 vs 3.9 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ "index = pd.DatetimeIndex([\"1980-7-20\"])\n", "tmean = pd.Series([17.3], index=index) # Maximum daily air temperature [°C]\n", "lat = 50 * np.pi / 180#0.354\n", "\n", "pe_bc = pyet.blaney_criddle(tmean, lat, method=0)\n", - "print(f\"Blaney-Criddle : {round(float(pe_bc.values),2)} vs 3.9 mm day-1\")" + "print(f\"Blaney-Criddle : {round(float(pe_bc.values[0]),2)} vs 3.9 mm day-1\")" ] }, { @@ -813,18 +650,10 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "6546fe45-7319-4429-ab30-57f45be364ed", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Haude : 3.6 vs 3.6 mm day-1\n" - ] - } - ], + "outputs": [], "source": [ "index = pd.DatetimeIndex([\"1980-7-20\"])\n", "tmean = pd.Series([21.5], index=index) \n", @@ -833,16 +662,8 @@ "e0 = pyet.calc_e0(tmean)\n", "rh = ea / e0 * 100\n", "haude = pyet.haude(tmean, rh, k=k)\n", - "print(f\"Haude : {round(float(haude.values),1)} vs 3.6 mm day-1\")" + "print(f\"Haude : {round(float(haude.values[0]),1)} vs 3.6 mm day-1\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "83fc4c19-8222-40b4-a6c7-420d6306499e", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -861,7 +682,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/docs/examples/06_worked_examples_McMahon_etal_2013.ipynb.nblink b/docs/examples/06_worked_examples_McMahon_etal_2013.ipynb.nblink deleted file mode 100644 index 25bcd2a..0000000 --- a/docs/examples/06_worked_examples_McMahon_etal_2013.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/06_worked_examples_McMahon_etal_2013.ipynb" -} \ No newline at end of file diff --git a/docs/examples/07_example_climate_change.ipynb b/docs/examples/07_example_climate_change.ipynb new file mode 100644 index 0000000..95813ca --- /dev/null +++ b/docs/examples/07_example_climate_change.ipynb @@ -0,0 +1,144 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Potential evapotranspiration under warming and elevated $CO_2$ concentration\n", + "*M. Vremec, R.A. Collenteur University of Graz, 2021*\n", + "\n", + "In this notebook it is shown how to estimate Potential Evapotranspiration under elevated $CO_2$ conditions and an increase in temperature.\n", + "The work follows the suggestions made by Yang et al. (2019) to include the sensitivity of stomatal resistance to $CO_2$ in the Penman-Monteith equation.\n", + "\n", + "Yang, Y., Roderick, M.L., Zhang, S. et al. Hydrologic implications of vegetation response to elevated CO2 in climate projections. Nature Clim Change 9, 44–48 (2019). https://doi.org/10.1038/s41558-018-0361-0" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import pyet as pyet" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Load daily data from ZAMG (Messstationen Tagesdaten)\n", + "\n", + "station: Graz Universität 16412\n", + "\n", + "Selected variables:\n", + "- globalstrahlung (global radiation), J/cm2 needs to be in MJ/m3d, ZAMG abbreviation - strahl\n", + "- arithmetische windgeschwindigkeit (wind speed), m/s, ZAMG abbreviation - vv\n", + "- relative feuchte (relative humidity), %, ZAMG abbreviation - rel\n", + "- lufttemparatur (air temperature) in 2 m, C, ZAMG abbreviation - t\n", + "- lufttemperatur (air temperature) max in 2 m, C, ZAMG abbreviation - tmax\n", + "- lufttemperatur (air temperature) min in 2 m, C, ZAMG abbreviation - tmin\n", + "- latitute and elevation of a station" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#read data\n", + "data_16412 = pd.read_csv('data/example_1/klima_daily.csv', index_col=1, parse_dates=True)\n", + "data_16412" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", + "\n", + "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", + " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", + "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", + "\n", + "lat = 47.077778 * np.pi / 180 # Latitude of the meteorological station, converting from degrees to radians\n", + "elevation = 367 # meters above sea-level" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.Estimate potential evapotranspiration under RCP scenarios" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# the first element in the list includes the rise in temperature, and the CO2 concentration\n", + "rcp_26 = [1.3, 450]\n", + "rcp_45 = [2, 650]\n", + "rcp_85 = [4.5, 850]\n", + "\n", + "def pe_cc(tincrease, co2):\n", + " pe = pyet.pm(tmean+tincrease, wind, rs=rs, elevation=elevation, lat=lat, \n", + " tmax=tmax+tincrease, tmin=tmin+tincrease, rh=rh, co2=co2)\n", + " return pe\n", + "\n", + "# Estimate evapotranspiration with four different methods and create a dataframe\n", + "pet_df = pd.DataFrame()\n", + "pet_df[\"amb.\"] = pe_cc(0, 420)\n", + "pet_df[\"RCP 2.6\"] = pe_cc(rcp_26[0], rcp_26[1])\n", + "pet_df[\"RCP 4.5\"] = pe_cc(rcp_45[0], rcp_45[1])\n", + "pet_df[\"RCP 8.5\"] = pe_cc(rcp_85[0], rcp_85[1])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig, axs = plt.subplots(figsize=(13,4), ncols=2)\n", + "pet_df.plot(ax=axs[0])\n", + "pet_df.cumsum().plot(ax=axs[1], legend=False)\n", + "\n", + "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=12)\n", + "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", + "axs[0].legend(ncol=6, loc=[0,1.])\n", + "for i in (0,1):\n", + " axs[i].set_xlabel(\"Date\", fontsize=12)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/docs/examples/07_example_climate_change.ipynb.nblink b/docs/examples/07_example_climate_change.ipynb.nblink deleted file mode 100644 index 8b15a70..0000000 --- a/docs/examples/07_example_climate_change.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/07_example_climate_change.ipynb" -} \ No newline at end of file diff --git a/docs/examples/08_crop_coefficient.ipynb b/docs/examples/08_crop_coefficient.ipynb new file mode 100644 index 0000000..fcac3d5 --- /dev/null +++ b/docs/examples/08_crop_coefficient.ipynb @@ -0,0 +1,224 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "999bc8b7-804c-4301-b8c7-5077a38dc06f", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "# Determining the crop coefficient function with Python\n", + "\n", + "*M. Vremec, October 2022, University of Graz*\n", + "\n", + "Data source: ZAMG - https://data.hub.zamg.ac.at\n", + "\n", + "What is done:\n", + "\n", + "- load the station data from ZAMG\n", + "- estimate potential evapotranspiration\n", + "- determine the crop coefficient function based on equation 65 in Allen et al. 1998\n", + "- plot and store result" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7a2ae568-3c3b-44f5-8b82-ab5a99d35d2d", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import pyet\n", + "pyet.show_versions()" + ] + }, + { + "cell_type": "markdown", + "id": "da6f3e98-0073-4db9-b763-03beb2611e78", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## 1. Loading daily data from ZAMG (Messstationen Tagesdaten)\n", + "\n", + "station: Graz Universität 16412\n", + "\n", + "Selected variables:\n", + "- globalstrahlung (global radiation), J/cm2 needs to be in MJ/m3d, ZAMG abbreviation - strahl\n", + "- arithmetische windgeschwindigkeit (wind speed), m/s, ZAMG abbreviation - vv\n", + "- relative feuchte (relative humidity), %, ZAMG abbreviation - rel\n", + "- lufttemparatur (air temperature) in 2 m, C, ZAMG abbreviation - t\n", + "- lufttemperatur (air temperature) max in 2 m, C, ZAMG abbreviation - tmax\n", + "- lufttemperatur (air temperature) min in 2 m, C, ZAMG abbreviation - tmin\n", + "- latitute and elevation of a station" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "236434b2-3c33-4772-93ec-de0cb7317209", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "#read data\n", + "data_16412 = pd.read_csv('data/example_1/klima_daily.csv', index_col=1, parse_dates=True)\n", + "data_16412" + ] + }, + { + "cell_type": "markdown", + "id": "22ebf3bc-6b9a-4f81-a455-7ca1b51879dd", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## 2. Calculate PET for Graz Universität - 16412" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bc5ba933-22c2-4c5b-9ca6-43a4bcdad344", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", + "\n", + "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", + " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", + "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", + "\n", + "lat = 47.077778*np.pi/180 # Latitude of the meteorological station, converting from degrees to radians\n", + "elevation = 367 # meters above sea-level\n", + "\n", + "# Estimate potential ET with Penman-Monteith FAO-56\n", + "pet_pm = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, \n", + " lat=lat, tmax=tmax, tmin=tmin, rh=rh)" + ] + }, + { + "cell_type": "markdown", + "id": "696cb6aa-773d-4e1b-8a11-64ee5a5242e9", + "metadata": {}, + "source": [ + "## 3. Determine the crop coefficient function\n", + "\n", + "Based on: https://www.fao.org/3/x0490e/x0490e0b.htm\n", + "figure 34.\n", + "\n", + "\n", + "![Figure 34](https://www.fao.org/3/x0490e/x0490e6k.gif)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f92b3767-7233-461c-a924-cafc6f5c9882", + "metadata": {}, + "outputs": [], + "source": [ + "Kcini = 0.3 \n", + "Kcmid = 1.1\n", + "Kcend = 0.65\n", + "\n", + "crop_ini = pd.Timestamp(\"2020-04-01\")\n", + "crop_dev = pd.Timestamp(\"2020-05-01\")\n", + "mid_season = pd.Timestamp(\"2020-06-01\")\n", + "late_s_start = pd.Timestamp(\"2020-07-01\")\n", + "late_s_end = pd.Timestamp(\"2020-08-01\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "86d39fcb-0dea-42ca-9b7a-afa5327ad990", + "metadata": {}, + "outputs": [], + "source": [ + "kc = pd.Series(index=[crop_ini, crop_dev, mid_season, late_s_start, late_s_end],\n", + " data=[Kcini, Kcini, Kcmid, Kcmid, Kcend])\n", + "kc = kc.resample(\"d\").mean().interpolate()\n", + "kc.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c73067c3-2d7e-4bb4-8cff-91f707f7c34b", + "metadata": {}, + "outputs": [], + "source": [ + "petc = pet_pm.loc[crop_dev:late_s_end] * kc" + ] + }, + { + "cell_type": "markdown", + "id": "e6e2564c-48ed-46b7-a275-fd17db592456", + "metadata": { + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "## 4. Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9a4582f-219b-47f8-9ed2-dac80720cf55", + "metadata": { + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "pet_pm.loc[crop_dev:late_s_end].plot(label=\"Potential evapotranspiration\")\n", + "petc.loc[crop_dev:late_s_end].plot(label=\"Potential crop evapotranspiration\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/examples/08_crop_coefficient.ipynb.nblink b/docs/examples/08_crop_coefficient.ipynb.nblink deleted file mode 100644 index 084378f..0000000 --- a/docs/examples/08_crop_coefficient.ipynb.nblink +++ /dev/null @@ -1,3 +0,0 @@ -{ - "path": "../../examples/08_crop_coefficient.ipynb" -} \ No newline at end of file diff --git a/docs/examples/09_CMIP6_data.ipynb b/docs/examples/09_CMIP6_data.ipynb new file mode 100644 index 0000000..ce87ca4 --- /dev/null +++ b/docs/examples/09_CMIP6_data.ipynb @@ -0,0 +1,115 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d8992de4-0b85-4df3-8835-d9dd3e7a3901", + "metadata": {}, + "source": [ + "# Potential Evapotranspiration from CMIP6 climate projections (NetCDF)\n", + "\n", + "*M. Vremec, December 2022, University of Graz*\n", + "\n", + "\n", + "What is done:\n", + "\n", + "- load the data from Copernicus\n", + "- estimate potential evapotranspiration\n", + "- plot\n", + "\n", + "Data source: \n", + "* Copernicus - https://cds.climate.copernicus.eu/ (SSP1-1.9, EC-Earth3 (Europe))\n", + "* [CMIP6 GMD special issue articles](https://gmd.copernicus.org/articles/special_issue590.html)\n", + "* [Terms of using CMIP6 data](https://pcmdi.llnl.gov/CMIP6/TermsOfUse/TermsOfUse6-2.html)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "768010e4-9e5d-4136-80ab-b8eea806dc69", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import xarray as xr\n", + "import pyet" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "69ade8af-753a-4b8d-8680-9531ea24a070", + "metadata": {}, + "outputs": [], + "source": [ + "# Import data\n", + "xr_ds = xr.open_dataset(\"data/example_9/tas_day_EC-Earth3_ssp119_r4i1p1f1_gr_21000601-21000630_v20200425.nc\", \n", + " engine=\"netcdf4\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88f411a2-13b5-41c5-859c-b7d661ea5959", + "metadata": {}, + "outputs": [], + "source": [ + "# Define mean temperature and latitude\n", + "tmean = xr_ds[\"tas\"] - 273\n", + "lat = xr_ds.lat * np.pi/180" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3acf61a9-de98-4048-bcf1-70ef84e871bd", + "metadata": {}, + "outputs": [], + "source": [ + "# Compute PET with Oudin\n", + "pet_oudin = pyet.oudin(tmean, lat=lat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8523231e-c618-4ad9-bb0d-204d2103ddb1", + "metadata": {}, + "outputs": [], + "source": [ + "pet_oudin.sel(time=\"2100-6-2\").plot()" + ] + }, + { + "cell_type": "markdown", + "id": "9abfc543-b01e-4f76-bc36-81094d5d842f", + "metadata": {}, + "source": [ + "## Acknowledgement\n", + "\n", + "We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/examples/10_example_paper.ipynb b/docs/examples/10_example_paper.ipynb new file mode 100644 index 0000000..395e663 --- /dev/null +++ b/docs/examples/10_example_paper.ipynb @@ -0,0 +1,1696 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "69c4d9fe", + "metadata": {}, + "source": [ + "# Improved handling of potential evapotranspiration in hydrological studies with PyEt\n", + "\n", + "This notebook is supporting the manuscript: Vremec et al. \"Technical note: Improved handling of potential evapotranspiration in hydrological studies with *PyEt*\". Submitted to: Geoscientific Model Development.\n", + "\n", + "*M.Vremec (University of Graz), R. A. Collenteur (Eawag)*\n", + "\n", + "Data source: \n", + "\n", + "* Example 1: KNMI - https://www.knmi.nl/home\n", + "* Example 2: E-OBS https://www.ecad.eu/\n", + "* Example 3: ZAMG - https://data.hub.zamg.ac.at\n", + "\n", + "**The supporting Notebook is structured as follows:**\n", + "\n", + "* Benchmarking PET methods\n", + "* Example 1: Estimation of PET from station data\n", + "* Example 2: Estimate PET for gridded data\n", + "* Example 3: Calibration of PET models\n", + "* Example 4: The effect of $CO_2$ on future PET estimates" + ] + }, + { + "cell_type": "markdown", + "id": "cc987fb4-cbeb-4b10-9e26-79dd87f61f9f", + "metadata": {}, + "source": [ + "Table 1: Corresponding literature to each method.\n", + "\n", + "| Method name | Corresponding literature |\n", + "| ----------------- | ------------------------ |\n", + "| Penman | Penman (1948) |\n", + "| Penman-Monteith | Monteith (1965) |\n", + "| ASCE-PM | Walter et al. (2000) |\n", + "| FAO-56 | Allen et al. (1998) |\n", + "| Priestley-Taylor | Priestley and Taylor (1972), McMahon et al. (2013) |\n", + "| Kimberly-Penman | Wright (1982) |\n", + "| Thom-Oliver | Thom and Oliver (1977) |\n", + "| Blaney-Criddle | Xu et al. (2001), McMahon et al. (2013), Schrödter (1985) |\n", + "| Hamon | Hamon (1963), Ansorge et al. (2019), Oudin et al. (2005) |\n", + "| Romanenko | Romanenko (1961), Xu et al. (2001) |\n", + "| Linacre | Linacre (1977) |\n", + "| Haude | Haude (1955), Schiff (1975) |\n", + "| Turc | Turc (1961), Xu et al. (2001) |\n", + "| Jensen-Haise | Jensen and Haise (1963), Jensen et al. (2016), Oudin et al. (2005) |\n", + "| McGuinness-Bordne | McGuinness and Bordne (1972) |\n", + "| Hargreaves | Hargreaves and Samani (1982) |\n", + "| FAO-24 | Jensen et al. (1990) |\n", + "| Abtew | Abtew (1996) |\n", + "| Makkink | Makkink (1957), McMahon et al. (2013) |\n", + "| Oudin | Oudin et al. (2005) |" + ] + }, + { + "cell_type": "markdown", + "id": "c554ae6a", + "metadata": { + "tags": [] + }, + "source": [ + "## 1. Import packages" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "75050118", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# 1. Import needed Python packages\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import cm\n", + "import xarray as xr\n", + "import seaborn as sns\n", + "\n", + "from scipy.optimize import least_squares\n", + "from scipy.stats import gaussian_kde\n", + "import pylab\n", + "import matplotlib.dates as mdates\n", + "from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n", + "\n", + "import pyet\n", + "import spotpy\n", + "from utils import *\n", + "pyet.show_versions()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f3398063", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import warnings\n", + "warnings.filterwarnings('ignore')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4a79810c", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "#edit default values for plots\n", + "params = {\n", + " \"font.family\": \"Arial\",\n", + " \"legend.fontsize\": \"15\",\n", + " \"axes.labelsize\": \"16\",\n", + " \"xtick.labelsize\": \"15\",\n", + " \"ytick.labelsize\": \"15\",\n", + " \"xtick.direction\": \"in\",\n", + " \"ytick.direction\": \"in\",}\n", + "pylab.rcParams.update(params)" + ] + }, + { + "cell_type": "markdown", + "id": "dc0ebed8", + "metadata": { + "tags": [] + }, + "source": [ + "## 2. Benchmarking PET methods" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f28a15f4", + "metadata": {}, + "outputs": [], + "source": [ + "# Read results from Guo et al., 2016\n", + "df_guo = pd.read_excel(\"data/example_10/df_Guo_2016.xlsx\", index_col=\"daily\", \n", + " parse_dates=True).iloc[:50, :]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "095d995c", + "metadata": {}, + "outputs": [], + "source": [ + "# Define input variables\n", + "lat = -0.6095\n", + "elevation = 48\n", + "\n", + "rs = pyet.calc_rad_sol_in(df_guo[\"n\"], lat, as1=0.23, bs1=0.5, nn=None) # Compute solar radiation [MJ/m2day]\n", + "tmax = df_guo[\"Tmax\"] # Daily maximum temperature [°C]\n", + "tmin = df_guo[\"Tmin\"] # Daily minimum temperature [°C]\n", + "tmean = (tmax+tmin)/2 # Daily mean temperature [°C]\n", + "rhmax = df_guo[\"RHmax\"] # Daily maximum relative humidity [%]\n", + "rhmin = df_guo[\"RHmin\"] # Daily minimum relative humidity [%]\n", + "rh = (rhmax+rhmin)/2 # Daily mean relative humidity [%]\n", + "uz = df_guo[\"uz\"] # Wind speed at 10 m [m/s]\n", + "z = 10 # Height of wind measurement [m]\n", + "\n", + "wind_penman = uz * np.log(2/0.001) / np.log(z/0.001) # wind speed at 2 m after Penman 1948\n", + "wind_fao56 = uz * 4.87 / np.log(67.8*z-5.42) # wind speed at 2 m after Allen et al., 1998\n", + "\n", + "lambda1 = pyet.calc_lambda(tmean=tmean) # Latent Heat of Vaporization in PyEt [MJ kg-1] \n", + "lambda0 = 2.45 # Latent Heat of Vaporization in Guo et al., 2016 [MJ kg-1] \n", + "lambda_corr = lambda1 / lambda0 # Correction factor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87ac4b76", + "metadata": {}, + "outputs": [], + "source": [ + "# Benchmarking against R-Evapotranspiration package\n", + "df_pyet_guo = pyet.calculate_all(tmean, wind_fao56, rs, elevation, lat, tmax, tmin, rh, \n", + " rhmax=rhmax, rhmin=rhmin)" + ] + }, + { + "cell_type": "markdown", + "id": "7b5b076e", + "metadata": {}, + "source": [ + "### Test Penman" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2bf863e5", + "metadata": {}, + "outputs": [], + "source": [ + "#%%timeit\n", + "pyet_penman = pyet.penman(tmean, wind_penman, rs=rs, elevation=elevation, lat=lat, tmax=tmax, \n", + " tmin=tmin, rh=rh, rhmax=rhmax, rhmin=rhmin, aw=2.626, bw=1.381, albedo=0.08) * lambda_corr" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2f5ce8ab", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_penman.iloc[:10].round(1).values, df_guo[\"Penman\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "340e434b", + "metadata": {}, + "source": [ + "### Test FAO-56, ASCE, Penman-Monteith" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "62525eda", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(df_pyet_guo[\"FAO-56\"].iloc[:10].round(1).values, df_guo[\"PM\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d76c406a", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_pmasce = pyet.pm_asce(tmean, wind_fao56, rs=rs, elevation=elevation, lat=lat, tmax=tmax, \n", + " tmin=tmin, rh=rh, rhmax=rhmax, rhmin=rhmin)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "78b598a6", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_pmasce.iloc[:10].round(1).values, df_guo[\"PM\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e798b43", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_pm = pyet.pm(tmean, wind_fao56, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh, \n", + " rhmax=rhmax, rhmin=rhmin) * lambda_corr" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a984d6b7", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_pm.iloc[:10].round(1).values, df_guo[\"PM\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "a2d92a3b", + "metadata": {}, + "source": [ + "### Test Makkink" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1b645390", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_makk = (pyet.makkink(tmean, rs=rs, elevation=elevation, k=0.61) * lambda_corr - 0.12) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d8da4e2e", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_makk.iloc[:10].round(1).values, df_guo[\"Makkink\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "df438315", + "metadata": {}, + "source": [ + "### Test Priestley-Taylor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "90229e51", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal((df_pyet_guo[\"Priestley-Taylor\"]*lambda_corr).iloc[:10].round(1).values, df_guo[\"PT\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "a073713e", + "metadata": {}, + "source": [ + "### Hargreaves" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2845cbec", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_hargreaves = pyet.hargreaves(tmean, tmax, tmin, lat, method=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5be2a361", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_hargreaves.iloc[:10].round(1).values, df_guo[\"Har\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "15d8f37b", + "metadata": {}, + "source": [ + "### Test Hamon" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a32920b", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_hamon = pyet.hamon(tmean, lat=lat, n=df_guo[\"n\"], tmax=tmax, tmin=tmin, method=3)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30f49a9c", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_hamon.iloc[:10].round(1).values, df_guo[\"Hamon\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "c40e2662", + "metadata": {}, + "source": [ + "### Blaney Criddle" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e469cdc6", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_bc = pyet.blaney_criddle(tmean, lat, rhmin=rhmin, wind=wind_fao56, method=2, n=df_guo[\"n\"], clip_zero=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e39a847b", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_bc.iloc[:10].round(1).values, df_guo[\"BC\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "7cf4c577", + "metadata": {}, + "source": [ + "### Romanenko" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3054678f", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(df_pyet_guo[\"Romanenko\"].iloc[:10].round(1).values, df_guo[\"Romanenko\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "039b841b", + "metadata": {}, + "source": [ + "### McGuinness-Bordne" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bb04f835", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal((df_pyet_guo[\"Mcguinness-Bordne\"]*lambda_corr).iloc[:10].round(1).values, \n", + " df_guo[\"McG\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "f298f524", + "metadata": {}, + "source": [ + "### Jensen-Haise" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "98ccfd66", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal((df_pyet_guo[\"Jensen-Haise\"]*lambda_corr).iloc[:10].round(1).values, \n", + " df_guo[\"JH\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "9a9a13a1", + "metadata": {}, + "source": [ + "### Linacre" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a2f18b60", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_linacre = pyet.linacre(tmean, elevation, lat, tdew=df_guo[\"Tdew\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "94104178", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_linacre.iloc[:10].round(1).values, \n", + " df_guo[\"Linacre\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "84fe4a0c", + "metadata": {}, + "source": [ + "### Abtew" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c97f2184", + "metadata": {}, + "outputs": [], + "source": [ + "pyet_abtew = pyet.abtew(tmean, rs, k=0.52) * lambda_corr" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b565fe5d", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(pyet_abtew.iloc[:10].round(1).values, \n", + " df_guo[\"Abtew\"].iloc[:10].round(1).values)" + ] + }, + { + "cell_type": "markdown", + "id": "1b6a0fc9", + "metadata": {}, + "source": [ + "### Turc\n", + "**Note** df_guo[\"Turc\"] was modified because a bug was found in R-Evapotranspiration for values when RH < 50. This was found after comparing with McMahon et al. 2013" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "460dddcb", + "metadata": {}, + "outputs": [], + "source": [ + "np.array_equal(df_pyet_guo[\"Turc\"].values.round(1),\n", + " df_guo[\"Turc\"].values.round(1))" + ] + }, + { + "cell_type": "markdown", + "id": "71cc537f", + "metadata": {}, + "source": [ + "### Benchmarking against McMahon et al. 2016" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9d5fb0eb", + "metadata": {}, + "outputs": [], + "source": [ + "# Benchmarking against McMahon et al. 2016\n", + "# Makkink # Based on example S19.91, p 80 McMahon_etal_2013\n", + "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "rs = pd.Series([17.194], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "elevation = 546\n", + "mcm_mak = [2.3928, (pyet.makkink(tmean, rs, elevation=elevation, k=0.61)) -0.12] # correction for different formula in McMahon_2013\n", + "# Blaney Criddle # Based on example S19.93, McMahon_etal_2013\n", + "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "rhmin = pd.Series([25], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "wind = pd.Series([0.5903], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "n = pd.Series([10.7], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "py = pd.Series([0.2436], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "lat = -23.7951 * np.pi / 180\n", + "mcm_bc = [3.1426, pyet.blaney_criddle(tmean, lat, wind=wind, n=n, rhmin=rhmin, py=py, method=2)]\n", + "# Based on example S19.99, McMahon_etal_2013 # Based on example S19.99, McMahon_etal_2013\n", + "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "rhmean = pd.Series([48], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "rs = pd.Series([17.194], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "mcm_turc = [pyet.turc(tmean, rs, rhmean, k=0.32), 2.6727]\n", + "# Based on example S19.101, McMahon_etal_2013\n", + "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "tmax = pd.Series([21], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "tmin = pd.Series([2], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "lat = -23.7951 * np.pi / 180\n", + "mcm_har = [4.1129, pyet.hargreaves(tmean, tmax, tmin, lat, method=1)]\n", + "\n", + "# Based on example S19.109, McMahon_etal_2013\n", + "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "rn = pd.Series([8.6401], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "elevation = 546\n", + "mcm_pt = [2.6083, pyet.priestley_taylor(tmean, rn=rn, elevation=elevation, alpha=1.26)]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fc107162", + "metadata": {}, + "outputs": [], + "source": [ + "# Based on example 5.1, P89 Schrodter 1985\n", + "tmean = pd.Series([17.3], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "lat = 50 * np.pi / 180\n", + "sch_bc = [3.9, pyet.blaney_criddle(tmean, lat, method=0)]\n", + "# Based on example 5.2, P95 Schrodter 1985\n", + "tmean = pd.Series([21.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "ea = pd.Series([1.19], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", + "e0 = pyet.calc_e0(tmean)\n", + "rh = ea / e0 * 100\n", + "sch_haude = [3.6, pyet.haude(tmean, rh=rh, k=0.26 / 0.35)]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "761295d8", + "metadata": {}, + "outputs": [], + "source": [ + "# Benchmarking against FAO-56\n", + "# Hargreasves # Based on example S19.46,p 78 TestFAO56\n", + "tmax = pd.Series([26.6], index=pd.DatetimeIndex([\"2015-07-15\"]))\n", + "tmin = pd.Series([14.8], index=pd.DatetimeIndex([\"2015-07-15\"]))\n", + "tmean = (tmax + tmin) / 2\n", + "lat = 45.72 * np.pi / 180\n", + "fao_har = [5.0, pyet.hargreaves(tmean, tmax, tmin, lat)]\n", + "\n", + "# Based on Example 18, p. 72 FAO.\n", + "wind = pd.Series([2.078], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", + "tmax = pd.Series([21.5], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", + "tmin = pd.Series([12.3], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", + "tmean = (tmax + tmin) / 2\n", + "rhmax = pd.Series([84], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", + "rhmin = pd.Series([63], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", + "rs = pd.Series([22.07], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", + "n = 9.25\n", + "nn = 16.1\n", + "elevation = 100\n", + "lat = 50.80 * np.pi / 180\n", + "fao_56 = [3.9, pyet.pm_fao56(tmean, wind, elevation=elevation, lat=lat, rs=rs, tmax=tmax, tmin=tmin, rhmax=rhmax,\n", + " rhmin=rhmin, n=n, nn=nn)]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6d1251c4-7423-4b98-a7ed-d0d359a99eca", + "metadata": {}, + "outputs": [], + "source": [ + "def add_metrics(ax, x, y):\n", + " ax.text(0.55, 0.04, \"$Bias$ = \" + str(\n", + " round(bias(np.asarray(y), np.asarray(x)), 2)) +\n", + " \"\\n\" + \"$R^2$ = \" + str(\n", + " round(rsquared(np.asarray(y), np.asarray(x)),\n", + " 2)) +\n", + " \"\\n\" + \"KGE = \" + str(\n", + " round(kge(np.asarray(y), np.asarray(x)), 2)), fontsize=12,\n", + " color=\"k\", zorder=10, transform=ax.transAxes)\n", + " return ax" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d09eb52a", + "metadata": {}, + "outputs": [], + "source": [ + "figw_1c = 8.5 # maximum width for 1 column\n", + "figw_2c = 17.5 # maximum width for 2 columns\n", + "cm1 = 1 / 2.54 # centimeters in inches\n", + "fs = 15\n", + "ms1 = 20\n", + "ms2 = 60\n", + "\n", + "fig,axs=plt.subplots(ncols=7, nrows=2, figsize=(figw_2c,5))\n", + "axs[0,0].scatter(df_guo[\"Penman\"], pyet_penman, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,0].text(0.04, 0.9, \"Penman\", transform=axs[0, 0].transAxes, fontsize=fs)\n", + "add_metrics(axs[0,0], df_guo[\"Penman\"], pyet_penman)\n", + "\n", + "axs[0,1].scatter(df_guo[\"PM\"], df_pyet_guo[\"FAO-56\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,1].text(0.04, 0.8, \"FAO-56\", transform=axs[0, 1].transAxes, fontsize=fs)\n", + "axs[0,1].scatter(fao_56[0], fao_56[1], c=\"goldenrod\", marker=\"^\", s=ms2, zorder=10)\n", + "\n", + "axs[0,1].scatter(df_guo[\"PM\"], pyet_pmasce, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,1].text(0.04, 0.7, \"ASCE-PM\", transform=axs[0, 1].transAxes, fontsize=fs)\n", + "add_metrics(axs[0,1], np.append(df_guo[\"PM\"].values, fao_56[0]), \n", + " np.append(df_pyet_guo[\"FAO-56\"].values, fao_56[1]))\n", + "\n", + "axs[0,1].scatter(df_guo[\"PM\"], pyet_pm, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,1].text(0.04, 0.9, \"Penman-Monteith\", transform=axs[0, 1].transAxes, fontsize=fs)\n", + "\n", + "axs[0,2].scatter(df_guo[\"Makkink\"], pyet_makk, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,2].text(0.04, 0.9, \"Makkink\", transform=axs[0, 2].transAxes, fontsize=fs)\n", + "axs[0,2].scatter(mcm_mak[0], mcm_mak[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", + "add_metrics(axs[0,2], np.append(df_guo[\"Makkink\"].values, mcm_mak[0]), \n", + " np.append(pyet_makk.values, mcm_mak[1]))\n", + "\n", + "\n", + "axs[0,3].scatter(df_guo[\"PT\"], df_pyet_guo[\"Priestley-Taylor\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,3].text(0.04, 0.9, \"Priestley-Taylor\", transform=axs[0, 3].transAxes, fontsize=fs)\n", + "axs[0,3].scatter(mcm_pt[0], mcm_pt[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", + "add_metrics(axs[0,3], np.append(df_guo[\"PT\"].values, mcm_pt[0]), \n", + " np.append(df_pyet_guo[\"Priestley-Taylor\"].values, mcm_pt[1]))\n", + "\n", + "p1=axs[0,4].scatter(df_guo[\"Har\"], pyet_hargreaves, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,4].text(0.04, 0.9, \"Hargreaves\", transform=axs[0, 4].transAxes, fontsize=fs)\n", + "p2=axs[0,4].scatter(fao_har[0], fao_har[1], c=\"goldenrod\", marker=\"^\", s=ms2, zorder=10)\n", + "p3=axs[0,4].scatter(mcm_har[0], mcm_har[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", + "add_metrics(axs[0,4], np.append(df_guo[\"Har\"].values, mcm_har[0]), \n", + " np.append(pyet_hargreaves.values, mcm_har[1]))\n", + "\n", + "axs[0,5].scatter(df_guo[\"Hamon\"], pyet_hamon, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,5].text(0.04, 0.9, \"Hamon\", transform=axs[0, 5].transAxes, fontsize=fs)\n", + "add_metrics(axs[0,5], df_guo[\"Hamon\"], pyet_hamon)\n", + "\n", + "axs[0, 6].scatter(df_guo[\"BC\"], pyet_bc, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[0,6].text(0.04, 0.9, \"Blaney-Criddle\", transform=axs[0, 6].transAxes, fontsize=fs)\n", + "axs[0,6].scatter(mcm_bc[0], mcm_bc[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", + "p4=axs[0,6].scatter(sch_bc[0], sch_bc[1], c=\"darkviolet\", marker=\"d\", s=ms2, zorder=10)\n", + "add_metrics(axs[0,6], np.append(df_guo[\"BC\"].values, sch_bc[0]), \n", + " np.append(pyet_bc.values, sch_bc[1]))\n", + "\n", + "axs[1,0].scatter(df_guo[\"Romanenko\"], df_pyet_guo[\"Romanenko\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[1,0].text(0.04, 0.9, \"Romanenko\", transform=axs[1, 0].transAxes, fontsize=fs)\n", + "add_metrics(axs[1,0], df_guo[\"Romanenko\"], df_pyet_guo[\"Romanenko\"])\n", + "\n", + "axs[1,1].scatter(df_guo[\"McG\"], df_pyet_guo[\"Mcguinness-Bordne\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[1,1].text(0.04, 0.9, \"Mcguinness-Bordne\", transform=axs[1, 1].transAxes, fontsize=fs)\n", + "add_metrics(axs[1,1], df_guo[\"McG\"], df_pyet_guo[\"Mcguinness-Bordne\"])\n", + "\n", + "axs[1,2].scatter(df_guo[\"JH\"], df_pyet_guo[\"Jensen-Haise\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[1,2].text(0.04, 0.9, \"Jensen-Haise\", transform=axs[1, 2].transAxes, fontsize=fs)\n", + "add_metrics(axs[1,2], df_guo[\"JH\"], df_pyet_guo[\"Jensen-Haise\"])\n", + "\n", + "axs[1,3].scatter(df_guo[\"Linacre\"], pyet_linacre, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[1,3].text(0.04, 0.9, \"Linacre\", transform=axs[1, 3].transAxes, fontsize=fs)\n", + "add_metrics(axs[1,3], df_guo[\"Linacre\"], pyet_linacre)\n", + "\n", + "axs[1,4].scatter(df_guo[\"Abtew\"], df_pyet_guo[\"Abtew\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[1,4].text(0.04, 0.9, \"Abtew\", transform=axs[1, 4].transAxes, fontsize=fs)\n", + "add_metrics(axs[1,4], df_guo[\"Abtew\"], df_pyet_guo[\"Abtew\"])\n", + "\n", + "axs[1,5].scatter(df_guo[\"Turc\"], df_pyet_guo[\"Turc\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", + "axs[1,5].text(0.04, 0.9, \"Turc\", transform=axs[1, 5].transAxes, fontsize=fs)\n", + "axs[1,5].scatter(mcm_turc[0], mcm_turc[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", + "add_metrics(axs[1,5], np.append(df_guo[\"Turc\"].values, mcm_turc[0]), \n", + " np.append(df_pyet_guo[\"Turc\"].values, mcm_turc[1]))\n", + "\n", + "axs[1,6].text(0.04, 0.9, \"Haude\", transform=axs[1, 6].transAxes, fontsize=fs)\n", + "axs[1,6].scatter(sch_haude[0], sch_haude[1], c=\"darkviolet\", marker=\"d\", s=ms2, zorder=10)\n", + "\n", + "for i in (0,1,2,3,4,5,6):\n", + " axs[0,i].set_xticklabels([]) \n", + " for j in (0, 1):\n", + " axs[j,i].set_xlim(0,10)\n", + " axs[j,i].set_ylim(0,10)\n", + " axs[j,i].plot([0, 10], [0, 10], color=\"gray\", zorder=-10)\n", + " axs[j,i].set_xticks([0, 5])\n", + " axs[j,i].set_yticks([0, 5])\n", + " axs[j,i].set_yticklabels([])\n", + " axs[j,0].set_yticklabels([0, 5])\n", + "\n", + "axs[0,i].set_yticklabels([]) \n", + "\n", + "axs[0,0].legend((p1,p2,p3,p4), (\"R-Evapotranspiration package, Guo et al., 2016\", \n", + " \"Allen et al., 1998\", \"McMahon et al., 2013\", \"Schrodter, 1985\"), ncol=4, loc=[0,1.02], fontsize=16)\n", + "fig.supxlabel(\"PET$_{benchmark}$ [mm/day]\", x=0.475, fontsize=16)\n", + "fig.supylabel(\"PET$_{pyet}$ [mm/day]\", fontsize=16)\n", + "fig.subplots_adjust(wspace=0.05, hspace=0.05, left=0.05)\n", + "plt.tight_layout()\n", + "#fig.savefig(\"figure1.png\", dpi=600, bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "id": "38a45751", + "metadata": { + "tags": [] + }, + "source": [ + "## 3. Example 1: Estimation of PET from station data" + ] + }, + { + "cell_type": "markdown", + "id": "c95c4c06", + "metadata": {}, + "source": [ + "In this example potential evapotranspiration is estimated for the town of De Bilt in The Netherlands using data provided by the Royal Netherlands Meteorological Institute (KNMI). The reference method used by the KNMI for the estimation of potential evapotranspiration is the Makkink method, also implemented in *PyEt*. The $PET$ computed with the Makkink method is compared to the $PET$ values from all other methods in *PyEt*. A number of steps are taken in a Python script to estimate $PET$. The code implementing these steps is shown in the code example bellow. *PyEt* provides a convenience method to compute the $PET$ with all available methods, *pyet.calculate_all()*.\n", + "\n", + "Data source: KNMI - https://dataplatform.knmi.nl/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cfecbf10", + "metadata": {}, + "outputs": [], + "source": [ + "# Load the meteorological data.\n", + "meteo = pd.read_csv(\"data//example_10//10_example_meteo.csv\", index_col=0, parse_dates=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ab21af19", + "metadata": {}, + "outputs": [], + "source": [ + "# Determine the necessary input data for the $PET$ model.\n", + "tmean, tmax, tmin, rh, rs, wind, pet_knmi = (meteo[col] for col in meteo.columns)\n", + "lat = 0.91 # define latitude [radians]\n", + "elevation = 4 # define elevation [meters above sea-level]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f6c9470f", + "metadata": {}, + "outputs": [], + "source": [ + "# Estimate the potential evapotranspiration with all methods or the method of choice.\n", + "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax, tmin, rh)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa4973b5", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Visualize and analyze the results.\n", + "viridis = cm.get_cmap('viridis', len(pet_df.columns))\n", + "colors = [viridis(i) for i in range(0, len(pet_df.columns))]\n", + "colors[-2] = \"k\"\n", + "\n", + "fig, axs = plt.subplots(2, 2, figsize=(6,5), layout=\"constrained\")\n", + "axs = axs.flatten()\n", + "axs[3].axis(\"off\")\n", + "\n", + "pet_df.plot(color=colors, legend=False, ax=axs[0], alpha=0.8, drawstyle=\"steps-mid\")\n", + "axs[0].xaxis.set_major_locator(mdates.MonthLocator(interval=3))\n", + "axs[0].set_ylabel(\"PET [mm/day]\")\n", + "axs[0].set_xlabel(\"\")\n", + "axs[0].set_xticklabels([])\n", + "\n", + "handles = pet_df.cumsum().plot(color=colors, legend=False, ax=axs[2], alpha=0.8)\n", + "axs[2].set_ylabel(\"Cum. PET [mm]\")\n", + "axs[2].xaxis.set_major_locator(mdates.MonthLocator(interval=3))\n", + "axs[2].set_xlabel(\"\")\n", + "\n", + "sns.boxplot(data=pet_df, ax=axs[1], palette=colors)\n", + "axs[1].set_ylabel(\"PET [mm/day]\")\n", + "axs[1].set_xlabel(\"\")\n", + "\n", + "axs[1].set_xticklabels([])\n", + "\n", + "for i, letter in enumerate([\"a\", \"b\", \"c\"]):\n", + " axs[i].text(0.05, 0.9, \"({})\".format(letter), transform=axs[i].transAxes, fontsize=12)\n", + "\n", + "plt.tight_layout()\n", + "\n", + "axs[2].legend(loc=(1.05,0.1), ncol=2, bbox_transform=axs[0].transAxes, fontsize=8)\n", + "#fig.savefig(\"figure2.png\", dpi=600, bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "id": "bf7f5fd0", + "metadata": { + "tags": [] + }, + "source": [ + "## 4. Example 2: Estimate PET for gridded data\n", + "\n", + "Data source: E-OBS https://www.ecad.eu/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d31888e0", + "metadata": {}, + "outputs": [], + "source": [ + "# Load E-OBS data\n", + "wind = xr.open_dataset(\"data/example_10/fg_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", + " engine=\"netcdf4\")[\"fg\"]\n", + "tmax = xr.open_dataset(\"data/example_10/tx_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", + " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", + " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"tx\"]\n", + "tmin = xr.open_dataset(\"data/example_10/tn_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", + " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", + " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"tn\"]\n", + "tmean = xr.open_dataset(\"data/example_10/tg_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", + " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", + " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"tg\"]\n", + "rs = xr.open_dataset(\"data/example_10/qq_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", + " engine=\"netcdf4\").sel(lon=slice(wind.longitude.min(), wind.longitude.max()), \n", + " lat=slice(wind.latitude.min(), wind.latitude.max()))\n", + "rs = rs.rename_dims({\"lon\":\"longitude\", \n", + " \"lat\":\"latitude\"}).rename({\"lon\":\"longitude\", \n", + " \"lat\":\"latitude\"}).sel(ensemble=10)[\"qq\"] * 86400 / 1000000 # concert to [MJ/m2day]\n", + "rh = xr.open_dataset(\"data/example_10/hu_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", + " engine=\"netcdf4\").sel(lon=slice(wind.longitude.min(), wind.longitude.max()), \n", + " lat=slice(wind.latitude.min(), wind.latitude.max()))\n", + "rh = rh.rename_dims({\"lon\":\"longitude\", \"lat\":\"latitude\"}).rename({\"lon\":\"longitude\", \"lat\":\"latitude\"})[\"hu\"]\n", + "wind = wind.sel(longitude=slice(rh.longitude.min(), rh.longitude.max()), latitude=slice(rh.latitude.min(), rh.latitude.max()))\n", + "elevation = xr.open_dataset(\"data/example_10/elev_ens_0.25deg_reg_v25.0e.nc\", \n", + " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", + " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"elevation\"].fillna(0)\n", + "lat = tmean.latitude * np.pi / 180\n", + "lat = lat.expand_dims(dim={\"longitude\":tmean.longitude}, axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e54b4c53", + "metadata": {}, + "outputs": [], + "source": [ + "# Estimate potential Evapotranspiration\n", + "pm_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", + "makkink = pyet.makkink(tmean, rs, elevation=elevation)\n", + "hargreaves = pyet.hargreaves(tmean, tmax, tmin, lat=lat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e2d1d81", + "metadata": {}, + "outputs": [], + "source": [ + "vmax, vmin = 7, 0\n", + "cmap = \"YlOrRd\"\n", + "\n", + "try:\n", + " import cartopy.crs as ccrs \n", + " import cartopy.feature as cf\n", + " fs = 15 # fontsize\n", + " fig, axs = plt.subplots(ncols=3, nrows=3, figsize=(16, 9), sharey=True, sharex=True, subplot_kw={'projection': ccrs.PlateCarree()})\n", + " for date, i in zip([\"2018-6-6\", \"2018-6-7\", \"2018-6-8\"],[0,1,2]):\n", + " pm_fao56.sel(time=date).plot(ax=axs[0,i],vmax=vmax, vmin=vmin, add_colorbar=False, cmap=cmap)\n", + " makkink.sel(time=date).plot(ax=axs[1,i],vmax=vmax, vmin=vmin, add_colorbar=False, cmap=cmap)\n", + " im = hargreaves.sel(time=date).plot(ax=axs[2,i],vmax=vmax, vmin=vmin, add_colorbar=False, cmap=cmap) \n", + " lon_min, lon_max, lat_min, lat_max = (-14, 42, 35, 67)\n", + " for j in (0,1,2):\n", + " axs[j, i].add_feature(cf.BORDERS.with_scale(\"50m\"), lw=0.3)\n", + " axs[j, i].add_feature(cf.COASTLINE.with_scale(\"50m\"), lw=0.4)\n", + " axs[j, i].set_extent([lon_min, lon_max, lat_min, lat_max], crs=ccrs.PlateCarree())\n", + " for date, i in zip([\"2018-6-6\", \"2018-6-7\", \"2018-6-8\"],[0,1,2]):\n", + " for j in (0,1,2): \n", + " axs[j,i].set_title(\"\") \n", + " gl = axs[i,j].gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False, linewidth=0.25)\n", + " gl.right_labels = False\n", + " gl.top_labels = False\n", + " gl.xlabel_style = {'size': 12}\n", + " gl.ylabel_style = {'size': 12}\n", + " if i == 0 or i == 1:\n", + " gl.bottom_labels = False\n", + " if j == 1 or j == 2:\n", + " gl.left_labels = False \n", + " axs[0,i].set_title(\"date=\"+date, fontsize=fs) \n", + " \n", + " cbar_ax = fig.add_axes([0.91, 0.11, 0.01, 0.77])\n", + " cbar = fig.colorbar(im, cax=cbar_ax)\n", + " cbar.set_label(\"PET [mm/day]\", labelpad=10)\n", + " axs[0,0].text(-0.13, 0.55, 'pm_fao56', va='bottom', ha='center', fontsize=fs,\n", + " rotation='vertical', rotation_mode='anchor', transform=axs[0,0].transAxes)\n", + " axs[1,0].text(-0.13, 0.55, 'makkink', va='bottom', ha='center', fontsize=fs,\n", + " rotation='vertical', rotation_mode='anchor', transform=axs[1,0].transAxes)\n", + " axs[2,0].text(-0.13, 0.55, 'hargreaves', va='bottom', ha='center', fontsize=fs,\n", + " rotation='vertical', rotation_mode='anchor', transform=axs[2,0].transAxes)\n", + " \n", + "except ImportError:\n", + " fig, axs = plt.subplots(ncols=3, nrows=3, figsize=(16, 9), sharey=True, sharex=True) \n", + " for date, i in zip([\"2018-6-6\", \"2018-6-7\", \"2018-6-8\"],[0,1,2]):\n", + " im1 = pm_fao56.sel(time=date).plot(ax=axs[0,i],vmax=vmax, vmin=vmin, add_colorbar=False, cmap=cmap)\n", + " im2 = makkink.sel(time=date).plot(ax=axs[1,i],vmax=vmax, vmin=vmin, add_colorbar=False, cmap=cmap)\n", + " im3 = hargreaves.sel(time=date).plot(ax=axs[2,i],vmax=vmax, vmin=vmin, add_colorbar=False, cmap=cmap)\n", + "\n", + " for method, date, i in zip([\"pm_fao56\", \"makkink\", \"hargreaves\"], [\"2018-6-6\", \"2018-6-7\", \"2018-6-8\"],[0,1,2]):\n", + " for j in (0,1,2): \n", + " axs[i, j].set_ylabel(\"\")\n", + " axs[i, j].set_xlabel(\"\")\n", + " axs[i, j].set_title(\"\")\n", + " axs[2,j].set_xlabel(\"Lon. [°E]\")\n", + " axs[i, 0].set_ylabel(method + \"\\n\\nLat. [°N]\")\n", + " axs[0,i].set_title(\"date=\"+date)\n", + " axs[0,0].set_xlabel(\"alalal\")\n", + " cbar_ax = fig.add_axes([0.91, 0.11, 0.01, 0.77])\n", + " cbar = fig.colorbar(im3, cax=cbar_ax)\n", + " cbar.set_label(\"PET [mm/day]\", labelpad=10)\n", + " plt.subplots_adjust(hspace=0.02, wspace=0.1)\n", + "\n", + "plt.subplots_adjust(hspace=0.02, wspace=0.01)\n", + "\n", + "#fig.savefig(\"figure3.png\", dpi=300, bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "id": "84918f2b", + "metadata": { + "tags": [] + }, + "source": [ + "## 5. Example 3: Calibration of PET models\n", + "\n", + "Data source: ZAMG - https://data.hub.zamg.ac.at" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "93b91863", + "metadata": {}, + "outputs": [], + "source": [ + "#Load station data\n", + "data_16412 = pd.read_csv('data/example_1/klima_daily.csv', index_col=1, parse_dates=True)\n", + "data_16412.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d37c6693", + "metadata": {}, + "outputs": [], + "source": [ + "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", + "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \n", + " \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", + " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", + "\n", + "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", + "\n", + "lat = 47.077778 * np.pi / 180 # Latitude of the meteorological station, converting from degrees to radians\n", + "elevation = 367 # meters above sea-level\n", + "\n", + "# Estimate evaporation with all different methods and create a dataframe\n", + "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax,\n", + " tmin=tmin, rh=rh)" + ] + }, + { + "cell_type": "markdown", + "id": "a6f6cd92-16c0-446f-9343-d26671613614", + "metadata": {}, + "source": [ + "### 5.1 Calibrate alternative temperature models to Penman-Monteith" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "68610698", + "metadata": {}, + "outputs": [], + "source": [ + "# Calibrate alternative temperature models to Penman-Monteith\n", + "methods = [\"oudin\", \"hargreaves\", \"mcguinness_bordne\", \"hamon\", \"blaney_criddle\"]\n", + "\n", + "# Define initial values for calibration for each method\n", + "params = [[100, 5], [0.0135], [0.0147], [1], [-1.55, 0.96]]\n", + "\n", + "# Define input for each method\n", + "input2 = ([tmean, lat], [tmean, tmax, tmin, lat], [tmean, lat],\n", + " [tmean, lat], [tmean, lat])\n", + "\n", + "# Define function to simulate the models and use required input\n", + "def simulate(params, method, input1): \n", + " input1_1 = input1.copy()\n", + " method = getattr(pyet, method)\n", + " for par in params:\n", + " input1_1.append(par)\n", + " return method(*input1_1)\n", + "\n", + "# Define function to estimate residuals \n", + "def residuals(params, info):\n", + " method, input1, obs = info\n", + " sim = simulate(params, method, input1)\n", + " return sim - obs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f0aadada", + "metadata": {}, + "outputs": [], + "source": [ + "# Calibrate the models to Penman-Monteith\n", + "obs = pet_df[\"FAO-56\"]\n", + "sollutions2 = []\n", + "for i in np.arange(0,len(methods)):\n", + " res_1 = least_squares(residuals, params[i], args=[[methods[i], input2[i], obs]])\n", + " sollutions2.append(res_1.x)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f7e8589e", + "metadata": {}, + "outputs": [], + "source": [ + "# Create DataFrame with PET estimated with default (params) and calibrated parameters(sollutions2)\n", + "pet_df_def = pd.DataFrame()\n", + "pet_df_cali = pd.DataFrame()\n", + "for i in np.arange(0, len(methods)):\n", + " pet_df_def[methods[i]] = simulate(params[i], methods[i], input2[i])\n", + " pet_df_cali[methods[i]] = simulate(sollutions2[i], methods[i], input2[i])" + ] + }, + { + "cell_type": "markdown", + "id": "d156c21f", + "metadata": { + "tags": [] + }, + "source": [ + "### 5.2 Hindcasting PET for Graz, Austria" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1ebebb9b", + "metadata": {}, + "outputs": [], + "source": [ + "# Load Spartacus dataset\n", + "spartacus = xr.open_dataset(\"data/example_10/spartacus-daily_19610101T0000_20211231T0000.nc\", \n", + " engine=\"netcdf4\")\n", + "spartacus_cali = spartacus.copy()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c794bad9", + "metadata": {}, + "outputs": [], + "source": [ + "# Define new input\n", + "tmean_spartacus = (spartacus[\"Tx\"] + spartacus[\"Tn\"]) / 2\n", + "tmax_spartacus = spartacus[\"Tx\"]\n", + "tmin_spartacus = spartacus[\"Tn\"]\n", + "lat_spartacus = spartacus.lat * np.pi / 180 # from degrees to radians\n", + "input_spartacus = ([tmean_spartacus, lat_spartacus], \n", + " [tmean_spartacus, tmax_spartacus, tmin_spartacus, lat_spartacus], \n", + " [tmean_spartacus, lat_spartacus],\n", + " [tmean_spartacus, lat_spartacus], [tmean_spartacus, lat_spartacus])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2659c0bc", + "metadata": {}, + "outputs": [], + "source": [ + "# Estimate PET and add it to the xarray.Dataset\n", + "for i in np.arange(0,len(methods)):\n", + " spartacus[methods[i]] = simulate(params[i], methods[i], input_spartacus[i])\n", + " spartacus_cali[methods[i]] = simulate(sollutions2[i], methods[i], input_spartacus[i])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8c8299db", + "metadata": {}, + "outputs": [], + "source": [ + "# Create DataFrame with PET estimated with default (params) and calibrated (sollutions2) models\n", + "df_def = spartacus.to_dataframe().reset_index(level=[1,1]).drop(columns=[\"y\", \"Tn\", \"Tx\", \"lambert_conformal_conic\", \"lon\", \"lat\"])\n", + "df_cali = spartacus_cali.to_dataframe().reset_index(level=[1,1]).drop(columns=[\"y\", \"Tn\", \"Tx\", \"lambert_conformal_conic\", \"lon\", \"lat\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6c477f92-7188-48f1-a86a-6fc261a8c052", + "metadata": {}, + "outputs": [], + "source": [ + "def scatter_1(ax, x, y, label=\"treatment\", xlabel=\"obs\", ylabel=\"sim\",\n", + " best_fit=True, veg_ws=None):\n", + " compare = pd.DataFrame({\"x\": x, \"y\": y})\n", + " if veg_ws is not None:\n", + " compare[veg_ws == 0] = np.nan\n", + " compare = compare.dropna()\n", + " xy = np.vstack([compare[\"x\"].values,compare[\"y\"].values])\n", + " z = gaussian_kde(xy)(xy)\n", + " density = ax.scatter(compare[\"x\"], compare[\"y\"], marker=\"o\", s=2, c=z)#, fillstyle=\"none\")\n", + " ax.plot([-0.1, 10], [-0.1, 10], color=\"dodgerblue\", alpha=0.7,\n", + " linewidth=\"0.8\")\n", + " ax.axes.set_xticks(np.arange(0, 10 + 2, 2))\n", + " ax.axes.set_yticks(np.arange(0, 10 + 2, 2))\n", + " ax.set_xlim(-0.1, 10)\n", + " ax.set_ylim(-0.1, 10)\n", + " if best_fit:\n", + " p = np.polyfit(compare[\"x\"], compare[\"y\"], 1)\n", + " f = np.poly1d(p)\n", + "\n", + " # Calculating new x's and y's\n", + " x_new = np.linspace(0, 10, y.size)\n", + " y_new = f(x_new)\n", + "\n", + " # Plotting the best fit line with the equation as a legend in latex\n", + " ax.plot(x_new, y_new, \"r--\", linewidth=\"0.8\")\n", + " ax.text(0.02, 0.9, f\"{label}\", color=\"k\", zorder=10,\n", + " transform=ax.transAxes)\n", + " ax.text(0.6, 0.04, \"$Bias$ = \" + str(\n", + " round(bias(np.asarray(compare[\"y\"]), np.asarray(compare[\"x\"])), 2)) +\n", + " \"\\n\" + \"$R^2$ = \" + str(\n", + " round(rsquared(np.asarray(compare[\"y\"]), np.asarray(compare[\"x\"])),\n", + " 2)) +\n", + " \"\\n\" + \"KGE = \" + str(\n", + " round(kge(np.asarray(compare[\"y\"]), np.asarray(compare[\"x\"])), 2)),\n", + " color=\"k\", zorder=10, transform=ax.transAxes)\n", + " return density" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "11a79765", + "metadata": {}, + "outputs": [], + "source": [ + "figw_1c = 8.5 # maximum width for 1 column\n", + "figw_2c = 17.5 # maximum width for 2 columns\n", + "\n", + "fig, axs = plt.subplots(ncols=6, nrows=2, figsize=(figw_2c, 5), dpi=300)\n", + "for i in np.arange(0, len(methods)):\n", + " density = scatter_1(axs[0,i], obs, simulate(params[i], methods[i], input2[i]), label=f\"{methods[i]} - default\")\n", + " density = scatter_1(axs[1,i], obs, simulate(sollutions2[i], methods[i], input2[i]), label=f\"{methods[i]} - calibrated\")\n", + " axs[0, i].set_xticklabels([])\n", + " axs[1, i].set_xlabel(r\"PET$_{sim}$ [mm/d]\")\n", + " axs[1, i].set_xticklabels((0,2,4,6,8,\"\"))\n", + "for col in (1, 2, 3, 4):\n", + " axs[0, col].set_yticklabels([])\n", + " axs[1, col].set_yticklabels([])\n", + "plt.subplots_adjust(wspace=0.1, hspace=0.1)\n", + "for row in (0, 1):\n", + " axs[row, 0].set_ylabel(r\"PET$_{FAO-56}$ [mm/d]\")\n", + "\n", + "viridis = cm.get_cmap('viridis', len(df_def.columns))\n", + "colors = [viridis(i) for i in range(0, len(df_def.columns))]\n", + "df_def.resample(\"y\").sum().plot(ax=axs[0, 5], legend=False, color=colors)\n", + "df_cali.resample(\"y\").sum().plot(ax=axs[1, 5], legend=False, color=colors)\n", + "axs[0,5].axvline(pd.Timestamp(\"2000-1-1\"), color=\"k\", linestyle=\"--\", lw=1)\n", + "axs[1,5].axvline(pd.Timestamp(\"2000-1-1\"), color=\"k\", linestyle=\"--\", lw=1)\n", + "#pet_df_def.cumsum().plot(ax=axs[0, 5], legend=False)\n", + "#obs.cumsum().plot(ax=axs[0,5], label=\"pm_fao56$ [mm/d]\", color=\"k\", linestyle=\"--\", )\n", + "#obs.cumsum().plot(ax=axs[1,5], label=\"pm_fao56\", color=\"k\", linestyle=\"--\", )\n", + "#pet_df_cali.cumsum().plot(ax=axs[1, 5], legend=False)\n", + "for i in (0,1):\n", + " axs[i,5].yaxis.tick_right()\n", + " axs[i,5].yaxis.set_label_position(\"right\")\n", + " axs[i,5].set_xticks((pd.Timestamp(\"2016-1-1\"), pd.Timestamp(\"2018-1-1\"), pd.Timestamp(\"2020-1-1\")))\n", + " axs[i,5].set_ylim(600, 1200)\n", + " axs[i,5].set_ylabel(\"Cumulative PET [mm]\", fontsize=14)\n", + "axs[0,5].set_xticklabels(\"\");\n", + "axs[1,5].set_xticks([\"1960-1-1\", \"1980-1-1\", \"2000-1-1\", \"2021-1-1\"]);\n", + "axs[1,5].set_xticklabels([\"1960\", \"1980\", \"2000\", \"2021\"]);\n", + "axs[0,5].set_xlabel(\"\");\n", + "plt.subplots_adjust(hspace=0.05, wspace=0.05)\n", + "axs[1,5].set_yticklabels([\"\",800,1000,\"\"])\n", + "axs[0,5].legend(loc=(-3.65,1.05), ncol=7, bbox_transform=axs[1,5].transAxes)\n", + "clb = fig.colorbar(density, orientation=\"horizontal\", ax=axs[0, 0], cax = axs[0, 0].inset_axes([0.04, 1.2, 1, 0.05]))\n", + "clb.ax.set_title(\"Number of points per pixel\")\n", + "#fig.savefig(\"figure4.png\", dpi=600, bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "id": "6f46ea03", + "metadata": { + "tags": [] + }, + "source": [ + "## 6. Example 4: Forecasting for Graz Austria" + ] + }, + { + "cell_type": "markdown", + "id": "ba18d232", + "metadata": {}, + "source": [ + "$$ PET_{CO_2} = f_{CO_2} PET $$\n", + "\n", + "Data source temperature: https://climate-impact-explorer.climateanalytics.org/impacts/\n", + "\n", + "Data source $CO_2$ levels: https://tntcat.iiasa.ac.at/RcpDb/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a85f2efd", + "metadata": {}, + "outputs": [], + "source": [ + "# Load increase in temperature for each RCP scenario\n", + "rcp_temp = pd.read_csv(\"data/example_10/tasAdjust_AUT_AT.ST_area_annual.csv\", \n", + " skiprows=4, index_col=\"year\").loc[\"2020\":,:]\n", + "rcp_temp = rcp_temp.loc[:, [\"RCP2.6 median\", \"RCP4.5 median\", \"RCP6.0 median\", \"RCP8.5 median\"]]\n", + "rcp_temp.columns = [\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dd58ca5e", + "metadata": {}, + "outputs": [], + "source": [ + "# Load CO2 data for each RCP scenario\n", + "rcp_co2 = pd.DataFrame()\n", + "rcp_co2[\"rcp_26\"] = pd.read_csv(\"data/example_10/co2_conc/RCP3PD_MIDYR_CONC.dat\", skiprows=38, \n", + " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]\n", + "rcp_co2[\"rcp_45\"] = pd.read_csv(\"data/example_10/co2_conc/RCP45_MIDYR_CONC.dat\", skiprows=38, \n", + " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]\n", + "rcp_co2[\"rcp_60\"] = pd.read_csv(\"data/example_10/co2_conc/RCP6_MIDYR_CONC.dat\", skiprows=38, \n", + " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]\n", + "rcp_co2[\"rcp_85\"] = pd.read_csv(\"data/example_10/co2_conc/RCP85_MIDYR_CONC.dat\", skiprows=38, \n", + " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7c1bf22a", + "metadata": {}, + "outputs": [], + "source": [ + "# RCP scenario 6.0\n", + "co2_600 = 600\n", + "pet_300 = pyet.pm(tmean, wind, rs=rs, elevation=elevation, lat=lat, \n", + " tmax=tmax, tmin=tmin, rh=rh)\n", + "pet_600 = pyet.pm(tmean, wind, rs=rs, elevation=elevation, lat=lat, \n", + " tmax=tmax, tmin=tmin, rh=rh, co2=co2_600)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3f14c72c", + "metadata": {}, + "outputs": [], + "source": [ + "# Compute the sensitivity of PET to CO2\n", + "def residuals_co2(S_CO2, PETco2, PETamb, co2):\n", + " fco2 = (1+S_CO2*(co2-300))\n", + " return PETco2 - PETamb * fco2\n", + "\n", + "res1 = least_squares(residuals_co2, [0.02], args=[pet_600, pet_300, 600])\n", + "res1.x" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea92559e", + "metadata": {}, + "outputs": [], + "source": [ + "# Define input for each method\n", + "inputamb = ([tmean, lat], [tmean, tmax, tmin, lat], [tmean, lat],\n", + " [tmean, lat], [tmean, lat])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a45ef088", + "metadata": {}, + "outputs": [], + "source": [ + "# Define function for input\n", + "def input_rcp(tincrease):\n", + " return ([tmean+tincrease, lat], [tmean+tincrease, tmax+tincrease, tmin+tincrease, lat], [tmean+tincrease, lat],\n", + " [tmean+tincrease, lat], [tmean+tincrease, lat])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0a3a04ed", + "metadata": {}, + "outputs": [], + "source": [ + "# Compute PET for each year for each RCP scenario with 5-95 percentile\n", + "dpet_rcp_et = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", + "dpet_rcp_et_5th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", + "dpet_rcp_et_95th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", + "dpet_rcp_etco2 = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", + "dpet_rcp_etco2_5th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", + "dpet_rcp_etco2_95th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", + "for year in rcp_temp.index:\n", + " for rcp in [\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"]:\n", + " df_rcp_et = pd.DataFrame()\n", + " df_rcp_etco2 = pd.DataFrame()\n", + " for i in np.arange(0, len(methods)):\n", + " input1 = input_rcp(rcp_temp.loc[year, rcp])\n", + " df_rcp_et[methods[i]] = simulate(sollutions2[i], methods[i], input1[i])\n", + " df_rcp_etco2[methods[i]] = simulate(sollutions2[i], methods[i], \n", + " input1[i]) * (1+res1.x*(rcp_co2.loc[year, rcp]-300))\n", + " dpet_rcp_et.loc[year, rcp] = df_rcp_et.resample(\"y\").mean().mean().mean()\n", + " dpet_rcp_et_5th.loc[year, rcp] = df_rcp_et.resample(\"y\").mean().mean().quantile(0.05)\n", + " dpet_rcp_et_95th.loc[year, rcp] = df_rcp_et.resample(\"y\").mean().mean().quantile(0.95)\n", + " dpet_rcp_etco2.loc[year, rcp] = df_rcp_etco2.resample(\"y\").mean().mean().mean()\n", + " dpet_rcp_etco2_5th.loc[year, rcp] = df_rcp_etco2.resample(\"y\").mean().mean().quantile(0.05)\n", + " dpet_rcp_etco2_95th.loc[year, rcp] = df_rcp_etco2.resample(\"y\").mean().mean().quantile(0.95)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "76d45437", + "metadata": {}, + "outputs": [], + "source": [ + "dpet_rcp_et = dpet_rcp_et.apply(pd.to_numeric)\n", + "dpet_rcp_et_5th = dpet_rcp_et_5th.apply(pd.to_numeric)\n", + "dpet_rcp_et_95th = dpet_rcp_et_95th.apply(pd.to_numeric)\n", + "dpet_rcp_etco2 = dpet_rcp_etco2.apply(pd.to_numeric)\n", + "dpet_rcp_etco2_5th = dpet_rcp_etco2_5th.apply(pd.to_numeric)\n", + "dpet_rcp_etco2_95th = dpet_rcp_etco2_95th.apply(pd.to_numeric)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8c97280e", + "metadata": {}, + "outputs": [], + "source": [ + "fig, axs = plt.subplots(2,2, figsize=(6, 5), constrained_layout=True, sharex=True)\n", + "axs = axs.flatten()\n", + "viridis = cm.get_cmap('viridis', len(rcp_temp.columns))\n", + "colors = [viridis(i) for i in range(0, len(rcp_temp.columns))]\n", + "\n", + "for col, rcp, name in zip(colors, rcp_temp.columns, [\"RCP 2.6\", \"RCP 4.5\", \"RCP 6.0\", \"RCP 8.5\"]):\n", + " axs[2].plot(dpet_rcp_et.loc[:, rcp]-dpet_rcp_et.loc[2020, rcp], c=col);\n", + " axs[2].fill_between(dpet_rcp_et.index, dpet_rcp_et_5th[rcp]-dpet_rcp_et.loc[2020, rcp], \n", + " dpet_rcp_et_95th[rcp]-dpet_rcp_et.loc[2020, rcp], color=col, alpha=0.2)\n", + " axs[3].fill_between(dpet_rcp_et.index, dpet_rcp_etco2_5th[rcp]-dpet_rcp_etco2.loc[2020, rcp], \n", + " dpet_rcp_etco2_95th[rcp]-dpet_rcp_etco2.loc[2020, rcp], color=col, alpha=0.2)\n", + " axs[3].plot(dpet_rcp_etco2.loc[:, rcp]-dpet_rcp_etco2.loc[2020, rcp], c=col);\n", + " axs[1].plot(rcp_co2[rcp], c=col)\n", + " axs[0].plot(rcp_temp[rcp], c=col, label=name)\n", + "\n", + "axs[0].set_ylabel(r\"$\\Delta$T [°C]\")\n", + "axs[0].legend()\n", + "\n", + "axs[1].set_ylabel(\"$CO_2$ [ppm]]\")\n", + "\n", + "axs[2].set_ylim(0, 0.79)\n", + "axs[2].set_ylabel(\"$\\Delta$PET [mm/day]\")\n", + "\n", + "axs[3].set_ylim(0, 0.79)\n", + "#axs[3].set_xlim(\"2020\", \"2100\")\n", + "axs[2].set_ylabel(\"$\\Delta$PET [mm/day]\")\n", + "\n", + "axs[2].text(2025, 0.7, \"T+\", fontsize=14)\n", + "axs[3].text(2025, 0.7, \"T + $CO_2$+\", fontsize=14)\n", + "\n", + "for i, letter in enumerate([\"a\", \"b\", \"c\", \"d\"]):\n", + " axs[i].text(0.85, 0.9, \"({})\".format(letter), transform=axs[i].transAxes, fontsize=12)\n", + " axs[i].tick_params(axis='both', which='major', labelsize=13)\n", + "\n", + "#fig.savefig(\"figure5.png\", dpi=600, bbox_inches=\"tight\")" + ] + }, + { + "cell_type": "markdown", + "id": "abfb2272", + "metadata": {}, + "source": [ + "## 7. Code example in paper" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b7d21bf4", + "metadata": {}, + "outputs": [], + "source": [ + "# 1. Import needed Python packages\n", + "import numpy as np\n", + "import pandas as pd\n", + "\n", + "# 2. Reading meteorological data\n", + "meteo = pd.read_csv(\"data/example_10/10_example_meteo.csv\", index_col=0, parse_dates=True)\n", + "\n", + "# 3. Determining the necessary input data\n", + "tmean, tmax, tmin, rh, rs, wind, pet_knmi = (meteo[col] for col in meteo.columns)\n", + "lat = 0.91 # define latitude [radians]\n", + "elev = 4 # define elevation [meters above sea-level]\n", + "\n", + "# 4. Estimate PET (all methods) and save the results in a Pandas.DataFrame\n", + "pet_df = pyet.calculate_all(tmean, wind, rs, elev, lat, tmax, tmin, rh)\n", + " \n", + "# (4. Estimate potential evaporation - Example with one method)\n", + "pyet_makkink = pyet.makkink(tmean, rs, elevation=elev)\n", + "\n", + "# 5. Plot PET \n", + "pet_df.plot() # daily PET [mm/day]\n", + "pet_df.boxplot() # boxplot PET[mm/day]\n", + "pet_df.cumsum().plot() # cummulative PET [mm]\n", + "plt.scatter(pyet_makkink, pet_knmi) # plot Makkink pyet vs KNMI" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e0c2479f", + "metadata": {}, + "outputs": [], + "source": [ + "# 2. Reading meteorological data\n", + "meteo = pd.read_csv(\"data//example_10//10_example_meteo.csv\", index_col=0, parse_dates=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cb4b5ee1", + "metadata": {}, + "outputs": [], + "source": [ + "# 3. Determining the necessary input data\n", + "tmean, tmax, tmin, rh, rs, wind, pet_knmi = (meteo[col] for col in meteo.columns)\n", + "lat = 0.91 # define latitude [radians]\n", + "elevation = 4 # define elevation [meters above sea-level]" + ] + }, + { + "cell_type": "markdown", + "id": "13bae9c9", + "metadata": { + "tags": [] + }, + "source": [ + "Now that we have defined the input data, we can estimate potential evaporation with different estimation methods. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "54f684ea", + "metadata": {}, + "outputs": [], + "source": [ + "# 4. Estimate potential evaporation (with all available methods) and save the results in a Pandas.DataFrame\n", + "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax, tmin, rh)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2c8652d0", + "metadata": {}, + "outputs": [], + "source": [ + "# 4. Estimate PE and save the results in a xarray.DataArray\n", + "pe_pm_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, \n", + " lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", + "pe_makkink = pyet.makkink(tmean, rs, elevation=elevation)\n", + "pe_pt = pyet.priestley_taylor(tmean, rs=rs, elevation=elevation, \n", + " lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", + "pe_hamon = pyet.hamon(tmean, lat=lat) \n", + "pe_blaney_criddle = pyet.blaney_criddle(tmean, lat)\n", + "pe_hargreaves = pyet.hargreaves(tmean, tmax, tmin, lat=lat)" + ] + }, + { + "cell_type": "markdown", + "id": "d43d1f5e-0bbc-43f9-ac94-6f952278245e", + "metadata": {}, + "source": [ + "## Acknowledgements" + ] + }, + { + "cell_type": "markdown", + "id": "49ac81b2-c7f8-4670-b8a2-2a4f64368903", + "metadata": {}, + "source": [ + "We acknowledge the financial support by the University of Graz and the funding of the Earth System Sciences research program of the the Austrian Academy of Sciences (ÖAW project ClimGrassHydro). We acknowledge the ZAMG dataset (https://data.hub.zamg.ac.at), KNMI dataset (https://www.knmi.nl/home), and the E-OBS dataset from the EU-FP6 project UERRA (http://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA\\&D project (https://www.ecad.eu). " + ] + }, + { + "cell_type": "markdown", + "id": "e69f71ff-fa2d-449a-9321-944acd4248b4", + "metadata": {}, + "source": [ + "## Literature\n", + "\n", + "Abtew, W. (1996). Evapotranspiration measurements and modeling for three wetland systems in South Florida 1. JAWRA Journal of the American Water Resources Association, 32, 465-473. Publisher: Wiley Online Library.\n", + "\n", + "Allen, R.G., Pereira, L.S., Raes, D., Smith, M., & others. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Rome: Fao, 300, D05109.\n", + "\n", + "Ansorge, L., & Beran, A. (2019). Performance of simple temperature-based evaporation methods compared with a time series of pan evaporation measures from a standard 20 m2 tank. Journal of Water and Land Development, 41, 1-11. https://doi.org/10.2478/jwld-2019-0021.\n", + "\n", + "Guo, D., Westra, S., & Maier, H. R. (2016). An R package for modelling actual, potential and reference evapotranspiration. Environmental Modelling & Software, 78, 216-224.\n", + "\n", + "Hamon, W.R. (1963). Estimating potential evapotranspiration. Transactions of the American Society of Civil Engineers, 128, 324-338. Publisher: American Society of Civil Engineers.\n", + "\n", + "Hargreaves, G.H., & Samani, Z.A. (1982). Estimating potential evapotranspiration. Journal of the irrigation and Drainage Division, 108, 225-230. Publisher: American Society of Civil Engineers. https://doi.org/10.1061/(ASCE)0733-9437(1983)109:3(341).\n", + "\n", + "Haude, W. (1955). Determination of evapotranspiration by an approach as simple as possible. Mitt Dt Wetterdienst, 2.\n", + "\n", + "Jensen, M.E., & Allen, R.G. (2016). Evaporation, Evapotranspiration, and Irrigation Water Requirements (2nd ed.). American Society of Civil Engineers. _eprint: https://ascelibrary.org/doi/pdf/10.1061/, https://doi.org/10.1061/9780784414057.\n", + "\n", + "Jensen, M.E., Burman, R.D., Allen, R.G., & others. (1990). Evapotranspiration and irrigation water requirements. ASCE, New York.\n", + "\n", + "Jensen, M.E., & Haise, H.R. (1963). Estimating evapotranspiration from solar radiation. Journal of the Irrigation and Drainage Division, 89, 15-41. Publisher: American Society of Civil Engineers. https://doi.org/10.1061/JRCEA4.0000287.\n", + "\n", + "Linacre, E.T. (1977). A simple formula for estimating evaporation rates in various climates, using temperature data alone. Agricultural Meteorology, 18, 409-424. https://doi.org/https://doi.org/10.1016/0002-1571(77)90007-3.\n", + "\n", + "Makkink, G.F. (1957). Testing the Penman formula by means of lysimeters. Journal of the Institution of Water Engineerrs, 11, 277-288.\n", + "\n", + "McGuinness, J., & Bordne, E. (1972). A comparison of lysimeter derived potential evapotranspiration with computed values. Tech. Bull. Agric. Res. Serv., US Dep. of Agric., Washington, DC. https://doi.org/10.22004/ag.econ.171893.\n", + "\n", + "McMahon, T.A., Peel, M.C., Lowe, L., Srikanthan, R., & McVicar, T.R. (2013). Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences, 17, 1331-1363. https://doi.org/10.5194/hess-17-1331-2013.\n", + "\n", + "Monteith, J.L. (1965). Evaporation and environment. In Proceedings of the Symposia of the society for experimental biology. Cambridge University Press (CUP) Cambridge, Vol. 19, pp. 205-234.\n", + "\n", + "Oudin, L., Michel, C., & Anctil, F. (2005). Which potential evapotranspiration input for a lumped rainfall-runoff model? Journal of Hydrology, 303, 275-289. https://doi.org/10.1016/j.jhydrol.2004.08.025.\n", + "\n", + "Penman, H.L. (1948). Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 193, 120-145. Publisher: The Royal Society London.\n", + "\n", + "Priestley, C.H.B., & Taylor, R.J. (1972). On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly weather review, 100, 81-92.\n", + "\n", + "Romanenko, V. (1961). Computation of the autumn soil moisture using a universal relationship for a large area. Proc. of Ukrainian Hydrometeorological Research Institute, 3, 12-25.\n", + "\n", + "Schiff, H. (1975). Berechnung der potentiellen Verdunstung und deren Vergleich mit aktuellen Verdunstungswerten von Lysimetern. Archiv für Meteorologie, Geophysik und Bioklimatologie, Serie B, 23, 331-342. Publisher: Springer. https://doi.org/https://doi.org/10.1007/BF02242689.\n", + "\n", + "Schrödter, H. (1985). Hinweise Für den Einsatz Anwendungsorientierter Bestimmungsverfahren. Berlin, Heidelberg: Springer Berlin Heidelberg. Publication Title: Verdunstung: Anwendungsorientierte Meßverfahren und Bestimmungsmethoden. https://doi.org/10.1007/978-3-642-70434-5_8.\n", + "\n", + "Xu, C.Y., & Singh, V.P. (2001). Evaluation and generalization of temperature-based methods for calculating evaporation. Hydrological Processes, 15, 305-319. https://doi.org/https://doi.org/10.1002/hyp.119.\n", + "\n", + "Thom, A., & Oliver, H. (1977). On Penman's equation for estimating regional evaporation. Quarterly Journal of the Royal Meteorological Society, 103, 345-357. Publisher: Wiley Online Library.\n", + "\n", + "Turc, L. (1961). Estimation of irrigation water requirements, potential evapotranspiration: a simple climatic formula evolved up to date. Ann. Agron, 12, 13-49.\n", + "\n", + "Walter, I.A., Allen, R.G., Elliott, R., Jensen, M., Itenfisu, D., Mecham, B., Howell, T., Snyder, R., Brown, P., Echings, S., et al. (2000). ASCE's standardized reference evapotranspiration equation. In Watershed management and operations management, pp. 1-11.\n", + "\n", + "Wright, J.L. (1982). New evapotranspiration crop coefficients. Proceedings of the American Society of Civil Engineers, Journal of the Irrigation and Drainage Division, 108, 57-74." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/data/example_1/klima_daily.csv b/docs/examples/data/example_1/klima_daily.csv similarity index 100% rename from examples/data/example_1/klima_daily.csv rename to docs/examples/data/example_1/klima_daily.csv diff --git a/examples/data/example_0/0_example_meteo.csv b/docs/examples/data/example_10/10_example_meteo.csv similarity index 100% rename from examples/data/example_0/0_example_meteo.csv rename to 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:caption: Click on one of the examples below: - :name: rst-gallery - :glob: - - ./* \ No newline at end of file diff --git a/examples/utils.py b/docs/examples/utils.py similarity index 100% rename from examples/utils.py rename to docs/examples/utils.py diff --git a/examples/00_example_paper.ipynb b/examples/00_example_paper.ipynb deleted file mode 100644 index b4fb8e8..0000000 --- a/examples/00_example_paper.ipynb +++ /dev/null @@ -1,1891 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "69c4d9fe", - "metadata": {}, - "source": [ - "# Improved handling of potential evapotranspiration in hydrological studies with PyEt\n", - "\n", - "This notebook is supporting the manuscript: Vremec et al. \"Technical note: Improved handling of potential evapotranspiration in hydrological studies with *PyEt*\". In preparation.\n", - "\n", - "*M.Vremec (University of Graz), R.A Collenteur (Eawag)*\n", - "\n", - "Data source: \n", - "\n", - "* Example 1: KNMI - https://www.knmi.nl/home\n", - "* Example 2: E-OBS https://www.ecad.eu/\n", - "* Example 3: ZAMG - https://data.hub.zamg.ac.at\n", - "\n", - "### The supporting Notebook is structured as follows:\n", - "\n", - "* Benchmarking PET methods\n", - "* Example 1: Estimation of PET from station data\n", - "* Example 2: Estimate PET for gridded data\n", - "* Example 3: Calibration of PET models\n", - "* Example 4: The effect of $CO_2$ on future PET estimates" - ] - }, - { - "cell_type": "markdown", - "id": "c554ae6a", - "metadata": { - "tags": [] - }, - "source": [ - "## Import packages" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "75050118", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python version: 3.9.13 (main, Oct 13 2022, 21:23:06) [MSC v.1916 64 bit (AMD64)]\n", - "Numpy version: 1.21.5\n", - "Pandas version: 1.4.4\n", - "Pyet version: 1.2.2b\n" - ] - } - ], - "source": [ - "# 1. Import needed Python packages\n", - "import numpy as np\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib import cm\n", - "import xarray as xr\n", - "import seaborn as sns\n", - "\n", - "from scipy.optimize import least_squares\n", - "import pylab\n", - "import matplotlib.dates as mdates\n", - "\n", - "import pyet\n", - "from utils import *\n", - "pyet.show_versions()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "f3398063", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "import warnings\n", - "warnings.filterwarnings('ignore')" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "4a79810c", - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "#edit default values for plots\n", - "params = {\n", - " \"font.family\": \"Arial\",\n", - " \"legend.fontsize\": \"15\",\n", - " \"axes.labelsize\": \"16\",\n", - " \"xtick.labelsize\": \"15\",\n", - " \"ytick.labelsize\": \"15\",\n", - " \"xtick.direction\": \"in\",\n", - " \"ytick.direction\": \"in\",}\n", - "pylab.rcParams.update(params)" - ] - }, - { - "cell_type": "markdown", - "id": "dc0ebed8", - "metadata": { - "tags": [] - }, - "source": [ - "# 0. Benchmarking PET methods" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "f28a15f4", - "metadata": {}, - "outputs": [], - "source": [ - "# Read results from Guo et al., 2016\n", - "df_guo = pd.read_excel(\"data//example_0//df_Guo_2016.xlsx\", index_col=\"daily\", \n", - " parse_dates=True).iloc[:50, :]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "095d995c", - "metadata": {}, - "outputs": [], - "source": [ - "# Define input variables\n", - "lat = -0.6095\n", - "elevation = 48\n", - "\n", - "rs = pyet.calc_rad_sol_in(df_guo[\"n\"], lat, as1=0.23, bs1=0.5, nn=None) # Compute solar radiation [MJ/m2day]\n", - "tmax = df_guo[\"Tmax\"] # Daily maximum temperature [°C]\n", - "tmin = df_guo[\"Tmin\"] # Daily minimum temperature [°C]\n", - "tmean = (tmax+tmin)/2 # Daily mean temperature [°C]\n", - "rhmax = df_guo[\"RHmax\"] # Daily maximum relative humidity [%]\n", - "rhmin = df_guo[\"RHmin\"] # Daily minimum relative humidity [%]\n", - "rh = (rhmax+rhmin)/2 # Daily mean relative humidity [%]\n", - "uz = df_guo[\"uz\"] # Wind speed at 10 m [m/s]\n", - "z = 10 # Height of wind measurement [m]\n", - "\n", - "wind_penman = uz * np.log(2/0.001) / np.log(z/0.001) # wind speed at 2 m after Penman 1948\n", - "wind_fao56 = uz * 4.87 / np.log(67.8*z-5.42) # wind speed at 2 m after Allen et al., 1998\n", - "\n", - "lambda1=pyet.calc_lambda(tmean=tmean) # Latent Heat of Vaporization in PyEt [MJ kg-1] \n", - "lambda0 = 2.45 # Latent Heat of Vaporization in Guo et al., 2016 [MJ kg-1] \n", - "lambda_corr = lambda1 / lambda0 # Correction factor" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "87ac4b76", - "metadata": {}, - "outputs": [], - "source": [ - "# Benchmarking against R-Evapotranspiration package\n", - "df_pyet_guo = pyet.calculate_all(tmean, wind_fao56, rs, elevation, lat, tmax, tmin, rh, \n", - " rhmax=rhmax, rhmin=rhmin)" - ] - }, - { - "cell_type": "markdown", - "id": "7b5b076e", - "metadata": {}, - "source": [ - "### Test Penman" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "2bf863e5", - "metadata": {}, - "outputs": [], - "source": [ - "#%%timeit\n", - "pyet_penman = pyet.penman(tmean, wind_penman, rs=rs, elevation=elevation, lat=lat, tmax=tmax, \n", - " tmin=tmin, rh=rh, rhmax=rhmax, rhmin=rhmin, aw=1, bw=0.526, albedo=0.08) * lambda_corr" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "2f5ce8ab", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_penman.iloc[:10].round(1).values, df_guo[\"Penman\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "340e434b", - "metadata": {}, - "source": [ - "### Test FAO-56, ASCE, Penman-Monteith" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "62525eda", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(df_pyet_guo[\"FAO-56\"].iloc[:10].round(1).values, df_guo[\"PM\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "d76c406a", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_pmasce = pyet.pm_asce(tmean, wind_fao56, rs=rs, elevation=elevation, lat=lat, tmax=tmax, \n", - " tmin=tmin, rh=rh, rhmax=rhmax, rhmin=rhmin)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "78b598a6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_pmasce.iloc[:10].round(1).values, df_guo[\"PM\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "9e798b43", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_pm = pyet.pm(tmean, wind_fao56, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh, \n", - " rhmax=rhmax, rhmin=rhmin) * lambda_corr" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "a984d6b7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_pm.iloc[:10].round(1).values, df_guo[\"PM\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "a2d92a3b", - "metadata": {}, - "source": [ - "### Test Makkink" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "1b645390", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_makk = (pyet.makkink(tmean, rs=rs, elevation=elevation, k=0.61) * lambda_corr - 0.12) " - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "d8da4e2e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_makk.iloc[:10].round(1).values, df_guo[\"Makkink\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "df438315", - "metadata": {}, - "source": [ - "### Test Priestley-Taylor" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "90229e51", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal((df_pyet_guo[\"Priestley-Taylor\"]*lambda_corr).iloc[:10].round(1).values, df_guo[\"PT\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "a073713e", - "metadata": {}, - "source": [ - "### Hargreaves" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "2845cbec", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_hargreaves = pyet.hargreaves(tmean, tmax, tmin, lat, method=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "5be2a361", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_hargreaves.iloc[:10].round(1).values, df_guo[\"Har\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "15d8f37b", - "metadata": {}, - "source": [ - "### Test Hamon" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "9a32920b", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_hamon = pyet.hamon(tmean, lat=lat, n=df_guo[\"n\"], tmax=tmax, tmin=tmin, method=3)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "30f49a9c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 20, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_hamon.iloc[:10].round(1).values, df_guo[\"Hamon\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "c40e2662", - "metadata": {}, - "source": [ - "### Blaney Criddle" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "e469cdc6", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_bc = pyet.blaney_criddle(tmean, lat, rhmin=rhmin, wind=wind_fao56, method=2, n=df_guo[\"n\"], clip_zero=False)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "e39a847b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_bc.iloc[:10].round(1).values, df_guo[\"BC\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "7cf4c577", - "metadata": {}, - "source": [ - "### Romanenko" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "3054678f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(df_pyet_guo[\"Romanenko\"].iloc[:10].round(1).values, df_guo[\"Romanenko\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "039b841b", - "metadata": {}, - "source": [ - "### McGuinness-Bordne" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "bb04f835", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal((df_pyet_guo[\"Mcguinness-Bordne\"]*lambda_corr).iloc[:10].round(1).values, \n", - " df_guo[\"McG\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "f298f524", - "metadata": {}, - "source": [ - "### Jensen-Haise" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "98ccfd66", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal((df_pyet_guo[\"Jensen-Haise\"]*lambda_corr).iloc[:10].round(1).values, \n", - " df_guo[\"JH\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "9a9a13a1", - "metadata": {}, - "source": [ - "### Linacre" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "a2f18b60", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_linacre = pyet.linacre(tmean, elevation, lat, tdew=df_guo[\"Tdew\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "94104178", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_linacre.iloc[:10].round(1).values, \n", - " df_guo[\"Linacre\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "84fe4a0c", - "metadata": {}, - "source": [ - "### Abtew" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "c97f2184", - "metadata": {}, - "outputs": [], - "source": [ - "pyet_abtew = pyet.abtew(tmean, rs, k=0.52) * lambda_corr" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "b565fe5d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(pyet_abtew.iloc[:10].round(1).values, \n", - " df_guo[\"Abtew\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "1b6a0fc9", - "metadata": {}, - "source": [ - "### Turc" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "460dddcb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.array_equal(df_pyet_guo[\"Turc\"].iloc[:10].round(1).values, \n", - " df_guo[\"Turc\"].iloc[:10].round(1).values)" - ] - }, - { - "cell_type": "markdown", - "id": "71cc537f", - "metadata": {}, - "source": [ - "### Benchmarking against McMahon et al. 2016" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "9d5fb0eb", - "metadata": {}, - "outputs": [], - "source": [ - "# Benchmarking against McMahon et al. 2016\n", - "# Makkink # Based on example S19.91, p 80 McMahon_etal_2013\n", - "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "rs = pd.Series([17.194], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "elevation = 546\n", - "mcm_mak = [2.3928, (pyet.makkink(tmean, rs, elevation=elevation, k=0.61)) -0.12] # correction for different formula in McMahon_2013\n", - "# Blaney Criddle # Based on example S19.93, McMahon_etal_2013\n", - "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "rhmin = pd.Series([25], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "wind = pd.Series([0.5903], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "n = pd.Series([10.7], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "py = pd.Series([0.2436], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "lat = -23.7951 * np.pi / 180\n", - "mcm_bc = [3.1426, pyet.blaney_criddle(tmean, lat, wind=wind, n=n, rhmin=rhmin, py=py, method=2)]\n", - "# Based on example S19.99, McMahon_etal_2013 # Based on example S19.99, McMahon_etal_2013\n", - "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "rhmean = pd.Series([48], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "rs = pd.Series([17.194], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "mcm_turc = [pyet.turc(tmean, rs, rhmean, k=0.32), 2.6727]\n", - "# Based on example S19.101, McMahon_etal_2013\n", - "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "tmax = pd.Series([21], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "tmin = pd.Series([2], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "lat = -23.7951 * np.pi / 180\n", - "mcm_har = [4.1129, pyet.hargreaves(tmean, tmax, tmin, lat, method=1)]\n", - "\n", - "# Based on example S19.109, McMahon_etal_2013\n", - "tmean = pd.Series([11.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "rn = pd.Series([8.6401], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "elevation = 546\n", - "mcm_pt = [2.6083, pyet.priestley_taylor(tmean, rn=rn, elevation=elevation, alpha=1.26)]" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "fc107162", - "metadata": {}, - "outputs": [], - "source": [ - "# Based on example 5.1, P89 Schrodter 1985\n", - "tmean = pd.Series([17.3], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "lat = 50 * np.pi / 180\n", - "sch_bc = [3.9, pyet.blaney_criddle(tmean, lat, method=0)]\n", - "# Based on example 5.2, P95 Schrodter 1985\n", - "tmean = pd.Series([21.5], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "ea = pd.Series([1.19], index=pd.DatetimeIndex([\"1980-07-20\"]))\n", - "e0 = pyet.calc_e0(tmean)\n", - "rh = ea / e0 * 100\n", - "sch_haude = [3.6, pyet.haude(tmean, rh=rh, k=0.26 / 0.35)]" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "761295d8", - "metadata": {}, - "outputs": [], - "source": [ - "# Benchmarking against FAO-56\n", - "# Hargreasves # Based on example S19.46,p 78 TestFAO56\n", - "tmax = pd.Series([26.6], index=pd.DatetimeIndex([\"2015-07-15\"]))\n", - "tmin = pd.Series([14.8], index=pd.DatetimeIndex([\"2015-07-15\"]))\n", - "tmean = (tmax + tmin) / 2\n", - "lat = 45.72 * np.pi / 180\n", - "fao_har = [5.0, pyet.hargreaves(tmean, tmax, tmin, lat)]\n", - "\n", - "# Based on Example 18, p. 72 FAO.\n", - "wind = pd.Series([2.078], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", - "tmax = pd.Series([21.5], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", - "tmin = pd.Series([12.3], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", - "tmean = (tmax + tmin) / 2\n", - "rhmax = pd.Series([84], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", - "rhmin = pd.Series([63], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", - "rs = pd.Series([22.07], index=pd.DatetimeIndex([\"2015-07-06\"]))\n", - "n = 9.25\n", - "nn = 16.1\n", - "elevation = 100\n", - "lat = 50.80 * np.pi / 180\n", - "fao_56 = [3.9, pyet.pm_fao56(tmean, wind, elevation=elevation, lat=lat, rs=rs, tmax=tmax, tmin=tmin, rhmax=rhmax,\n", - " rhmin=rhmin, n=n, nn=nn)]" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "d09eb52a", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "figw_1c = 8.5 # maximum width for 1 column\n", - "figw_2c = 17.5 # maximum width for 2 columns\n", - "cm1 = 1 / 2.54 # centimeters in inches\n", - "fs = 15\n", - "ms1 = 20\n", - "ms2 = 60\n", - "\n", - "fig,axs=plt.subplots(ncols=7, nrows=2, figsize=(figw_2c,5))\n", - "axs[0,0].scatter(df_guo[\"Penman\"], pyet_penman, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,0].text(0.04, 0.9, \"Penman\", transform=axs[0, 0].transAxes, fontsize=fs)\n", - "\n", - "axs[0,1].scatter(df_guo[\"PM\"], df_pyet_guo[\"FAO-56\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,1].text(0.04, 0.8, \"FAO-56\", transform=axs[0, 1].transAxes, fontsize=fs)\n", - "axs[0,1].scatter(fao_56[0], fao_56[1], c=\"goldenrod\", marker=\"^\", s=ms2, zorder=10)\n", - "\n", - "axs[0,1].scatter(df_guo[\"PM\"], pyet_pmasce, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,1].text(0.04, 0.7, \"ASCE-PM\", transform=axs[0, 1].transAxes, fontsize=fs)\n", - "\n", - "axs[0,1].scatter(df_guo[\"PM\"], pyet_pm, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,1].text(0.04, 0.9, \"Penman-Monteith\", transform=axs[0, 1].transAxes, fontsize=fs)\n", - "\n", - "axs[0,2].scatter(df_guo[\"Makkink\"], pyet_makk, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,2].text(0.04, 0.9, \"Makkink\", transform=axs[0, 2].transAxes, fontsize=fs)\n", - "axs[0,2].scatter(mcm_mak[0], mcm_mak[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", - "\n", - "axs[0,3].scatter(df_guo[\"PT\"], df_pyet_guo[\"Priestley-Taylor\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,3].text(0.04, 0.9, \"Priestley-Taylor\", transform=axs[0, 3].transAxes, fontsize=fs)\n", - "axs[0,3].scatter(mcm_pt[0], mcm_pt[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", - "\n", - "p1=axs[0,4].scatter(df_guo[\"Har\"], pyet_hargreaves, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,4].text(0.04, 0.9, \"Hargreaves\", transform=axs[0, 4].transAxes, fontsize=fs)\n", - "p2=axs[0,4].scatter(fao_har[0], fao_har[1], c=\"goldenrod\", marker=\"^\", s=ms2, zorder=10)\n", - "p3=axs[0,4].scatter(mcm_har[0], mcm_har[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", - "\n", - "axs[0,5].scatter(df_guo[\"Hamon\"], pyet_hamon, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,5].text(0.04, 0.9, \"Hamon\", transform=axs[0, 5].transAxes, fontsize=fs)\n", - "\n", - "axs[0, 6].scatter(df_guo[\"BC\"], pyet_bc, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[0,6].text(0.04, 0.9, \"Blaney-Criddle\", transform=axs[0, 6].transAxes, fontsize=fs)\n", - "axs[0,6].scatter(mcm_bc[0], mcm_bc[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", - "p4=axs[0,6].scatter(sch_bc[0], sch_bc[1], c=\"darkviolet\", marker=\"d\", s=ms2, zorder=10)\n", - "\n", - "\n", - "axs[1,0].scatter(df_guo[\"Romanenko\"], df_pyet_guo[\"Romanenko\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[1,0].text(0.04, 0.9, \"Romanenko\", transform=axs[1, 0].transAxes, fontsize=fs)\n", - "\n", - "axs[1,1].scatter(df_guo[\"McG\"], df_pyet_guo[\"Mcguinness-Bordne\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[1,1].text(0.04, 0.9, \"Mcguinness-Bordne\", transform=axs[1, 1].transAxes, fontsize=fs)\n", - "\n", - "axs[1,2].scatter(df_guo[\"JH\"], df_pyet_guo[\"Jensen-Haise\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[1,2].text(0.04, 0.9, \"Jensen-Haise\", transform=axs[1, 2].transAxes, fontsize=fs)\n", - "\n", - "axs[1,3].scatter(df_guo[\"Linacre\"], pyet_linacre, c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[1,3].text(0.04, 0.9, \"Linacre\", transform=axs[1, 3].transAxes, fontsize=fs)\n", - "\n", - "axs[1,4].scatter(df_guo[\"Abtew\"], df_pyet_guo[\"Abtew\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[1,4].text(0.04, 0.9, \"Abtew\", transform=axs[1, 4].transAxes, fontsize=fs)\n", - "\n", - "axs[1,5].scatter(df_guo[\"Turc\"], df_pyet_guo[\"Turc\"], c=\"None\", marker=\"o\", s=20, edgecolors=\"k\")\n", - "axs[1,5].text(0.04, 0.9, \"Turc\", transform=axs[1, 5].transAxes, fontsize=fs)\n", - "axs[1,5].scatter(mcm_turc[0], mcm_turc[1], c=\"red\", marker=\"x\", s=ms2, zorder=10)\n", - "\n", - "axs[1,6].text(0.04, 0.9, \"Haude\", transform=axs[1, 6].transAxes, fontsize=fs)\n", - "axs[1,6].scatter(sch_haude[0], sch_haude[1], c=\"darkviolet\", marker=\"d\", s=ms2, zorder=10)\n", - "\n", - "for i in (0,1,2,3,4,5,6):\n", - " axs[0,i].set_xticklabels([]) \n", - " for j in (0, 1):\n", - " axs[j,i].set_xlim(0,10)\n", - " axs[j,i].set_ylim(0,10)\n", - " axs[j,i].plot([0, 10], [0, 10], color=\"gray\", zorder=-10)\n", - " axs[j,i].set_xticks([0, 5])\n", - " axs[j,i].set_yticks([0, 5])\n", - " axs[j,i].set_yticklabels([])\n", - " axs[j,0].set_yticklabels([0, 5])\n", - "\n", - "axs[0,i].set_yticklabels([]) \n", - "\n", - "axs[0,0].legend((p1,p2,p3,p4), (\"R-Evapotranspiration package, Guo et al., 2016\", \n", - " \"Allen et al., 1998\", \"McMahon et al., 2013\", \"Schrodter, 1985\"), ncol=4, loc=[0,1.02], fontsize=16)\n", - "fig.supxlabel(\"$PET_{benchmark}$ [mm/day]\", x=0.475, fontsize=16)\n", - "fig.supylabel(\"$PET_{pyet}$ [mm/day]\", fontsize=16)\n", - "fig.subplots_adjust(wspace=0.05, hspace=0.05, left=0.05)\n", - "plt.tight_layout()\n", - "#fig.savefig(\"figure0.png\", dpi=600, bbox_inches=\"tight\")" - ] - }, - { - "cell_type": "markdown", - "id": "38a45751", - "metadata": { - "tags": [] - }, - "source": [ - "# Example 1: Estimation of PET from station data" - ] - }, - { - "cell_type": "markdown", - "id": "c95c4c06", - "metadata": {}, - "source": [ - "In this example potential evapotranspiration is estimated for the town of De Bilt in The Netherlands using data provided by the Royal Netherlands Meteorological Institute (KNMI). The reference method used by the KNMI for the estimation of potential evapotranspiration is the Makkink method, also implemented in *PyEt*. The $PET$ computed with the Makkink method is compared to the $PET$ values from all other methods in *PyEt*. A number of steps are taken in a Python script to estimate $PET$. The code implementing these steps is shown in the code example bellow. *PyEt* provides a convenience method to compute the $PET$ with all available methods, *pyet.calculate_all()*.\n", - "\n", - "Data source: KNMI - https://dataplatform.knmi.nl/" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "cfecbf10", - "metadata": {}, - "outputs": [], - "source": [ - "# Load the meteorological data.\n", - "meteo = pd.read_csv(\"data//example_0//0_example_meteo.csv\", index_col=0, parse_dates=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "ab21af19", - "metadata": {}, - "outputs": [], - "source": [ - "# Determine the necessary input data for the $PET$ model.\n", - "tmean, tmax, tmin, rh, rs, wind, pet_knmi = (meteo[col] for col in meteo.columns)\n", - "lat = 0.91 # define latitude [radians]\n", - "elevation = 4 # define elevation [meters above sea-level]" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "f6c9470f", - "metadata": {}, - "outputs": [], - "source": [ - "# Estimate the potential evapotranspiration with all methods or the method of choice.\n", - "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax, tmin, rh)" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "fa4973b5", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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YIO+//35p23ZC4/fpp59KQJ511lkJ+xg/frz0eDzSNM2E+5XASn9s25b+Br+0bbtDxymB1fP01PepN9uYn3/+WRqGEfWYAdLlcsmff/55m86lP6I8gf2P7rAxaReD1RqZmZnstddejBs3bpv6ueyyy1izZg0XXnghQoiEbZYtWwbA+PHjE+4fP348gUCANWvWbNNYFKlBSsmi3z3A5QfM4fbzHojL4q3ov/RWGyOl5KKLLkq6XX2+O8aCBQvYtGkTAJs2bWLhwoUpHpGiN5LyUjl///vft+n4c889t8PHHHjggW22qaqqAqCgoCDh/ry8vLh2yWi+Csnj8eDxeNp8fUX3EvQHKfphLbYGq75fS9AfxONT70tfpD/YmBUrVvDWW2+12GeaJm+99RbLly9nypQpbY5JAatWrWLhwoXYtg04tSkXLlzIWWedxYQJE1I8OkVvIuUC67zzzkv6C681pJQIITpl/NpDXV0dQFIxFNnu9/tb7WfUqFFxz+fOncv111+/7QNUbBNSSlbskENdtous2pD6hd+H6W82JhbDMDj00EOZPHlyJ0fZv2jLE/jGG2906rOUiFdffZWLL76Ye+65hxkzZnRJn4r0IuUC66yzzmrxgf30009ZuXIlQ4YMYfr06RQWFmIYBhs3buTNN99k1apVTJ06lenTp3fbuLxeLwDBYDDh/kAgAEBWVlar/axfv56cnJzoc+W9Sg8CpkVdtguAumwXAdPCm+IxKbqH/mJjioqK2HPPPePyZwkhuPfee7tMFPR1li9f3iOewIaGBi688EJKSkq48MILOeSQQ8jIyNjmfhXpRcoF1uOPPx73/MMPP+Rf//oX5557Lvfdd18LQWLbNldffTV33nknM2fO7LZxRdz2ydzzke25ubmt9pOTkxMnsBQKRc/SX2zMrrvuypVXXsktt9wS3XfllVcmjfFStGTy5MkcccQRvPvuu3FCtas9gYlivObNm9clfSvSh7QLcp8zZw6jRo3ioYceSujt0TSN2267jYkTJ3LjjTd22zgiv1KKiooS7i8qKiIzM5PRo0d32xgUCkXXo2yMIhkRj1+ikIGu8gQmi/FatWrVNvetSC/STmB99dVX/PKXv0TX9aRthBDsvPPO/PTTT902jt12243s7Gw++OCD6BchQnFxMUVFRUydOrXVcSr6OipuqzfSV23MqlWrWLRoUdy2RYsWqRt3B5kwYQJTp06N2zZ16tQu8QSq1Z79i7QTWLm5uaxYsaLVNlJKvvvuOwYOHNht4/B6vZx++umsWbOGu+++O7rdsiyuvPJKAP70pz912+sr0hcpJaFgiKA/hBlUAfK9jb5oY9SNu+tYtWoVn332Wdy2zz77rE2h2p4SRZEYr+Z1JmNjvBR9h7QTWIcccgg//PBD0rwjUkquuuoqfv75Z4499thuHctNN93E2LFjufzyyzn22GOZOXMme+65Jy+++CInn3wyxx13XLe+viI9CfqDSNu5Ydm2JOhPHKSsSE/6oo1RN+6uobNCNRK0vnbtWi688EIaGhoStovEeBlGfPizYRgceeSRarVnH0PINPtps2rVKvbcc0+qq6vZddddOfLII6NV6IuLi3nllVdYsWIFI0eO5PPPP2fIkCHb/JpCCEaMGMGGDRta7Nu0aRPXXXcdixcvprq6msLCQs455xwuvfRS3G530j5ramrIzc2lurpaBbmnIdU19Rx2zX3R52/f/CdyczLbdWzplmr2feLh6PNPzv4DQwpaD0RWbBtd+X3qizYmOzubo446Kmlw9uuvv65WEraDZcuWsf322yfdv3Tp0oSrCK+77jrmz5+PbdtomsY111yTNGh91apVTJkyJe59crlcLFu2TC1ISCHdcs/uspzwXciXX34pd9lll2hNME3TpKZp0ecHHHDANpey6G5UqZz0pqq6Tu5x0S3Rv6rqunYfu7mySo6//dbo3+bKqm4cqULKrv8+9UUbk6xUzqpVq5L2oertxWPbtjziiCNaXEfDMOSRRx6ZsKxWZ0oUqZqR6Ud33LNTnqYhEbvvvjvffPMNS5Ys4cMPP2Tjxo0IIRg5ciSHHnoou+++e6qHqOjHSCmxdYEUICQqvqUX0hdtzIQJE5g5cyY333xzNEnqzJkzk3pFVC6mlkRWESaaqku0ilB2MjHprFmzeOyxxygpKWH48OHdmg5EkTpSLrCuvfZapk+fzt57742mNYWECSHYd9992XfffVM4OoWiJQHLQoZtphTOc0X60p9szKWXXsr8+fOjAuuSSy5J2lblYkrMhAkTGD58OOvXr49uGzZsWEKh2tnEpBkZGTzwwAPRTO79Xdj2VVIe5H7bbbex//77M2jQIE499VT+8Y9/UFZWluphKRSdxrYltq28WulCf7Ixd911V9SjKqWMW50Yi8rFlJx33303TlyBky3/3XffbdF2W4LWZ8yYQXFxsSqT04dJucCqqKjgueee4/jjj+e///0vZ599NsOHD2ePPfZg7ty5fPbZZ2oKRpFWyGb5r2Kf27bklAef4pQHn1IiK03oLzYmIppiBVYi0dTWtFZfuBadxbZtTjnllIT7TjnllBb5yiJTis1JdYmi9qSMUHQ/KRdY2dnZnHTSSTz66KNs2LCBb775hnnz5uH1epk/fz777rsvgwYN4owzzuBf//oXFRUVqR6yop9jBkJJn9f4AwkfK1JHf7AxHRFNKqVDcl5//XUqKysT7qusrOT1119vsT0S+xaZftY0rdXYt+6mvSkjFN1PygVWc3bZZRdmz57Nxx9/THl5OU899RRHH3007733Hr/5zW8YOnQoe+21F/PmzePzzz9P9XAVCkUvoy/amI6IJpWLKTnTp09nwIABCfcNHDgwafHvWbNmMWzYMICUB60niq1TpIa0E1ix5OXlccopp/DEE0+wadMmPv/8c+bMmYOmacybN69FOQOFoueQzhJCVS6nV9NXbExHRFO6TmulA5qm8eyzzybc9+yzz8YtkoglErQ+ZswY7r///pQFravYuvQirQVWc375y18yZ84cPv30UzZv3sw//vGPVA9J0Q+RUuId2EjmsHq8Axv7dcxKX6O32piOiqYJEyaw9957x23be++9VaJLnEz/++23X9y2/fffn4MPPrhLX6er46RUbF36kfYCy7bthH8FBQWceuqpqR6eolcTmxuw/QSlhe52fiHqbpugVGkaejN9xcZ0JBZo1apVfPrpp3HbPv30U+XpCPPSSy9Fr6Ou67z44outtu9o3FN3xEmp2Lr0Iy0F1p133sn222+P2+3G5XIl/WutjIRC0RpSSkxTEgrZmKZUv+76GX3VxrQnFiji0Ug0Fag8HQ4DBw5k9uzZ6LrOrFmz2iz63dG4p+6Ik1KxdelH2gmsBx54gCuvvJLly5djmiZSyqR/zZfMKhTtJRgIxS1nDzZbGbgtyPB/ivSkL9uY9sQCKU9H+7jxxhsxTZMbb7yx1XYdjXvqrjgpFVuXfqSdwLrvvvvQNI2HH36YLVu2JHXfR/4UinTClpKlopKlohJbeQLSkr5uY9pKYKk8HV1HR+OeujtOKt1SRvR30k5grVmzhoMPPpjzzjuPvLy8VA9HoegQtcFAwseK9KG/2xjl6eg6OuoN7AnvYTqljOjvpJ3AGjlyJJaq7aZQKLoJZWOUp6Or6Kg3sCe8hxkZGZxzzjnous5vf/tbVecwhaSdwDrvvPP45JNP+OGHH1I9FIVC0QfpazZGSkl9fT319fXU1dVRVlZGWVkZdXV11NfXJ512Up6Obaej3sCe8B42NDTw2GOPYVkWjz32mMrknkKMtpv0LFdddRXfffcd++23HxdddBG77LJLqys4ujo3iULRPlR8VW+lr9mYhoYGhg8fnnR/XV0dmZmZLbZHAuIvvvhi7rnnHuXp6CQRb+D8+fOxbbtNb2Ck/c0334yUEiFEl3oPE61QnDdvXot2UkoaGhqi/4LzmYiIvNjHis6RdgKroaGB+vp6amtr21y6KoRoMZetUHQ3Ukryshpx6RYhS0/gIVDiK51RNqaJGTNmJA2G7++8+uqrUfGZ7BpFxMnFF1/Mo48+yqZNmxg2bBgXX3xxVDwl4tJLL2X+/PnRNpdcckmXjDnZCsWzzjqLCRMmxLVtaGggKysraV/JhHlnaM+17IukncC6+uqr+c9//oMQgsmTJzNo0CClohVpRUiauHQnhselW4Rk0w3YlhK/bUUfK9KPvmZjMjIyqKurA6C+vp4hQ4YAUFpaSmZmZqueqf5642uLhoYGzjnnHCorKznnnHNYt25dwuuYSKSUlJQwePDgVgXKXXfdFZcm5u67707oZeoIba1QfOONN1LyOY8kVS0pKeHCCy/kkEMO6Tfe0rQTWC+99BI5OTm8//777LrrrqkejqIPIwEEXepwqgsEEj5WpA99zcYIIRLeyDMzM1v1QPTnG19bzJs3j8rKSgAqKyu58cYbWbBgQZf0HfEyxQqsZF6mjhBZodic2BWKU6ZMiW6PCPNEojyyvyto75RlXyTtgtyrqqqYNm1anzB8ivRFSknDKI2G7aBhlJY0ENi2JbatPFF9CWVjHLojm/i20tX1+TrDqlWruO222+K23XrrrQkTgUZESmlpaXRbaWkpdXV1CQVKd+bB6ugKxYgwjxXhkeeZmZld4u3q78Wn005gTZo0KfrLQaHoLvyWyX57LOe4vb5mvz2W47daxtnYtuSUB5/ilAefUiKrD6FsTHre+LqjPl8s7RFvUkrOPffcFglmbdvm3HPPbSGAWhMpiQRKd+fBuvXWW1tsE0Ik3N7dqOLTaSiwLr74YpYsWcJrr72W6qEo+jCmDDKwoBbhthlYUIspgy3a1PgDCR8rejf93cak642vOz1q7RVvy5Yt4+OPP0647+OPP2bZsmXbNI6IlylR+oZtzYPV0NDALrvs0kK8hUIhdt555x5P16BKMqVhDNbUqVM5+uijOe644zjmmGPYa6+9KCgowOVyJWx/7rnn9vAIFX2BkLRAhG8kQjrPFf2C/m5jOhqr0xN0ZPVbZ0iXOCAhBH/+859bXH8pJVdddVWvXmzRnIiYfPfdd+NElmEYHHroof2iJFPaCawdd9wRIQRSSl555ZU25+L7mvFTdBwpJQHbxKMZPWOgmv/C7weu7r5Ef7cx6Xbj6+7Vbx0Rb1OmTGG//fbjv//9b4t+DjjggG0WnlJKbrvtNjRNi5uG1DSN2267jYMPPrjT55ooaP3JJ5/kxBNPjO7vSSLJU5tfs/5UkintBNZZZ53VLy68omuQUjL3+5f5uWYzk3KGcv3Ox3f75ydkWq0+V6Q3/d3GpNuNrzs9ah0Vb0IIHnvsMSZOnNjimL///e/bfG2Snatt29t8rolWk5544oldlsuqM0yYMIErr7ySW265Jbrtyiuv7DclmdJOYD3++OOpHoKiFxGwTX6u2QzAyprNBGwTr554qqerCDYTVM2fK9IbZWM6nn28O+lOj1pnxVsiD1NXxKalm/dQ0b2kXZC7QpEKumKWT0rJHe98su0dKRQ9QLrUIuzO+nwdTV0Q8WwlWkXYFQsAeqIWYTqxatUqFi1aFLdt0aJF/SZNQ9p5sCJ8/vnnrFq1Cr/f32q7vhYfoWhCSknAtPAYercbnifmPsOCR69u1+skM7EB06K8pi763G3oXTQ6RXfQ321MOtUi7C6PWkenQ5N5vIAuWwDQX6bNkq1KjYjVVGWW70nSTmCVl5dzxBFH8N1337WrfV81fv0dKSXXvvQ2KzeXs93QQdx4wmFd+mVs/kO0dE05QX8Qj88T366ZnJJS8tj/voFRLcfrt0Lh9s4xfd149FaUjWkinWoRzpo1i8cee4ySkpIu9ah1RLxNmjQJl8tFKBRqsc/lcjFp0qQuGVPz/hO9Xm8nmVi1LCtlq1V7mrQTWH/+85/59ttvyc/PZ//99ycvL0/dqPohAdNi5eZyAFZsLscfMhE6XbJSUErJE3OfgT+13s6WknVDiqOPAfwhk411dYBEQ2IjkMDc719mRfUmtgyoI8PVEHeMIr1QNiY96U6PWnvF2xtvvJFU7IRCId544w2OOeaYbRrLqlWruPPOO+O23XHHHVxwwQVdkpIiXZg8eXLSFZn7779/v4g3SzuB9c477zBw4EB++uknBg0alOrhKNIAieSmH19hVV0pk3OGcf0u8SsFHRe0xCks2DZBf5DSNeW09emqCTXSKKzo43zpZd4P/yEwZTk75W0i2/BTE/ISkE2B9iFXU8LSekslJ01H+ruNkVLS0NAQ/RcccRP5TsU+7mm6y6PWXvE2ffp0srOzqa2tbbEvJyeH6dOnb9M42soU/+GHH/Ypsd+XzqUzpJ3Aqq6u5ogjjuiXhk+RGCkkH65fSdA02VRVw8wdQ/gMt7NPSurlZiwC6HjbFYRq25K1RxlhgeVUe157lNHi2LpgIO5xwDZZWbsRDUm24cTt5Lj8/OvLr5GFYKlyOr2C/m5jGhoayMrKSrq/rq4upUv7u4v2ijfLSrwquHlG8s7Qnkzx22+//Ta/TnfQmjBPJMqXL1/e6rn2hynCtFtFuMcee7BixYpUD0ORRkgkmnsrWTlVCFclDcEmL1HQNrFwhJCFn6DduhGUUnLbhQ8QKHCElYYNSAIFgkDCY5tiqhyc49y6hVt3DHFpXQMryytYWV5BUFoJjlGkE8rGpC+pLva8ePHipCVlGhoaWLx4cQ+PKH2ICPPs7GyGDBnCkCFDyM7OJisrK+E1mzx5Mvvvv3/CvppPEUopqa+vp76+nrq6OsrKyigrK4smTu2tdQvTTmDNmzeP5cuXc8MNN7Rwoyr6J7a0MQxHzOiGzT0/P9PpL1zQH2TDz5tA2EzIKGfHrBImZJTTXBBJKbn757cYmFvLwNzauHgqTTRrq1mYthU9blBuHYNy6zDS7+ulQNmYSMbv0tLS6LbS0lLq6uqoq6tL2WrC7i72nA5EMsUnoisyxacb7bXTEfHWEQHXG0i7KcL99tuPBx54gD/84Q88+uij7LjjjgwcODBhWyEETzzxRA+PUJFqNgcqCdohPLq7w8fats2ayy1y8oNkGQGkhEw9gKHFTwsEbJOKYDUR4WVJs8WKwgiycB25QHVtBkI0ea/8UsVgpSP93cYkyvidmZmZ8mnB7qgX2NF4s2OOOYacnBxqampa9JWTk7PNAe5CCK6//noOPfTQFvvmzJmT1jFLiUrxlJaWkpmZmVCUL1++PGGAO/SfKcK0E1hffPEFV1xxBQAbNmxgw4YNSdv2RePX34n1KMho0oNmHiM6PwFXZ/mRuTIuHF4IEsbHS2xGZVaHx2Vy7pJHE/YZkjaGSyKExNZsRmU5x0jZ/7wjvQFlY9KP7ir23NF4M03TePHFFxMKoJdeeglN2zavtJQy6QrGmTNn8vnnn6etyOqoMI8keX3nnXfi4tp0Xeewww6LmyKMiDeg3QKuN5B2Ausvf/kLdXV1/PKXv+TXv/41gwYNStsPnKJrsW2bi/aaBcBtH8+jWFTTQAiv0MiN+Qhs9ldzx4pnmDnlN0gpCQVMpJTRAr6tIaXEEBYHDV4RlwvryMk/RnNZeTTnayHtpuXaG6vKnP2itHmXUQry6uL6bO4VU6QHysakF91d7LmjHHLIIey1117873//i27be++9Ofjgg7e576VLl/Lll18m3Pfll1+ydOlSdthhh21+nXQgWZJXTdNaJHlNJN4gPTyr20LaCawvv/ySSZMmsWTJkhblDRR9m7qq+ujjyi01VAcbkbbE1CW5Me2CtsX6xjKCdohQIBgVVY7YCoIn8RdSSklR3a2cOPLrcPaqJvJ99SxY/jLr/HVMyhnKzB2PxpJOADwIGk0Tx6fliK5kSSF0LaZ+mVAxWOmIsjHpRXcWe25tWiuyP5bIVOIzzzzDuHHjoj/cnnnmGerr67c5hUVRUVGb+/uKwIL0qnmZCtLuDmAYBjvuuKMyfP0cMxBC2k3CyUGGhVFzL1XT9mRxUgC2DFBvrY7btqJhaPTx+sat6JisrNmEPxTgmMGvc3D+8vjXk83+BXAl9lT1xwDq3oCyMemDlJJRo0Zx6KGHouvxpaUMw+CII47YpoSUEc9IrBck8jwzM7OFWIpMKRYWFsb9cBs7dmyXBFu3JSz6ovBIl5qXqSDtLMz+++/Pl19+iWVZLb5wiv6MZLCvDo9uYUoXUg5C4uSsGZhVh1c38VsG9695kbk7/67dvzJjddJe+R+S7aqmOjSA+obpuN1O2gaXsNDdRvSI4ZlNSQhdmkWyiLCGusaOn6ai21E2pmN0NFC8I/mSGhoayM7OTvi6pmly22239anp2+23355f/vKXCacJ99hjj7TNgbUtpFPNy54m7TxY8+fPp6KigrPPPpvKyspUD0fRCWwpO10mJlkAuwA84bxTLhECbO5Y+QyVjfVMzVvNgfkr2DtvNRv9ztRh/Hhs7DYCzjWXxGdXEPQHyZSl1Fu1xNp1D25q5DqsZrmyhGhv/nhFuqBsTMdoLf9RIq9OR/Mltca4ceO68lTapLtTWAghuPjiixPuu+iii/qUmIxlxowZFBcXp03dy54i7TxYTzzxBHvttRdPP/00zzzzDOPHj6egoACXy9WirRCCDz/8MAWjVCTDlpJjX/gnAK+cdCZaGwYjInw0oWFLyZd7FwAtizHHEhFhJQ3lBLPryDUcT1Ge0YiGGdcvwCVf3wHAHb+4MGmfQkiky0azwTZtgoFg3P5/bv6EYCDI4Oy6Vs5GMsTXtN/n87XSVpEqlI1JH2JXj5WXl1NYWAjAsGHD+O6773rc29HdKSxs246uYG3OFVdcwZlnnhldqRjrAWxv9vR0oTePvStJO4H117/+NfpYSsnPP/+ctG1/eIN6G1WNjawu3xJ9XNCKgbSlzRn/fQiAf+13PtWNfkJ7O1/EmkDiHFKmpSEkoAMCHtzwAlPzm/ZL6YiviKiav/MF0X11pr+pHY73yaM7gsxnhGgw3VGf7i1Fb3FoODxr9+y1LK4fhgAMzU4a5RXZH8FIv6+XAmVjOkpHA8U7ki8p2eqxu+66q0+WMnr99deTek0rKyt5/fXXo7m2enNJo9489q4k7e4A77//fqqHoNgGamM8P7WBYFKBZds2pbXlaNLEQqc25I8rjtxgB1us9IsgaT3HVL3ZFPtUZyaOg2p+29TCgfKRDFmWbIrNydCD2FYDjqoDy0o0sy7DSUZjXkPdnNMSZWM6Rke9Ol3hBUpWVLm3e0amT5/OgAEDEoqsgQMHbnMxaUV6kXYCa9q0aakegqKbsW2bf758KjJ3M/sPEJTXZmNZvwGIiiqJzaXT3gTg7o8PZUhGa1Nz24aU8YJLc0n82qYWbSKTk3p0krLpqEgAviL9UTam99LbPSOapnH77bdz9tlnt9h3++23xyUy7c3JN3vz2LuSlAe5FxQU8Mc//nGb+7ngggsYMGBAF4xI0d34/bWQvZlAniNQBmXXUlddhZQ2v9/pQ36/04fYshbDbeLyhBg9vjy8Wq9tdGHFJRttkXg0/NRnhGiwDAKNEltCXG53AdMHfhV3mABOHvUVB+cv56AByxnt2YIIF4oWQipxlcYoG6NIF6SUPPXUUwn3/etf/4qzV7EpJhKlmUhnT113jz1SHDpRYeh0Kg6dcg9WVVVVVOluC/X19VRVVW37gBQ9ghRg62CHJb4hdGya0h/UeBYggo7s0V2OkNGiXqOmycPm36O98j5iVVUIKAAEC5Y92fSa0qZ4Sxl4YEX9YBbf8B2lK5cycXsXv7+5MPlYAY8Wv3rQp4WY6C2j0XYByY9VpB5lY/oOvd0zkiypKrDNSVX7E73Fk5lygQWwZMkSzjrrrG3uQ5F6pG0T9Aejj1vsl5Ifqm6iPlcHPbxfQhAntYNh2JFNuHQbTUiGZNWye/Zaco1GtoYy+KJqLKX+WkZlFiCRuDQTDbARmLakIVSERi52s493IBDCFDYaEAxISn+uIWAbrF/RQCggsWwNzR2v2CLC6uDBy6PjisWnhcB2pgwjMVwaElslb0grlI3pG/T2kiqTJk1C1/W42nwRdF1n0qRJKRiVortIC4G1evVqVq9e3XbDNkhnl2l/ob6mIf7xgIK4/bYMUBtai/RIqkMZ5Lmc9kJI/LIpyN3GEVcAXiMUk4qhAR1JyDaxAaQVnefWkARNk7L1FUhPyzgpIlOBIlb4Cfx2y+X5kUiwSA9eGcIMCgxveL+0sQMSzSMYllHHrlnryTMaormzqkwflq2mDdMFZWMU6cBrr72WUFyBkzT5tdde49hjj+3hUfU+OlsCqacXRqRcYD322GOpHkKbXHPNNcyfPz/hvszMzC6ZfuiLBG0rWssrFls6guqltb/gnAlLQMCaxkU8skQwbbdIq1hfkcQlLDQhsWW8QJJShmsQSlweJ+tnvS9IcW0FltQZlzWIiMgyA049wUwj1BTTJZv6aY5EsKpxEBN95TEbBRKL3J/KGTlAsKFSog22yDMiK5uc9A95RiP+2prOXzxFl6FsjCJdaKt8liqv1T46ulK1tSnF7pxOTLnASrSaIt349ttvEUJw3XXXtRALbrc7RaNKf2Z+/h67rB/GLdOOiF632FqBtoRa6SXf1cC6xp8IeSdE94kYz1MooEe9WZqQ7JG7lv+rcGpb2bbNw7OLWbeigTGTMzjt+knY7sjREktK9Ohrg+G2EdLmleu/R8qmWK6/XbuG826dhKZB0HLSMbhj4q48HgtbCid2LGAzcoDT58gBAi3ktJPSEXiRXmsb45OVKlKDsjGKdCF2lWBn9it6FykXWL2Bb7/9lnHjxnHDDTekeii9CiklyyrKCVgmXsOFlJJvy28AJB7DZPshZSxvGM60/BU0BgLsP245WS5nmtC2m4SYZsR7l7INPxkMYMFOF3DDkntYt8LxHq1d3kAoYOPyahw7+HMAvqo7Jnpcg+UkGg0FJJVr6wnETA1uLvYjzBAer4ZL2DSYrrgltk5i0lZKSYeFVez+t/yfcLjc0zkHoQynIjnKxvR9pJTRosfJ6IvFntOBjiS/7UqU1W+DiooKNm7cyC9+8YtUD6XXsb6qhpKqmuj0my0D1IXWIYF624OFQCMS6C7JcDV5fCQxcQoJpsfLautxay4O8u2Z8LVtW2LbEpdoiutyiabfExEhdOCtRza9jJQE/XY4/UJTH62NI9KbW1h4dBOvbuLRTFyaxVariku+voNLvr6jzVqIiv6LsjH9g4aGBvbcM7G9Athtt936ZLHndCA2bUSEnkh3oTxYbfDNN98AsMsuu6R4JL0JR5SEAiGskIk/ZOFrFkf+RdUYRExbzSWJlSB2THx6oo9/0LYImBYhq/V8J5ZlI8JJ2UMyPtVC8xj4R64pZlOxnzGTMzh17iSuO2UpAdtg4QvbNR0iJcGAHXesEM7UZexINCROTR9n69ZgLQXuHBUkrWiBsjEKgMcff1zZhz6G8mC1wbfffgtAbW0txxxzDIMHDyYrK4tp06YlzWcSS01NTdxfIEmNvb6CLSXeUfV4R9UDjgcokrahCcnIjCom5pRRmFEZToUQL5SqK5oCxH+ZW+wIG7/teMMEhEJOAH2yFTnhlwl3K5G2zV3rn3M2J0lCt6nYmUJcu7yBmvKmMd99ySoaQzoeEeIf163irguWxx23e87apENYVbmFVZVbmPvjI9yx8pkuSYAnpcQfMtMmmZ5i2+hqG6NITyLTVHV1dZx//vlx+y6++GJ23HHHFI1M0V0ogdUGkV+XixYtAuCcc87hqKOO4tNPP+Woo47ivvvua/X4UaNGkZubG/1bsGBBt485ldRZfhACIUBoyQSAxKuHHAdQ+Aebodu4dCvqUIo90i1CPDy7mBtOX8Yj1zhiy5aSUNBEtuLBskIav80/hs3FZaxfUUL5hkosKbn/Kme5vpTJfy16Y6blKzcGMIM2Qb/NuhUN4YSnMePTTOywAHQEpSMEt/gbCZgmAdPEtCWr6zYStENJX7M9SCmZ9ebbnPrUs8x6820lsvoAXWljhg8f3u3jVXSO2GmqG2+8Mbo9KyuLhQsXKu9VH0RNEbaBy+VizJgxPPzwwxx++OHR7V9//TX7778/l112GUceeWTS4MT169eTk5MTfe7xeLp9zKmkIRRCILlwuw+xCzXu+vDIlo0SaILYws6xwgsgFLBbBLIL7MSpFZqHTAUk2YMrAKhc7+OJmcup2BQEXFh5w/hh1ah2nZeUMO+M5QRsAw9mi32PhFcyRhgzOQPvefsxKr8KAFsWEJ44pNEM4NZc6J1YMRQwLZaXOWkjlpeVEzAtvC71Ne7NdKWNqa+vVyKrFxAbWP33v/+9xzLQx+aBilBfX5/wcYR0L6CdzqTcgzVu3DiuuuqqVA8jKU888QTFxcVxhg+cgMTLLrsM0zR59tlnkx6fk5MT99fXBZYtLS7c7gMiKsrrajk9aFl2VEBZViSQ3NkQG1ju0pyAcXeCOn/Hjf0ef6O/5eubTR9pKcEiRCReXtghSoubjhl26tHYtp74RJppN9HQCBJsqbUwNvUNGuuWxxuttcsbIBTrrXIizO5Y8QwnvHcDM964CVMlIu0R+puNUfQupk+f3mOvFckHFfsXWVUHMGTIkBb7mwsyRftJucAqLi6mrKws1cPoFJEVIV2RIbovIKWkQbsDnxHCZ4QQ4RqCsftLi8sp3VABUhJsNHno9CVc96ulUWF13a+WOs+ljMnQHo9LmAzw1tEYbIxu84RTBXk8Jjo2VsARQQJwbU3260tg2VrCqcJF5y2LbxnOwyUEPH37wObdtJt19aUA2C4/8396ssen+Ozw9Gp/QtkYhUKRCtTcQisEAgG+//57LMti7733brE/4k71+Xw9PbS0xJYB0CsJaxGEkJiyyUMUDAQJNAaRhuQ/c79n88pap3QN0FATP+3WIEM0z7vr9ThtH72mmHNu2Y4/vfAqf9htIguuzGPyOBfLi0JUIdE0GRU9z/31VTg+kscqpjMJeHxgmgQtHV8zR1YksWkkeegjs9cAkJvVUk1lGcGmPkWz1wmTZ2TTIAOUxAQhf1m2moAVxGvEezWllARMC4+hJ3XN2xK0DnrtbSk58cmnAHjxrNPRlNs/5Sgbo0gVM564EMPr5Ce0Ao791T0GQghMf4hXz34gxSPs/SiB1Qp1dXXstddeZGdnU1FRgcsVn2vgo48+Amg1t0l/QwiiTiuBRCbI/xQK2pSurI3b5vJohAIxbePcVjIqogCWrw5RFTSpsvwEQg3sEt4+ebyLT4I20iORhiMefhwkGOI2EFq8gDvzwf15/js3ngxBlWzNkesE7Ndtdab7/MGW3h8jRqcIAS/eOwiA2TUSDRsbwYlDjuDJTa8QjFn1GLQsAqaNN+ZbGAliX15WzuTBg1hw5GFxIktKSUlVDf6QicfQ4/N0tUFVg5+i8i3RxwWZ6qadapSNUaQKw+vC8Dquf5evb4eupIqUTxGmMwMGDODQQw+lpqaG66+/Pm7fO++8w9/+9jdGjhzJr371q9QMMM3xuUx22WVdu+prtXCmiKZ4LB2i4grpPNbDx5TUPxx32D0XLuPJ61ZFp94aso1o4HtEiiy4Mo8zB5bx0iEv89zBr/Hw47vGpHSIGwJvPlLAC/cOQgiw0BIG6B85sIEbryjAQiMnxsN1yKCfOLBgBbvlrOXm9z+I8141Ed9hoiD2uP2WhT9cmidgWlzz0lvtnmasjUkRUtvH04X0FpSNUSj6Lmnhwfr0008599xzO3ycEIJHH320G0bUxH333cd+++3H/Pnz+fjjj9lrr734+eefefXVV8nIyODZZ5/tl+77iGiKrZ1lS5vqshqICVHyuUM02vHB6DLBk+YiQUq47ldLAbjhX9vRnANy63lAC5CT17II7roVDehmAJdHQyIxvQIaXWQ+r+FxN4k1Ea54uF1eNYZbwwzGC8GcLEHW0CyqN9Tg8nmor5XcNyu7xeuVrvWz/XgDX4aLYIyYzHE1Ajp5RiO6sAk2uMFtIkJepMu5JvcW/ZvZ258V76WKJCltJY1EhP9uXIc/ZOJzu9ps259RNkahUPQ0aSGwVq9eTVFRUYeP6wnjN3HiRL7++mvmzZvH66+/zqeffsqAAQM4/fTTmTNnDhMnTuzW109HbNvmor1mAXDv/xagaRpSSr4uvZ4GTZITno4L2AaC5Ik9Y3niuiJOv3Zc9HlsTFZDbcvVdrmGjUs3sQwBCRxkC3/zEwDDzzo0Go9le+IFSzQdhISgZRCwwGfEr3qsC3iirb1uGDdSByQbyyyGD44P3Hr6tlw2liVeGSilxFU5FilsKjNKcbnrMYRNSWMZQTuER3dH24UGFGO7G9CCGUgp42KymuO3LQKWhQ8lsFpD2RiFQtHTpIXA2mmnnTjhhBNSPYykjBgxgoceeijVw0gbarfWIVwWdkijrqqenILscJ3BtcgMm6DUcQsLkOyWU4y/lemozEGZ2FuDbC72YwYSTyUm02fN82UBYU9Q0wGhhgDCa6IjcZ1UDwub2roMHSHAH7QRonmpZph/RX6zvpsez759K48vbLaaEMKiK/GARfhcgkaQYH02OdlVbKipiROgATuE7XaWRdvuBgJ2iNmL32bNlq1MHjyIv0zbP/HFULSKsjEKhaKnSQuBtfPOOzN37txUD0PRDmzb5vm3f8tOi6ooLc/DipkSk0jQYG1gAKM9WwBJthEgaCbPo1Lwq5OoeORvABiiyfvjczXlkHps7lqmzs1rceycAz+mKGhDU7YG5l+RxxULtjZt0CV75K4hz2igSrj4tFkfbt3AT4i//jmLq26rjebM8rjDYimsfQIhyYt35bZ6bZpj6DagOwJRwoxf/AMJPLRmfzINZ2PQbAp0l1Iy9+13ISbe9C9vvEVpjXP9lpeVxwXJdwQpJTe990Gnju0LKBujUCh6mrQQWIreg99fizGwghAGQwZV4SfeO+U2TDBhXaCA0e5KAELN5/BiPEFGzK6/XVMcfezyNMV21VTFl5dZs8HEcAcYPbCWX+TXUdZ0GIUjDTxuCIYcZWRoIc7I2wTAf+rjEz+MyMzG43JR29jIuJE6L96Vx8rVQWbdXtXivB+53kngaAwYiF1Z3mJ/IkxboNvOyXpjph7PnvglGXodmwNuPirdhaAdQkovAdOieOtWGNrUx+baOkQXrEUJmBaba5vi1Tx6kgSrCoWiVVQ2dEV7UQJLsW3E2AwpnRxUzVMHOEWZIzFVEvegJlHm3dLUQc3WJiHlcicWFaddUQECnl40kCw9FM1XFTckIXjxXmf6bvY3Te4td7O2m7W7GZRVgKhoyqQ8eZwLr7ulIRyQF05cKjTWlJgt9sfRlJg+OlloS0lQd0RWRjgz/UB3Lbqwmbv0YUb4BnHZxFMJDShu0V1szispJWbAxJY2mtAwPJ38Citjr1B0ikg29GTEZkaPUFdXR2ZmZncOS5GGKIGl6BSJoows6RQ7fuT0TwC48fnJaJpg6bo/sWK14MSpr6APCvLQdcVOH1IgzcQfwVt+twKEk1zU4yLpasNExKZKyMhOLoZcRgbgZUV1AePZHN2+4Mo8xo5I/tWYvagqmjk+Ft3QsMwYl5xoygBvhusXaiIaVx+lpKaG1Vsq+X7zLdiuRmJV68aqGvxBG6/LYEReDkF/EDucWyzyryr43L+pr69HD3skW/OkKC+KQtGzpFxgTZs2jSlTpqR6GIoOYoXjhGJv7jbQUON4ZyTwwKUr+OPdk6P7t1SVYNoWm4r9gAuGDsaXFV/kVMR4fqLJRZPohwy97VxON+z9XfRx86wHQjhp1+d+uR/Gs//j8ZudFAyx4qpFei4hkFJS0zI7BFlDs9GFTdX6lvmuPKU2PiMY5zgywwlOA2aIAwf/wAB3DdWhTN4p/UX0lZ2cVxr+UAghQgnF1I2vvMuiU47u0M3zxlfe5d4zju0XN9y+bmOSFXdu7klRXpSuZ4crrkJzuZ3VvuHao8LlQgiBHQry0+1/TfEIFakk5QLr/fffT/UQFB0kNvF5bdDJ5ySlpHLTVlwZTTfsyk1BQgE7aQKBKZcfCj81PY9mQZdw2pUVTclFm2GHlVKi6UGAYPP60mHMpHmlNMq2JF7BuK4um+rVm5kyzvEQrG8YSCDc/4kXObFY86/IY9I4N2X+0WSJMqClwNJdFhIZtyLSpVkE/UHcXjcD3M4xua56Dh3ybVRkCQEIi+N3/YTRBTWsCyzHSTQm0MKlHtdWVhEwLbyu5F9niYwTd5+XlfSb/FnKxvR+Ohr31FPeOs3lRndHC6F2++ulgubXtivjzdL1fe0qUi6w1q1bR1ZWFgUFBR067uWXX+b7779nzpw53TQyRXvYELydifYdBANBQv4gTyxoyjXUvIiybdtILSaFgq3j9ocQwklfcO8c5zMgEXHTfBGWrw4RCII0jFYLLN98RV70cY63MW5foi+nrbvJGTOIEy8t4+WYlYIbyyz+vPlAXC9toGZLOTmjBjLilMOA98Pn57SbtaiKnWbdyF27nI2/dAaJ1vlZCUraCJxyQs09dLmuenRhY0md3LHleHx+Rg4uRaLTaK/G0PMxLQNvo0WDFqSsvLzVaUIpJbPffJvYi9af8mf1Bxuzd8Yh6EJHSokd/gRq6NjYfNbwbopHt+10NO5Jeeu6jkQxZa3t68i17+vva8pL5RQWFnL55Zcn3Ddv3jxefvnlhPteeOEFbrjhhm4cWf9DSoll+9uO6QmnHTDcJhsC33PXz/9ESkkwZLO52PFo2VIQlAYurUluNAb9PBKOvwrYBpqQ3H7SO7x47yC8HhGXuDMQU/PvtCsqOPXycmYtqko+Hogm+YztR4sRdAh4+vam3FXucNyKEBrajAsYcN4f4rr94/w6XJqbkw5bQM5pf8Z1+EUIkfgrE8JACJ0rPj82foejoqgqr054nACCgVDCfQCGN2afsMK5upxM75G8XX5/iKA/idsOZwXhmi1bAYk7yfj7Mv3BxuhCRxcGhubCrXlxa14MzYUu1GpRhSJVpNyDFclUnYjrr7+eM888k+OPP75nB9UPkVLybfn1VAd/JtcziV8MnJvUFSsBhEQTzpTXmvqNBGwTLa9JTNm2hq5baEAoT6JXCAKBAJvW+EFAzqgcfJqOFn6N3AQeq9ixBWL0gz8Iy4tCDB3ro2JjAIlgRVGQG+6rjhNQEJlGdPr2aPGfMyEEHkPD6zLwh0wMwxv/ujYMysriqt8fQ/XHXlZuraQwQ2NZq1eyScAckFvP+zWZTsmeJOmrThr3Fc+v3iP63KU7wfAuTSNhyisJrpGNuL02do0Bm9r/a25NxVYm+PJY1VjldNVPguOVjelb7HPy1eiGE/dkW84PEE13YVshljx3a4pH13c5/4VzcHld0ZXMAIbHQAhByB/ioZMe26b+73/tADw+xwsb9DshG26vRtBv88ejP9rm8aeClAssRXpgywDVwZ8BqA6sxJYBdOFt0U5KScCrk+ELomkSKW1KamoI2UEiP5YlUOv3kJ/Z4NzcXM7SOcuyorNU+87eh+VFOTDW2bDgyvwWr9Uas26v4qodhnHb79eDbiCsUMKVfU0jIm4qbm1dNqNcznz+iLwcbCShusQJUTVN8NeDjyJgmVRvreQVqaGJxDFbIamzpsSkcKRBqLSRvQP1uHwab4caiORvkFISCti4vY4Y8+ohkBoits9qCHktpC2RIj6Z64mTv2Sgt47NDbk8u3k/6vP1NsVSoinKuW+/x13HTu9VMQ0KhW640V2RL3tT3JMVUp/j7sTldeHyOSEF7oykxrbTeHw6Xp9zE/HFrH0SonPJldOB/jdfoNgmAqaN1Jum3oSQBEyTUIy7xclc7hi7R64pRiIJDpY8suWVaBuB5KZdl0RFT35uBz6K4b4tWyCl49FqjU1FjWwqauTwgqalfzd+vRciUqhagCYEtnCzfLXzi3j56hD+YNOqRiEEXsOF1+fBtNwEzCYDYyOwMcjxeBBozA5PZZpBGwSEGm1u/ON/meqrw7ZtHr+uiIW/+YnHri1CSskxY75FmO64UCzfymFIadNUaLFp75DMWgzDZmTOVoZMrMRySQLtzPCuIfBqjhEr3uoExysU/RkpJfX19S3+IrS2Lx1INP4I6T72vo7yYCmAyDSKHfZmdOyXYMiysKWNjPk0ufNzIVTPpmI/oYCNxxXvZTl/WBHZtgCTJu3QiR+gyVYSghO7df6tEzlQbwQBMsaLk8jhIxHMCue4cqYk3Wha/KCEELhcOrbUAEfZ+S0XGoJcj5frdtmfPzTvXICGJFBcy1+vLOaZRQOADE64qAJhhXB7dRrNAF69KWeXhc2pY/8HSJ4rbppCtGw7mlsLCa7MEEKzsWUAKWW7vFGjPTmsbNzaZjuForcSER0RWluZVl9f3+FA7nSitUDxdB97d9LRFYrdIT6VwFIgpeSuCx9h0K834slwM2TMoA4db0t4sPhlxugRrxYMP30G1U/EF6+N6A6PG4a6/dQHfGxt8JHRvMN28vic1XHPA+HYrMnjXSwvCuEPSAIWbNxixQW+Ly8KYUoPHiOx1yw23qu5XDGEG0PzELT8NFiOF0sTGv869hQ0IZJqRJ/wUwthceUQu1LS6wnFHau7m3J8efSmQPeNdbUQ450XwK/2/Iyf6r6ixCxk98HzEwbiq1lARUdEB4DP56OxsbHd7dNpCX1DQ0NScdGfRUd/ojMZ97saJbAUBP1B1vy4jkG/hkBDsNV4Htu2yczy49IsbAQhWwckFaEq3pu7GiHgtfvzced8wIxngFBibxEAEm58e39u3n8t4Hh5Isy/InlMVka+G1kbpHJjwCkhE9P/rNtjPVAAgtm3b+XxhU7w+/nXVVJWaTP2z+27GWjNxIoQglzXEOqsRgI4NQ7dmhuP3ixerZlXrtZsKXquvziXsma5saKHi6YTM5rFexmas3jAlqALi2F5VcAg6kLr+KpsNrsPXhA9N1tGVhuK8LD6R2C7oiUdFR2lpaUdat/bltAn4hcXXh1NHGqb4QB6oylx6LcPdH8QfUc9L7H2euq9l6C5DexguHKE2wlCtwIhPr3o7m4ctSIRSmApOoQ/0IAertAcEURSSkL+EGVrG8nNFhhuHakJXrgjn5VrgpQLJ7VArJ6RUiClICNJLb1Yj1Nzjr5mVxbP/DhmS7xQCiSJyaooCUTTP2gJwg/1ZoIrkfzyer3ssssu/O/LL4gkvMrSB7Up1t7Z7GVfmoymBApHGFRI51qImKlOCZSNrkTibJ8+6ntnu3Ri1yIj12KmCiNirC60LrpAwZaSE598KtqrRLJcq0x6/gpFX+SXZ1+NZrhaCCYrFOTLJ+IFk+aKCaB3pyZxaEc9L6WlpdHHuseF7nGDt28mPe0sX7+/DxnhFYqN4RWKPq+GEIKGRovdDlrSLa+rBFY/R0o7HEzdbDtOTixNeNr29EiI5CEIBCFzSBbBeo0QTvHkGs3CcAuEsSV6SEPAMWK7DOnYdCTgzHfJSCLT1j0yPq9NTZ3TxrJk9HF7ZjIKRmVjNFuaKITgb3/7G0vXreCQI/cBQNdbCrw1JSaFMSV39JjQti3VNvk5jsA5ILeeT/y5SCQhv43h1pys65qJZUNkHYph2FFXoEszHQ8WAsIiS9oSoqs4ZTNx5dQ0bInyZvVXpo0+2UlEGv7eakJ3RIc0+XDdcy3aH7LLH9CEgWU7nhFdC3tG7BDvfvdwj469o+gR0ZQiwaRIPRk+nYwMx0D2pJM1LQTW22+/zcEHH9yhfUuXLu3uYfV5pLT5sORMR2CJkXH7vi2/gbrQunBOrDnYMgjSFXVdO6kGJNIlGZJTiwx6otvr/J7YMCGizhnR5FqKSCOfb9uX+0amDBPx6DXFSAkn/qk8PL7k/TSfGp0xZ0+WlbVUYkIIcnzeaA6vMWNG4/U6U4R62CM3e1FVXE6uoN3Uz3nXVLJoZj6FIwxyDRtNSv52bREbVjjXduFVedyz70dII8SHdTnE+dJcAYSUBAMSl0fEBfk7Qe7w342/Y5eCv0W325LoakFD1zHDKw43VtVEz9kO/6ulSQxNV6NsTDyRpKQtSJx9BF1zYeguXHTN8vx0CEDuDey48Ao0t5N7SgbDtQ7dLmTI5MeZt6d4dD1PRxcvpJq0EFilpaVxbs727kuXgMreSsiujT52ZcZnE68LrQOcnFhflc2mLrSW74vr+WD9aE7Y1ebBK1ezqdjPiO0yGXfFdtEbdKL3RDoOJ0wz3noLS3TJe9hyyrCJmq3OecVqJwsNS7acgtS0+GmzxmAWdoJ24AgRTzgT/AMP3xs9D4/mfKX8Acny1SEmj3OxfHUIc3xT7UIpwwLsDkeA2UGL9WFx5XHD5EIDbJsBRogMw0QKsJFYpo3u1nh4djHrVjQwZnIGvvP3QAKba+oI2jZew2BEfg4huwZbQrNFkMiyOkyfjhsvAdMpl+ORRtTb9eJZp/dJkaVsTPfTkZp1vX3lXk+hucNTfhA37Wf1089lb1u8kHKB9dhj25b9VdE6TlZcp6Bw0ptFGzNFdaG1mKZFRs5WhBjBA39eHS2Js355A2ODVtQTMj9cB1DQtKLuqRuL+N2CcfiD8b+YBS3jnjo6NujYCrlG2x0O+U6w0q7Z8xUluzBpWAEeveXXJC8vL3qE89jBFVM8OTblw+/vGom0m14kcr02r25keiHkz87j8gVV0fco39PojFJITAmPhz1cQ8Z6KVvrrOxau7yBSSELl9ekLuhExAWCFrK6hjc//y9rKirJ8ggGZYfHF1nF2WghPc5YpJSU1zXd/C56eTH3HX9MnxIWysb0DEowKaBjQruvV5NIucA6++yzUz2EPouUkkW/e4DVP6xl/M5juOJvFya4cUpK15YDyQygpLS4nIA/CINBWMGouIrwi+y1fLtlKB43FI40wgnLNXS3hh2y2LzWz5xfLWW/RZPijvMKA5e78x/B1nJgJSIirmLx6AZTBgxiWWU5w7KyWBm3V3DLtCMSio0MI5s5L50cfdw0Jjc2IroAIBJw/+AlS9ETaRYBti0pHGFwx6y86DZNa1oUEArY0enD0mJ/C0EptPiVgn7TpKi8khN2+5ihuVup8w9lTcWeCa/J3LffY11VVfT5xpoaAqaF15Vy09BlKBuT3kw7+qqEpW+EEFhmkA9f+2uKR6joCB0R2sk8x32FvmNFFS0I+oOs/sFJgVD0/VqC/iAeX3ygp+PhSl5sWEpJoDEY9bwcPHEpX8fs14QkSw8wdcAnfBnZKBwPlm9IDvUbmhJaTjZW899ov86/PiPeq3XOzEoev20Q0kounhpCnvDLbPuvHyEcERWwTL5dtZQPW+xPdpzGb8ffFX0c21/AduHT2kgv36JDZ1Vh1I0W868uJB6PIBBoeb4HDVzZYhtAqVnNQbnOtS/IKselW9i2jd+0AIGZG8IbcFG8tarFNGIi+nqMlqLrOHTaZei6K1w83rEtuhYWTFaIdz68M669brgxjPA0mEsFoiv6DmkhsCzL4v777+eFF16gtLSU0aNHc8YZZ3DWWWelemg9ipSSgGnhMfSem6LpgEaRGshmbhiPG5ASPaZelI5g/runcu0xjwCROBbp1NyLPnewpIulRSbbjzec5KBBSe6wDKo21JEIv+3hy9UTgLej2wKhbfsYR8rguNzx8VaiDeWRKKFnltvV+jVNsK9snT/JfslUXy3ZXos9bh/A8jUmf/lrVdxUZqbhR0a/xk0Hz9g1vjjqr375AbkZdWyqyOb5Jbthd+CNj12R2JkYrZR8rpuhbEzPoeuuqGByoQRTf2XOKyfi9hrhND7O/cHl1QkFLOYd+2KKR9czpFxgBYNBDj/8cD7++OPofOyKFSt45513WLx4Mc8913LJcF9ESsmsN99meVk5kwcPYsGRh23Tzahl+gWJJf1I2RSLJWVketC5NTdkGUSfNA+OpilYHRzPzqKZ+RSONHDnNvBRdVM+dsPSENIIp1Fw4rKuWNDkyYrEaYV74sq/1uFzy2jB5vqQO/pCa0rMFnmtmk/bf7dhdJKLkHgzwKic3BaxVULzYDmL17HQKMwdlDD+qjW83gQrszqBtGFzsRNrFVlrNbnQwOOGUAKHo3RbCCGda24bZHrip3HzMuqRtmT06EpGGpUUf9/+G1+NPxD3OM/Xsgh40vPo4s91Z1A2RpFqOroAoC/g9hq4fY799GQ02cW+FN/ZFinPNvjggw/y0UcfMXz4cO6++25ee+01Fi5cSF5eHi+88AL//Oc/Uz3EHiFgWiwvc8TO8rLybSrCa9sWH2w4nU8rzgnnSJDscMFP/K/yfL6tuMGZKgqZBPyB6PSg5Yr1KrXt3YiIK4ACw6L5WjvLclFU6ZSFKRxp4PU4OZu8HhE9bmNtAWZ4lV6kYHMgCCu35ACOuLoyRpgBuLSWq/o684Wdvde0Fse5PToB26DRdhOwDf6y9wEd7luIxCsjdZFk/XsSSoubSpQgmv4EgAS3S+Bxh6dJBYDN5mofYBNMVvhZa0ovL4z49/iBE45t99j8IbPdwanNP9fV/kCPB7YqG6PoLuxgECvJnx1s+mU4ZMgQsrKyon+xsUit7VP0blLuwfr3v/+Nz+fjk08+YfRoxxNx1FFHceSRR7Lrrrvy9NNPc+aZZ6Z4lJ3Htnv2ZmLbFv9ecgSBxiBurwtXxjCsoE726Fogm+rACq79vzdYWlrF9oO8THYBAnY+70fM8I2vbF0FwwsHE+fGinkYDWZvts/rjri4BHf/4Xj+8GAJ1+z5MwBP3z6QwaMaGH9lXvSw+5cczYxdYyoRhi/VTV/uQP1jXyTNyN6cjET5fJIR9qr59JbHRD174VNqnrahy4n5aGwsi6+XuLHMYviQBKkkBCy4Kp9JhS40IXHn1rEkkM0/5q5m2VKLnPEDuOqGEeHpy9jPnsTwOUkiRdOmKH/8x8sUNVYxflBBq0Oe9eb/sammttPeqN8+90KPe7L6uo1RpI6f7lAB+IrkpFxgLVu2jAMOOCBq+CLsvPPO7L777nz33XcpGlnXcPajz/HS5eehtSeSuAuob6x0gtLB8U41n+qTsKK8HHCxsnILYwt1bF1Aph294YYCoXDSyqaDZbLhh485IK+ePRY2JdYU0VSiTdgSxg43oiLMq1uMHTkiQadaUnHV5j25PWkdAE+CEj1Zrm1Pouj1eskZ4iNYHmi7cQyx9RLBqan4xC0DWrSThotJhU3i0C5rQHoz2LCyHiG81K6uJBQcitsjMLzhuURTx+0NYOg2NnDooKU8bDX9SrbspiguK8EPAtuWFJVvidsW8bJ2ZrXhthzbGfq6jVH0Hra/9qqmxKHhuX7hCtc6DIZYepMSbH2JlAus2tpa8vMTF/YtLCzkhx9+6OERdS0bVm6iuqGR/KyMtht3A7vP/orPr0+0RN+ZOrT0sBQKCyopZZxIkRICg0AaEkO3wbDiuwiTq9tEJrUq6rMYiodgyMWaDWa8tyuMZsOwvOFkeN2c+bdDCdU18uoV7wNgSyMuFkoAGjY2GiDwZmVQG9OXZbff0ySEYMjEPHw+X4t9uW4fGsIpVYMg29X+WKMIHsPFcdftwb8vebvFvubpG2ITkbbXW9dcMZtBm7/fWBS31ecLYLhtbCFw3s7we4cTE5DvamTE2C1s/dmHrgUJWXqLfmOpDTSJRcuW6D30Y6Gr6Os2RpE6drj8KjR34h9mdjDYwsOluV1N7T1qAUBsuECgMXFoQ+z23pY3K+UCKxQKYRiJh+F2uwkGO7jcPQ2pq67vsMDym2aHV11JafNj1c3OkxgHUvMs7dN3fhqAN74/qdnxkmDAwicdb5YUNpvXlSHzIkv0E3+4K0oCFAxtEiP3fDyNx3YzKMjM5IZ7qnj8loEtjpmz+Hj+dcWRrKveHF6t13SeAgjYRvQUnMLEjgCc88wJvPxtBuUtTt75JyJiYsVMLKfcfgBZA30Jr6umaXh0Y5umCF2ah4F64vqKAcuFT2/6PMcmIs3NbhrPxjKL6jrJ8qIQk8fHi1SPO2bc4YFu2RRACIlHM7HD9Rk1zcaSGm7DAsNscSXOmPQZ1ihnwcOmqgJ+WHZMTLfxrSMZ6ztD875SQX+wMYrUoLnd6EkEVrpjtpKep7V9XUlsuaQ/Hv1RKy1btu8NpFxgKRLz2+deoLAgn0XHHNWuZfFSSr4qm43fKsXvc6b9NEviTfKrAMBl+OOOf+avS9nwcz2jJ2Tyx796sKRJKMNESkEoYGPoNlbACnu6RDQPVShgx63sqw96EAiO32MKHz4iE07buXSLYMjCo2eGA8Ob9mkxsVAALk2LbhNCI2Ql/9gGbIOIWGuZi0qQNSCxuIptsy3+GSEEw6wjgacS7mtOxHMVKUINcNG8Ldi2xqzbHQEmhIjWNXzsppxou4iIjKTBAEcECwFoEkOaBP02Lo8jFIMBp9SObUs0TaB7QlgBF0Nzt7BUM6P9zn7zbW4/5qimty3J9WpLPNlSctpTaoVeT2BJs83tve3Xv6J7efXsBzrUPtSK6GptX39GCaxuZltM2potW7ly8RvcfsxRCW/Otm3TGGrA58pAEqQutA4bSV3AS0ZGwImtincOOWMygkhhYResx9ZBmJJQ0GbDz87y4HWr6mls9Ds5TFw2T85Zzcaf61l4VR67FxoMC6dZsBGc8Zcqnr4lN/oap11Rwa5nevG4dKRlOYWWLypn/pV57D8m3ouX7fNgCZvFX0/FZ24C3gMgX3ezvsXZOi9w/Mh5/PvLfzTbFX+CkWve3It11sMHtZnbqkuIyY8VGYMVHkmj5QFknCcLiF6nyOMIgSB43K1/ihZcmcsVC7ZGPW8y3Mlj1zjldVyFQwEIrdkcvRozn/1F7DDREHjDKzTXbNlCYyjI6U8/D8CDxydeYRgRYgnrT0rJRS8vbnXciUiHnFm9kc8a3muzTW/79Z8My0zscYzdrsRk1/PQSV1fciojo+mecP9rB+DxtfSWBxqtqHcrtn1vQAmsbqZmkB7Ngt0Z1mzZmjAg2LZt/v7VH9CM9WAP4ze/uD+67+U39uH0k96PPt/1qm+ajkMiw0lBbVcQzRPCCrb8UIcCJghJKGBT8nM93kgRYpwVhJFTivxbtrYhGsv161/ugBCCEMFom1l/reLKSaPYL5zV6cx9dkHTBJomGDdoAA1bthBJyLCbZxDfJ7keIvq/JtxJso00z6jeGMzG7QtRH8hDFy3d+l6vl1FTBrJ+WQWjpgzE6+14DBbEB9AHLFdU1GhCtBbqFCes4tI6SFoo9VUbBZptMmGURuEIJz9Wo9/pfuGZPzHznztEy+tsWVWFBHJi3mazLkBWnot6nGNsJKM9OQSRzPjFP1my+VVgBiCoTRIgFvlsusNTiLELOQKmxcaamuTnmuCnR7KcWVJK/KHEHhpF/2PJc7e22aazYtIKJZ8ubm1fb2TGExdiJMnbZ/pDHfZwdYbYH1Een443gcBK1r43kBYC6+WXX2bcuHEttldUVAAk3AfOxS4qKurWsXUFdUliPGJ/rbcHKSW2DKAJD42hBkdcAWib+O/G30U/fKalUVaey+BB1UjZ8p4euZGbIYuFp38LFlxx/65xbWwJQb+Frcmmaadm4T8A/qBk+eoQ24WDtRuCGt5wcLhlxt9E/zaniP2uywxfk9jEc/Hjaz7ewWNzqVhbGxU9zSfxdvMO5OekRzexfMPO+KrysWVi74hL8zDzjt9RUr2KEbkTcGmdC0KN7VuEL5wAho7MZfOG6g73V+V3RQPil602ue0FwYFX7M7LV3zAy3c3eQ9jE8TWV5st8sXWWl48uolbmNFpQyEkSIGOwAQ84Wnjkuoa3IafoOlrdSrQtiWnPOJMhz57wentXi2byPuVKBecx9CZ9ebb/LB2bbv6TUZftzF7ZxyMLlqac0uaUe9Wb/v1nwq+e6Bt8dZXMLwuDG/748fOf+EcXEkEWcgf6hYPV28nLQRWXV0ddXWJS6MAFBcXJ9zeG9SslInd1VJKrn3pbVZuLme7oYOYfcyBbfQj+bb8eqqDP5PrmcSknKuc7TSTFBJMU/LS63vgctn8Zs/38Q0IoGnOzTA23UKgtikGq6E23kPw9+uLKC32M6SwDS+OdIK1DZdGbUBHYpCZ2XKFHkDV5kZOvMj5ZXnT3ckDyHVX/L6zbjoQr9uNy6PjMVwMzcxiVcz+5oJLRP8ff92F0LBl8o+8EIKjhl+OOSyIIdyd/nzl5jSlV4h9f86YcwCL/vAqEqKrJFslMnwpogHxhy88iENn+cj269AsvC5naAY1mxtAwD1/WhHXkVvYaJpk8X3Oaro/XlfEH26biEto6ELHMCzMoMH+2/0fAKZtE8nYcOtH/432NNqVzW0nH8XpT/8bgJqYFYYVdfUMys5s87rZ0vF++U0Tn6v1HGaxomtb6Ms2BkAXRkKBFUtvOZe22Ofkq9GNlsLAMoNR75YSk12Py+vC5euaShX9hZQLrPfff7/tRr2cxrqWOZECpsXKzeFf65vKmPmGs6zfliQsvmvLANVBx09THViJJf2EAmbLfFVShgWdIBTSefem7TjisWUAlKzchCvDBXlOW0ML36Ej6cEjCChd68w3lRb7W8Y4J3BoxM4iJVt9J5BR75mn+aqumJPOaLZ8Od8zHMtTxWBvIS7Nw++324sPY9I4SLvJAyhigs6aC6+R2TmUWTBlQPISOEIIXGLblk8Pz8mlwXa3GENWntd5ryQELReJYrGSrX4E5xoLKdB1jcGD88CKLzJ9wo278vKcrwmU1oa3xSSBF5KH5zYFyNeVhwj6bYQRBNPHIb/8N1X1eWR6aqJVBFaX1+IxGrFjSi5trq4laMVOXzaN9U///A/bDR3EjScclvTalFTV4A85K2RnvfE2d8xo8mI195T5TXObVjBG6A82pj3E/tCz7CRB8Xb6B8Xrhhu9jZx1nRWTu1x4ddK+rVCwX3m4FNtOygXWtGnTUj2ElBBrvCRQvHUrm6pr8YdMvC6DEXk5yQ8GAv5gtA9n6tBGFy1vRpv3Hwosc+JYgha2sDEGONN+hw7/kR81GzTQM2LFVtO4Ik+9ntYNli5skPGvP2TI4KTtM5onmYwxiJoeL9AOGHw+w/IHRr1K+VkZcWkc3DF9DRyaRW25nyGFeWxeHV9m59LdpzJp2AQ8utGtv+ZzPBnRVY85Qxyv0uCJeQzIHspN/zkVf2OIG095Hlu29GT5bRdCEie8Yoeq6xoul8GgrFF4GA7hjGDzr8hj1+HrOeHBEZx24jIkgpfvc1YeTv9jFR4XcZni64Ia15y2ioUvTEKaXiwjQFb+Jmxb4JgFwa/3+IBcXz11/qGsqdiTyKch9rN743sfREW+bUtWbE5e5smWTpkdt9AImBb/XV2MP2TiCydenP1mU+6wkqoafvf355k4pGWKj47SX21Mc2Ljkj5c3/bqzr4SFN8RdFfb4q0nsZPEP8ZuT1chrEgDgdUfuOS9t/lkp3HRO6UA5rwcn4hShm8+4PybzJMVbs1t//dfxo1q+7UtrxMk/M8FKygpqmPU+Cx+99exgIjrX7gSfEnDCmvBlXlMHtfSNbx6g0VjUJChRZo7HUbqBWZ4fTTYbgQtUyZEXjvH40xBxp5qbmYWQyblUbayisGT8sjLzI6Lh8oOu/+jaRxipkZOnrMXQwYPwnDrPHTFW2xa7Y96ugZl5uE1ut/FrQmBR3PyaR1z7V4YHh3Do3Po0Ev4T8n16DEevlih2ET8G681yxEGcNjwS/joWB14EHAWHthSMMwdwOtx6hRGyM0WNEZmg8MvdO+sbH47t4HaihAZBQ2Op81JOtZ0nM9ZVVqQVY5LtzAtHV0LcfOr7zK2IJ/iLVtZV1WNGygtLifQGMTrc8d5VSMZ4J0SPBIzZOGptjBzw+dvWfhwETAt1mxxBHFEiGHAz6UV2Jl9Y2pLoegoP866o802/UkId1ZMNrSSrqi1fduKElg9QK0Zotof4Jx/vwjAU6edTHFF+GZiJ4hCB0BiS0cENZ86kRJGjvx3u18/FLTZWFyL0GHd6nqCfguvp3mtunicIsICr0e2EFd2eMA/jNqb0x4wefrC+CmYjAxHDAmRPKeUHo690YTgPyeeyaP/9yoLoi/uZca1UzEDJobHaDHl6EyzNfVsuOOnytxe52N97oKDmXfyvwkh0RBkuDu3KrBzOHnCPIaB5tXxGgbu8LSky6MzeGIeZT9XAeHs+UmSuAKcfdt+PP2Xd6PPXQwly5XJITN2iYvDqvN7yc1sZP4VeeRlN12Tfy3MY/UGi/xR2WhCUL2pnuGD4f5rMrn6j8sZsV0Wv7l+QlKvXsiyOO+AxQgEHk1na+1gztn9Ic59/iXA+QxHyjP5G4ME/UE8Pk+07M54b270sS2doPrmK2vjP+PO43WBGkZ7WvfkKtpPbFzStFEno2sJguJtM+rdiq12YFqJ8xwl2m5ayVfbJdqXLO1CW/taI246NMnqv76yKjDuXAOJ36dk23sbnRWTux20pItH0j6UwOohYoOBL1/8OlJKStdWEGgM4vG5yJsyEDNgYksbTWhsrKqJpme4YvEb3Dr9ICIuJYnELSrj1byT/Ig1mypbvnjMzVsISd63G5lcaOAZkcEdwhFshtZM6AnwWwY+Ycb0H8+gnEy2lMVPww2akMugcFmSzFa8RbHSSxMCj9cTjVtyeZypwGQrVgJW/C8OI2YVpi6zARjsHUu91RD1pjnn3jOekLy8vMgrMmH4wGgiVZfmZrC3kNLG1Rxz3V74a4I8ddH7Yc+mc4FzB2dSUxpvRGJzdw3ZOoMrDz4XTdMSxsaZltZUmijmPRs3UkfTBFuCXrQCA0q3MH6kju7SKFlRh7BDGB4D02oZPyelxNZk9B3Lzy7Dwvk8l1RVM87tI8Fyi6bxRwcqkbYkFLCQMeWNQiGLma//X/R5SaWT3sFvW9it9KvoGLGff10zMNookt7Y2Bh9/N73D7f7dd798K4OjevD17q+/l7sjfjLJ7ovbsoORVLRJKgt2AUCbscFl6N5Wk5Z2oFgQu/Wpxfdvc2vqeg6lMDqIW5894Po4001dei2xO8POELGH8Sy7GgwsS3taByLP2TyxdoNHP7AY1x8aA3D83KwrZarzzZW1zI8LxsriVdKwxFQHo+M5rPK0WwWzcznigVbcWtOxnZwRJjHDQG/E9uTCN2l4fLqGDHepRMW7UNWfiZ6JC+SENGg7rYYXtD0OsPz81jbitd2cG5O1AM0dFI++VnZTccGp3Pa2GMwhJvahir+zD1tv3gXo2kac146Ofw4XrUeOewyGq1abq+9CHKInkfk2p9/6+GU1Gzhpcta1jIEMKQe9egJ6Y2v9SgEdY0tA/QLRmchdA3L0njgphMYfMr/ODFrCwKJX7rxh691slJIEpCak4wr6Ddxuw3+9OTLrPNXcfxuHzMoq4bNo3L5zzt7O0WNkrjxZWRZomzq2LJs9rn+HmpyJZNHDGZkTg4lS8sJ5krcbmWeFOnNT7d3b3FmzeNGTyCwYukrq0PbQ2dXh379/j5kJMmx1dBodZuHS1mwHsAMmvyveH1c8Pr6YC01g5zLr4UkiarXRUrRBEwTzRWkMWSSbAo6aFrRlBC2GcTlFgQDEcGUOMGllJLCkYZTB09KglIHIbhvVhaFIw1WrbcpHJl4RWBdQQG20OP6NTzx+aUykxRLdqYY4389Z2c2tc3K8BBXzbkZuq5x7Jy9MQMWhkdniJUX3Tc0Pz8ar+X1+rokcWhniAirHNcgakLlDPYWRoP0XZqHkdm5FFVt4Zjr9sIMWDx+niOocvJ8bAnFX5vYa+qOSWLq0g0uXbCVRbPyKRxhUN6YxQBPXTT32YVzK3nghgFRH1BdoxchBZouMDw6ZsDijj9n8rt5fgKNFl6PUwLJkgE03E1CKEYkSun4lPbZ6S0O8lUgcaYIR2RVoukmlmXg9weRLp2SqqZEo8WVW6P9RaYDQ6ZFaWVTm5Bpcdmee3P6Z0WRhqzz1zIiM7fT74Oi88TezA7e+Q8YekuPl2mFWni3Dpl2KYaeWBSYVrCFh2va0VclTLsAzhRhZzxcsWP/5dmJVwZaoWAL71asR8o2HY+UZnSdR8pupe5la/taI/Zcp957Cbqn5ftkBUI97t0KNiZeqRq7vaMxVZ0Vkxk+nYyMbV+R3FGUwOpmfJuDhMK5pCLB6yAJ2E0uGtslkLaME09mIMRFhy8GBKW1BQzN3QrorKnYEpNF3cm0DuDySDZsqebv1y9lfdH36IYkd8QAmHg2ZVtzw+3jw6krNjgetMcXDqRo/RaEgLtn5TBmhI4tnWmlRIru9KurOXThDlyyyxy+Wz0rZtBOzUCP4Yiygvx8PJqBZcd73AK2q0UKhSzDE92S486mPpBHpqcqadZ1ZwrR+fgOHjAkun3YwCFxbc5dcDChgIXLk5rSK0cOvwxDuJPm1Yqcx3lPHgk4wmygNzOujWvz/oAjwFxGfIJWKeGK+VvxuGHeHXcw0HsLdliab6o2HDErHS9icW0uIb+L2vJMghMKGKD5GSfryMsWDF6+mZ2muFm1webiOZUMH5/FGXMKnReSXjLdTpR8g/QSFCbZmc7n0fkcS0KZGsF8Da0Cbv74v6ytqyVkNXdDxn+WbMsmEGyKDVm/pZo/v/AmALoFuCAouy8AVdE6sZ9XQ3clFFiJMHQ3RhLBlAjd6Fj79hA3HdqBlYHftjMNQ2lpKZmZTd/T+vp6hgwZknBfWVlZNJHt0psWtav/jhB3rh5Xmx6vnmLecS+22aavB+grgdXN1I/XMSwbQzMxbR2QbIz5Ze8gqaivAmx0Cyxd4BOB6D5HXMVj2Tb/XLCCjauc5IkjJ+VgBm3K1jWguQwkgqqNlQybEOStJbsSsD8GwEsoPvN3mPEjdXKzBIUjW6r8NSUmgaBkcqGTUbyqVmL7sslyZbJy867AqwC4dR2X3iRknKmyU6jaWsud57zQlLcKyM2NFxH5+XmI8BK2wQMKMIqP4fvNm9muYGibK/9choHfdkSs0Sy/VmzQe0/h1TLjHgsR7wU0hJuBnrEUsSW6LTbOqnlQf2xesIwk+bsCQXCJnOi1n/7HKqSEpUUm+46C8pCHuUsO4qTRQ/ni2e15YUIj5w9diSYkLy/KQMcm5LcZPRA8HigpquO23/4AwPAJWWxe5bgUr3xiZzSvhmWb6KZzzSMeMtvlLMooqtoanSYGZxWkTzNotEJooXiRddfn/yMYMGNisiQCQWYd1OhmON1FW2WlFYqeJTMzM05EtbYvWTtF30cJrG5GCsHJe3/GiIJqNlcX8M3aGQRME2n5iayJ//XenzKioIpK08d7mydjVruxvnd+hUiAsAfIDDWtxArYks1ratENiZSCklW1hPOLkpnnoX5rEASseOXvTPjtuUjA56ZpOX4brNlgUThSZ02JyZULtiIlTlxWEM585BC+qtqeXF8GU4aP4qfwMb6c+Pgfr5aJpgmErrVIRxBbrw8cUXHuE0dEH98y7UgClpkwZ5VbN/AaBn7TxGsYDCzIj+7LzUv9dJIQGmcV3hl93HK/YPrwy/lo1essq9zCqByDAQWvATB92BzWhDZi8e+oIM3IaJpAzstLnhfK63Zz/atnseTJ2VHH459vqeeUkbtiZHt47uTfMm7YIGZe+qgTVxVuIxJ8IGIvecnPdejh57ed/QMjt8vkN/MmYOohpC2c9Ge6I4OkEKzfWh3XgQRGe7IJhSzWbC1z+jcl0hCUVFdhaCbgIhg0KanYQqjRKfOjZ+lYumTFxnIsf1PVAUVLrLCnT0qJHV5a6mRYa6NagALomEcKOhYLFNt2+2uvRHMn9jDZwWC3eLhSxZz/nIjb11JiBBvNqHcr9toEGps+w0G/87l1e7Xo496IEljdjKFZDMvbCmgMzd2CrpmcsNvHDM6upKI2h+eX7M2wPEfADM6qdhJ25obIPLABly+ELTVMv+MNsCwLMyQx3Fo0OzeA0CRS2ohw7M3Rc/fgucs/AcB2gT+zmr9elc2UcUbczXT1BsuZBgzfC2+9smlJ/FWLapA2iHAcgo0gEJROYkzdxf5DJ+DTXVy73wHkPXFUeBwibkovIjQ++elH4KW423hWsxpY2R5v1IuT7XEynifzXLk0D7sN/AWl/tUM8Y7DpXvixFn02gtn1V6Zf000BqqnSCSsYnFE5NEELJOqwFbuW/5adN/Q/IFxgnTUqMHRFZYDB+Yl71PAHeefxDGf3kr5yipA4HYbfLR0KiHLw4I9B6FpGhdfeyz3r34rYd1AgbOi1BQy7EsCCxHVS5qUlKyoI+S3gQAhU8cwHK+lkJLAQJ2IzDYDJpZts2ZNCeOmDMfQzfDnT+DZahMYpHHYzm+RtWslJXUFPP/5PiCdVbICia9Opy6slzU1U9gqnzW823YjRVI64pHqKLE/EDW3O6nA6mu4fUZCgRVL7LX549EfdfeQehwlsLoZEY1hcm4shmYyNHcrtg0Ds2s4ferHMY0Bt0SzTbCdQ7Tw8nhbSv41bxkla+qRlSMZ/MutTcfEHC+QeL1NcS3ZGX6Cz/+DKXeH47BiJNbMRVVkeCSP3+J4RUYM1tEMwapiE38AXD4DPSywAraT3VsCQ1y5nL/j0dEvR0QYLd1wAONzR8cJIyG0aP6nCAWjs1v8AtSEYEJ+QfRxq9dUCI4cfhmmdGoGljaUx02xxbUb1tQu3VbbRERkNk3B99keL7p0M3hCPmU/V4UzwOdG3+bsNnJ5Dc7KZvp1vyQUMCnIymR4Rh6/Gv1HfHo2RjhDfl6WD2kKqiw3AwpzwLY56w9ruesa5/rPvyKPKxdu5aV7nM/FYRfW8vYDzkrNEy6qwOOCf8xZRenaRueHwegMzrpxe3S/xHI7qw1BYEkb3bYJeTR2mvAfhhZUscPYHF5+Zy8kglP3+ZgsXy0EYVjeVnTNJOjXEEj+cJoTi3Xnu9MRmk5mQ3q9d70dS5pIS2KHPV+acESyJRMHJisUio6jBFY3E4k5sW1H2ozIzWnSRDrk5Du5ZgyXiUuzOHHUN3j1IPUBj5O2wRbo3hB1pVCyph7Tr1Nbv4WtqwXZbgNPOE+VJmQ0GMbl1Rg0NoPKtXVxmbljWbbaJBS0aT7xkj8yk6suXg/ACbftySsXfxjdFxFmQoBPzwIcQRDhb0f8mjxPfgsh42pW0Hf6nN2TeKfafxONrRkYO4bYx83bpSsZelZUXGboWdiueo66Zg8nJYLXYPCA/Gh8Wn5+Xqt96ZrGlPyh2FKGharA0LWouALI9GWRUzWcZ/2S87f7GSlh/SaLNSVOyofCkQaP3jwg+naMGaZFH790ryO61pSYXLGgARuoWF/Pk9cuRU49nIuPeA2B4LEPTyB39BZcuUF0YTF8ZCkAI8aVk3PgFirW5jEorwZpxy93kEi8niC2C9DAnR8gWJW4eLjCYePGjeTkON7n1qa2Yldsfbiu7VI5ir6N6Xd+PEspsQLOfUT3OCEZkX2xhGLam+H2Rrh9KEH79pCRkdGiCHt7P8O9ASWwuhkhJFIHYTkCJVQdwD1So1HYRMIjpCYJBUMcmFNHvh6eC8mSLPmolisWVDFiUgbrVzRQUZONUWWhj5Zouh3u32lu2wIhnOzvQdvgxPm78eLsr6lcW0dszPRpV1cTCEr8AfAlEV+nPXwQJhqNtTH1rmJug/vn/iU6BRYrDvI8eQm9RAMG5kbzPQ2emEduVgaeZiuSmgeGd4SOeL/SEWcq9a7oYyEEbsPAneV8PXN9vugUaK6vPbEfotXroGkalx18K2eeuZB7/ywI1TYg5Wpm317F07c7Aio/t+nDccMfM5oi2cPzloUjDG6flcfl86uQQNm6BgYeUgfC+VExypBU5QWxXU7dS02T4cgggccXwpBNKURljBXK/74O/95G9IeB1AFpEQr2jUzU3UGyKazm2+vr63tkPJYVc+O2nce65qQ6sBJkfo9ka5dSYof3a3q4fSczucf1HwomTLuQikzudrDp2rRITNrDn/FXz36gQ+0fOumxLh+DEKLV6ddUfYa7CiWwupkRUyowXCEa/BqZORYlg79jR3+QoLRBQm6+yWPXFVGxtoFDHhgEwx1vi2VKCkcY3Dcnnz/N24oAcgoaYYAzXecSFl4PvHinEwB99B+3OgHHwGv/+wXHHvATJyzYjUBNiH9f+ml0PP6AxB9M7CvSXRoIgdAEkf8isT+x5GQ1eYSai4NE+Aw3R167G2bQxnBrjMho6eVqKzC8bXqfsIqltXMWAiYOGADEC0i38ESLRVtouIUnLu4sQiLB6stws+eO46it+gEZXintD8j4xKWALQUjhmrYpnRi/CKBfmGRlZstqK51BNQ5B30AmgcJlG6qwD3O4jdjPmffzBoKdJOKoM6SxhxA8tuDP8Slm5iNBkG/hcujIWwTzg6SN7wazRXCNHUu2PNdXC6Tf/60C9y/LVdY0dxb0FYgd2e9Be98eGeH2nc0z1UyQWYnKefTnZncO8rSm7o3MakivVACq5089thj3HPPPaxcuZKMjAwOP/xwbr75ZsaMGdPqcQYm/5y7kg0rGhg9JZNjZ3v4143L2Pizo8SHjPFSutbPHbPzCDbaSBsqNgYww/mthg/Wm0RWOPDYq5vcMysnnFLBMYJPzM/jvLk1+AMwaGwVa+sKGJtbiScHBk904q9cXp1BE3JZv7SagtFZNG7YEjfW3OG+OJ1iBZsMbs7QDGo2NzB4Ui6+Zl6UtgSR16UjpAvDkE6iyyRaqHPCatu8X72HlhfNcHnjguENl7dZ3JnjJUy2kvGquaex4KPXCTSEf8lLmL2oiqfviF+pmDs8k9rNjaxcHeS6O5zPTMTT9cTCASxfY3L9PdUIYePzNYIXcg7YyuxJXzHZ57SvKAlg+m329dazz3bv81ljFiFb8vh1Kyhb18ioyRmM+MNOzo8HLcgtp30LEq58cnc03SYro++vIuysjWkvrXkLEnnB0tVbsOS59BFM3U2cxyv8WLhdyFDnY+U6smIyIrJjfxC31j52XzrRELNCsTG8KtHndWYLVLHnFDNz5kxuueUWtt9+e/70pz+xbt06nnnmGd566y0+//xzCgsLkx57z+SP+OlXbq5YUM+9F3sZMmAjf1/XgBDgdkHVJj+52YLCEc5bUb7Bj9UsV1BEZF20oAZ/EB6em8Pwwc7KQjtcYqUgV/DinU5R30dsi9qqLErcJnZA5+hrdmRA3nqEgMNnjccfAKTN8+e/BzHLuOtMDz5hY0g3LjmCMnMnwAk2Pv7WvTGDTsLOHE/HMqILIXDH5EXKc4/o0hV92+79Si+ap6HwJCjKCzB4kBN4Lps9b2/cmWEYzJ72T34uWc2/rD3x6Cb+gM3yohCTx7lYviaEJTX2KxQEh+TzceNg/P4PQOC0Ge8CAZPHGTxzxwB8+TUc9+t1BIKSPe7ciZHuBjYVNca9ZshvM1QPcEx2gCVL6qnYUA8INq6s49phnzE1N4jbhh9n5/KXRdUQrGPawAB7jfsfb3X2gvYCtsXGpAvpdOOOeOuklDQ0NFBfXx9N9rl69epo3xkZGQghOl2CpSNjiaW95/rjzNs79FpWIOR49oLh2Fy3EyMVW+y5K1dMbusKy55CFXtOU7799ltuueUW9ttvP959913c4SW2p5xyCieccAKXXnopr7zyStLjhZSMG6Hzr9ucKR4pJc/cPiBhWwn8vMZk3EidZWtMphQ2vT3Dh+g8f0cBLq9O7lAfQhOYpmTrOueLq7s0rJDNpAlu/lrwJbpus9H08fdN24HQiOiObLcXwyXBLwnYBprdJNIsW2NpbQG/GXcHhblDKKrZwKAnDwYgy+PFdFl4dRfeDmZdbi4Ypg+/rMtX9PUFYRWheRqKLFdBdF+sh27IgIK42LYhAwoSddcquq4zYuhAhCYIWM7n7S+LqvG5JYEgnHj3wfxQ4sGUAoSFjYYmbWYtqiIrW+eJhQOidS4b19dHP9uDxv4XDZmw4lHEQztuqIbPI2jww8Kr8piWV4umg20504/P3T6ATSWl+IM6mYP67tL2bbUxPYFlh8IxVeFgaC1847Z75sbdUZESEU6JhFlEaAHU1dV1u0DoaJzRttDXiz13ZJo7HbxpSmC1wX333QfA3Llzo4YP4Pjjj+fAAw9k8eLFlJSUMGLEiITHV2wMkOEVZPqceoBla+OnOkJSxyUsELCx1ObyBVVouk5ZvZchPicVw6JZ+YwZ4SJ/VCa64azo2mK6eaZ0NE9d+j6BEPzvjVFO3ipNUBMABAx3NTJ7u6vw158NgGnrTMjagTq7lJzcoQye+DllP1extMhk+/EG6xqymF28D/9XmImmaWQanmj6gxG+/HDx5o7Xg2qRt0rruZqAvZHmaSiEEAk9dLquc+x1UzEDJobHiMue3hEM3eDm/5zOXZe/RumqKvy2Cy1cF03U6Zhe5zUNt05e4QBKi6oByByUE/3saM2SlQppgxAsX2My955qrr8ol8njDJavNpn/UA3/uKUAC41b/zKA6+6oZHKhQWlxI4ZHi06PAwwb5JxTaXHfnSLcVhvTE7z73cNtN+pGekqkxHq8IsQ+jgi37iRdV9a1dm0SXZeg34weFwpXlHd5dUKBllNykb5j+0zUf0emuTt6HWtqahg+fHhrl6DDKIHVBh9//DGGYXDAAQe02HfIIYfwwQcf8P7773PmmWcmPP6USyu5+7o8xoxwoSFZU+J86ApHGqzZYHLZLTW8dHcuSLj4ziDljVmMmpzBaDNIQ4mGhs2l86vxZbp4+9/Z0VCc57aOwlvv4tSHDsbWJA9UOjt0Kfn0892594iXAbAbLyMTm3rTw6r6XPYd/ScGZmUgpc3ym5ZRW9/Ilee+h9cNA66fisAg2+VML+V6fbik81jXIkvIOk4iwaBonebTfIk8dG7dwOdy4RcCr2G0yDfWETRN47I7j6au1s89l71BTWl4RxD81R58uQFctuDES/ak2htCahLDpfOtsPnrvC+pWbsFl0tj4ZW5jB1h8Nkn9cxcVOVMRwOzFlXhdUv8QYEtBUUbLMaO1Bg5RPDEwgHRwPnTLqugtt7G54H75hREVzNuKu+92ZzbYlttjCI5zacKI9siNqj51GBDQwNZWVlx22K9INvi8eoKEQEthYSUskOLFzo7HdratUl0XeYd23Ytwtb6bq3/9grhjlxHq0Xt1G1HCaxWsCyLlStXMnbs2LhflhHGjx8PwPLly5P2ISVccFM9o6bkULemgoaARlAa5HmDBIJw7O0HMv2PzvzwuX89BLJzwNOIRzN4dtYHbFlfx6CJORx53W5sDG1kmMvPV1VDWLxmF/ZZnMWwM75AG+yhzmpEIrGEhntUHuv9WYzy1pGpVREI/8K5cc1evDnBjUvzELIDjMjMx8rI47f/OASJ5NMyH7kMj2ZDj01/kOMaTE2ovNMZ0XtDPqrehhCCkdk5SEmnPIsRItOOQmhkZ/v41c1T+ft57wKCrGw39Y/uQZ3LxjBsMn7zOXl+N0EpkbYkNAgOmrkbL57/HqYfLp1fjWYYlNV5wc4ix+PHE87gHgg6qWotW+e8OzN48+k8hrobqdnUQMhvsazIpLrWSd7g99ucc81WXr53ICC5ZEHz+p19g66xMTJ6c2mPd6G9N6fOxjF1xNPRXtHR2faxN9lEN/BtpSPn2lkREdtnov4j5xjbPhGd/RykIx0Vwh31vnUVSmC1Qk1NDVJKCgoSx7bk5eUBUFVVlbSP0+YdjJ3lwnBr2DkmUoAVsHn6905ZgAFkctajBwGgVQkKh/jQtEwEcMpVUzFDFoXbDcMfDPFClUZd0MtH68YzbehO3PLQIbywYS0Amfp4llWvYqs/C4HBNSun8uTObxOwTRCw3p+FEBl44/JPOekrXZobkAzQBmLJpg+ac+N1nh8/8hpMGVIeqDTCSckwbptLAQmhcfrYW3mq+GoQgklDh3HTK6ejIfj1iIVkHJZB0G9y9XkPhtsL3AjQwbNFQ6KTVziQ0lVVDJqYy6F//gUCgS4EmJAZ0AkETYSu8fcr3wPgkpt24YVqEwOJrUtMtw07aWSN/Iot6+ooGJ3F0fN+yRnXf8nWdXVkD89m04pEEV29m66wMaWlpWy33XYttie7cbf35hS5cXc0jqkjno6Oio6Otu8oXenx2taxdMW1aU10dLR9a9cmcl0ibdqKf4p41pofB7Taf2fpzvepNZTAaoXIG+7xJPa8RLb7WylEW9NYSn7eKECgVenk+CQ6mVxw52EA+HweZK3AsmwMQ0fXNQrcIzE0F0yI9CLwedy88vFuhFwwRs/n7v1PCKc7cL74J42+jpAdxLQ1Zn72GutKN7GqMZcJvmrW+7O4cukBHDls52gG9aZ8SavxGQaNpokl3UzJG4InPNXUfHWe8kClF11ZCsgQnqb8WUJg6DqDvYVk+pwbrcfnYsz4EVRvziFrjLMysG6dD/eQGgSC0/68L7kFmXi8LmQ4HksTTi41BGzesJVgwHQ+90Lg87kxt0Lt1gwsUyN3aD1ZGR7OnL0/DXUBTEMgqgTHX7k3waCNZkluff+lLrlu6URX2JhE4krRObrT49XdIqK7ac+1aWtaLkLz6bnmx7V17TsqhFOFElit4PU6wdjBYOKMv4GAE2DS2odh5kFPk5mVSe3WINn5bjJ8PlxuN1Y4NkX3gI5BXa0fb5aOpmlRT4QpnUaR56efa1ETCFCQkRGdxosVQG7di1uHu/Y7nobgUZTX12HKBiblZvDZuCwy3J6m+oExN2cdg4BlInbS8OhGMxd731md1xfpqqnX5vmzmnsrhRBcMe9EAv4ZaG4nHsr+pYaUzmPdE5mijBZUCv/rPJdjwA4KhMuO9hdoDGKZTg08zW3jcTvmKBQwMW2LUNAiK9tLQ0MQywpwK31PYHWFjVm3bh2G4Vw7KSWWZeHxeJLeuDt6c+rK9snaRsbe1e27m46ca2dFBHTs2nTX+9oRuvt96qgQ7sj71JUogdUKubm5aJqW1D0f2Z6bm5u0j4K8geTk5DCo+QxAs/c0N6/lh8Ql4lfbuV0aA5vV9UuWRDLT4yWzjXxVsTdnn9a5FWiKvkPs5yGRaBNC4PXFTEN2tERgs/burMSfT3ez74Y3N4Oamr4Zg9UVNiY3Nzdai7A9dPTm1J3tOyo6Otq+u+lOj9e2XJvueF87Qn96n1pDuSdawe12M378eNatW0co1LIMQ1FREQDbb799Tw9NoVD0AZSNUSj6LkpgtcG0adMIBoN88sknLfa98847CCHYd999W+yLuPYj//Z2AoEA119/fZ85H+ib5wR997z6Kp21McnoyPvf0c9Kb26fTmPp7vbpNJbubt/dY9kmpKJVlixZIgE5depU2dDQEN3+0ksvSUAed9xxCY9bv369BOT69et7aKTdS3V1tQRkdXV1qofSZfTFc5Kyb55XXzynCJ21McmuSUeuVUeva29un05j6e726TSW7m7fVX13h41RHqw2mDp1Kn/605/49NNP2WWXXbj66qs5/fTT+dWvfsWQIUO4/fb214qKZGzuqefd0ecjjzzSrf33xDn09Dl1R5/tec3u7j/V59RX6Eobo1Ao0oguk2p9GNu25T333CN33HFH6fF45PDhw+UZZ5whi4qKkh6TyIM1ZcqUuDbd/bwr+4yo++22267XnkPz5z11Tt15DomeJ/ol1hfPqS/RGRujPFjqXHvDWLq7fTp7sNQqwnYghOCiiy7ioosuavcxMpw9vba2NroCyrKsuNVQ3f28K/vsC+eQqnPqideIfd783750TpHvVV9jW2xM8/cl0fufjI607e3t02ks3d0+ncbS3e27qu/usDFC9lWLlWJWr14dLXOhUCi6hvXr1zNy5MhUDyMt2LBhA6NGjUr1MBSKPkVX2hglsLoJ27bZuHEj2dnZqrSMQrGNSCmpra1l+PCmWpn9HWVjFIquoztsjBJYCoVCoVAoFF2M+imoUCgUCoVC0cUogaVQKBQKhULRxSiBpVAoFAqFQtHFKIGlUCgUCoVC0cUogaVQKBQKhULRxSiBpVAoFAqFQtHFKIGlUCgUCoVC0cUogaVQKBQKhULRxSiBpVAoFAqFQtHFKIGlUCgUCoVC0cUogaVQKBQKhULRxSiBpVAoFAqFQtHFKIGlUCgUCoVC0cUogaVQKBQKhULRxSiBpVAoFAqFQtHFKIGlUCgUCoVC0cUYqR5AX8W2bTZu3Eh2djZCiFQPR6Ho1Ugpqa2tZfjw4Wia+l2oUCh6AbKXcMopp8gRI0Yk3FdWViYvuugiOXbsWOn1euV2220nb7nlFhkKhRK2/+ijj+Shhx4qCwoKZHZ2tjz44IPlBx98kLBtMBiUixYtkttvv730+Xxy+PDh8sILL5QVFRWtjnf9+vUSUH/qT/114d/69es7ZjgUCoUiRQgppSTNmT9/Ptdccw0jRoxgw4YNcfu2bt3Kvvvuy/LlyznxxBOZMGEC//d//8c333zDSSedxPPPPx/XfvHixZxwwgnk5+dz6qmnYlkWTz31FDU1Nbz44oscd9xx0bZSSs444wyefvpp9t57bw488EB+/PFHFi9ezIQJE/jf//5HQUFBwjFXV1eTl5fH+vXrycnJ6fqLolD0I2pqahg1ahRVVVXk5uamejgKhULRNikWeK3S2Ngozz///Oiv10QerEsvvVQC8v77749uM01TnnjiiRKQL7zwQlx/Q4cOlQMGDJDr1q2Lbl+1apUsKCiQQ4cOlfX19dHtL730kgTkKaecIm3bjm6/4447JCAvvvjipGOvrq6WgKyuru70+SsUCgf1fVIoFL2NtA1mePXVV5kyZQoPPfQQ06dPT9gmGAzyyCOPMGrUKM4///zodl3XWbRoEQAPPvhgdPsLL7zA5s2bueCCCxg1alR0+/jx47nkkkvYvHkzL7/8cnT7fffdB8BNN90UF0d1ySWXMG7cOB5//HH8fn+XnK9CoVAoFIq+Q9oKrEcffZTa2lruv/9+Fi9enLDN119/TUNDAwcddFCLwNexY8cyfvx4PvroIyzLAuDjjz8G4JBDDmnRV2Tbe++9B4BlWXz66aeMHj2aCRMmxLXVNI2DDjqI2tpavvzyy207UYVCoVAoFH2OtBVYl112GWvWrOHCCy9Mugpv2bJlgOOBSsT48eMJBAKsWbOmzfaRbcuXLwdg3bp11NfXt9p3bHuFQqFQKBSKCGmbpuHAAw9ss01VVRVA0kDzvLy8uHatte9I20Ttk1FTUxP33OPx4PF4Wj1GoVAoFApF7yZtPVjtoa6uDiCpYIlsj8RJtda+I20TtU/GqFGjyM3Njf4tWLCg1fYKhUKhUCh6P2nrwWoPXq8XcILdExEIBADIyspq0d7lcrW7bXv6TkbzNA3Ke6VQtI+gHaIiUE1FoIq1FSWpHo5CoVB0iF4tsCLTd8mm6SLbI3lzYttnZma2u217+k5GTk6OyoOlUDTDtC3qzAaqQ/XUhOqpNRuoDtVREaiiIlBNeaCKmlB9tH2wTq3WVSgUvYteLbCmTJkCQFFRUcL9RUVFZGZmMnr06Gj7//73vxQVFTFixIgWbQG23357AAoLC/F6va32Hdu+K1m0aBHffPMN//znP9tsGwgE2GmnnXjyySfZe++9u3wsCsW2YEub8kAVGxsrKGksp6SxnI2NFVQGqtt1vE93M9CTR6bh7uaRKhQKRdfSqwXWbrvtRnZ2Nh988AG2bcelaiguLqaoqIhDDz0UXdcBmDZtGo888gjvvfceBxxwQFxf77zzDgD77bcf4KRi2G+//XjnnXdYs2YNhYWF0ba2bfPee++RmZnJrrvu2qXntHz5cm6++WZ++OGHdrX3eDwsXLiQ3/72t3z77bfRqU2FoqcwbYstwRq2BKupCFRTGayh3L+VsoDzZ9pWwuOEEGQbGeS6MslxZZJtZDDQk8dATy4DPXkM8uSRoXsRQlBTU8PFPXxeCoVCsS30ilI54BjjRKVyLrjgAh566CHuuOMOLrvsMsDJYXXyySfz4osv8tJLL3H88ccDTuB6YWEhtm3zxRdfMG7cOMDxRu255564XC6Ki4ujIuWZZ57htNNO48QTT+S5556LCrU777yTyy+/nEsvvZQ777wz4XhramrIzc2lurq6Q1OExx57LCNHjuT+++/vwNWBHXbYgfPOO4/LL7+8Q8cpFB1BSklpYAvLa9aysnY9mxorqAhW05oZcWsGw3wDGe4byAjfIEb4BjHEW0CW4UMT7VtnU1VdTX5eXoe/TwqFQpEqer3AqqioYI899qC4uJgZM2aw/fbb8/bbb/P1119z8skn88wzz8Tl0Xruuec47bTTyM3N5fTTT0dKydNPPx2tRXjsscfG9T9jxgwWL17MbrvtxmGHHcbSpUt59dVXmTx5Mp988knSNA6dEVg//vgjO++8Mx9//DH77rtvdHtRUREzZ87k3XffRUrJ1KlTue2229hhhx2ibebPn8/999/P6tWrcbvVdIqi6/BbAYrqSvixejU/Vq9ma7C2RRuXZjDAk8sAdw4D3LkM8uYx2JPPIE8+Az257RZSzbGl5KsNJTy25DMeOPXXSmApFIpeQ68XWACbNm3iuuuuY/HixVRXV1NYWMg555zDpZdemlBsvP3229x000189dVXuN1udt11V+bMmcO0adNatA0EAtx66608+eSTrFu3jmHDhnH00Uczd+5cBg8enHS8nRFYs2bN4sknn2TDhg1RUbhp0yZ23HFHhg0bxrXXXktOTg7z5s2juLiYH3/8kYEDBwKwatUqJk6cyFtvvcXhhx/ertdTKBLht4IU1W0Ie6nWsdFfQayVMDSd8VkjmJw9htEZQxnizSfXlZU0IXBHkVLyw+ZS3lq5ih9LS6lu9BNqbOD1C/+gBJZCoeg19BqB1dvojMDaa6+9GDZsWFw9xD//+c/cd999rF69mqFDhwKO6Np777259957mTFjRrRtQUEBv//977nlllu69FwUfZ+QbfLV1hV8Vvkjq+tKsJuZhQGeHKbkjGXH3PFMyh6FW3Ml6anz2FLy2br1vPjjUlZVVEa3Z3k87DN0MH86aJoSWAqFotfQq4Pc+xqrV69mn332idv28ccfM3Xq1Ki4Ahg2bBhr165tcfyYMWOiZYEUivZQGajm4/Jv+bTyR+rNplQIAzw5bJc9hu2yRzMxexQ5rsxWeuk8DcEQJTU1/Li5lDdW/ExZOMGv29A5dMJ49hkzmkmDBuKvr+dP3TIChUKh6B6UwEojqqurW+TnqqysjFvB2BqZmZlUV7dv+buif1PSWM5rG5fwQ/Wq6PRfvjub/Qbtwu752zHQk9dtr/1zRSVvrviZbzZuYktDQ9y+LI+H6dtN5Ogp25EbsyJWZcFSKBS9DSWw0oiBAwe2SGyal5dHeXl5i7bvvfceY8eOja6EBNi6dStjxozp7mEqejF+K8hLGz5kSeX3UWE1OWcM0wbtyg65hZ0ORm8PtYEAj37+FR+sjvey5vq8jMnL44DCsexfOAaPocySQqHo/ShLlkaMGTOG9evXx23bf//9eeihhygrK4sG1VdUVHDUUUdxyy23RFNTSCkpKSnhuOOO6+lhK3oJK2vX8a+1b1EZcAqQ75Y/ienD92God0C3vm59MMi/vvmOD1cXUx8MIoRgWuFYDp4wjnEFBWR51KpXhULR91ACK404/PDDuf/++5FSRldkXX755TzxxBMcccQRXHPNNXi9XubPn8+wYcM466yzosf+8MMPVFdXc+SRR6Zq+Io0pTbUwEslH/J55VLAmQo8a+xRTMwe1e2v/fn6DTz8vy+pqHfK3ozIzeHSfacyadDAbn9thUKhSCVKYKURJ510EvPmzeOLL75gzz33BGDUqFF88sknXH311Zxzzjm43W4OPPBA/vnPf8bl4HrjjTcYNmxYXP4sRf9GSslnlT/x0v+zd9/hUVRtA4d/sz3JpvdCCiT0GnoPVZoggoIIUgQRQUR97X6IKPjasfGiooAKFkCQokiN0lsInYSQhPReNtlsnZ3vj8hKpBiaFOe+rr0Iu2fPnJmd3X32nDPnyf6NKrsZQYAufi0YHNoVF+WNSzpeZbVxMDuHbWdSScjOASBAr+fRDm1pGRKM4hLLOUiSRGl+GenHMinNL6eitBJjWRVlheVkpcnJnmUy2e1FDrBuIc2bN2fQoEF8+umnzgALoGHDhqxZs+aSz5Mkic8//5xnn33Wudq87N8tz1TMd5mbSamoXjcu1MWPByL6EukWfN23ZbbZOVFQwLG8fI7m5XOmuMS5zINSoWBIk0aMaN7UObeqqsLEmcR0CrOKKcsvpzS/jNL8cgqzi6koqbzoNqyi5bq3WyaTyW4keR2sG+RqU+UcPXqULl26cPToUWeS6r/zww8/8Pzzz3P8+HFcXFyutsmyO0CV3cym/P1szT+AKDnQKFQMCOlEj4BYlML1C75NNhu/JqewLzOLpMIiRIejxuOhnh60CwujpZs3tsxyCjOLKMouoSirmPTjmdis9ovWq1AIhDUIIaCOH+7eevTebui99bh6a2jTM1ZeB0smk9025ADrBrnaAAvgzTffJDExkW+//fZvy1osFpo0acLixYudiapl/z4OycH2wsOsz91F1R/rWTX1rMt9dXriq/W8btuRJInf09L5cn8C5eY/F0/w0eoIsCrxKrPjWmDClltB9pk8zMaL9zwFRvgTUi8InyAvvAM98Qqs/jc0OgiN7sJJ79fyfpLJZLKboVYB1syZM6/rRmfPnn1d67sVyV8Isn9KgbmUbzM2cvqP4cAgF1+GhHSlqWfd65a+BqDYWMWCvfvZn5mF3WrHw6GkkVWH7qyBrN1nLtorpdaoCK0fTHBkIL6hPviH+RASHURIvaArapv8fpLJZLebWgVYCoUCQRC4ls6uc88XBAFRFK+6ntuF/IUgu9FEycHW/AOsz92F3SGiVqi4J7QbXf1bXNf1rKxmK6t3HWJhQiIVRhM2s42QFCMhZ00ozvtICKkXSFSzCAIj/PEK8CS4bgBBkQEoVdc+NCm/n2Qy2e2m1pPcmzVrxtChQ69pYz/++CPHjh27pjpkMhlYHTY+PbOaJEMGUL1Y6APhfa7LcKChuIITu5M5lXCGbalppOvsVHhV5x7UG+w0OFGJp00gtHEdQuoFERjpT6MO9QmNvrJeKZlMJruT1TrAat68Oa+88so1bSwlJUUOsGSya2Rz2PnszE8kGTLQKtXcF9aT9r5Nrim4Kcop4fC24yRuPcrpExkU+6nJqueKJUgJqFEqBdqrvHlwQEsin6lDQLjfdbti1eaoxGTPxyqWYHUYsDuqsDnKMdqysIhlVFhKKSq+MJuBTCaT3cpqFWCFh4fj7+9/zRvz8/Or9ZVxMpnsQjaHnS9S13LKcBaNQsVj0fdSTx92xfVIkkReWgGJ246RuO0YmUk5WLQKMmJcKenqjdpNg9ZVSx0vD+5t2ZTejWPwc7vyhM8OyY5VLMfqKMEilmARi7HYi7E4SjHZCzDb87E5jOe3DKtdxGyzU2mxYrHbkSQJU+XFrzqUyWSyW5V8FeENIs8ZkV1vVXYzn6X+REpFFiqFkin17qWBx5X9YJEkiYTNR/jliy3knMl33l/hqyazgz9KLxdc3XWE+XgRVzeKIY0boVNf+neYJDkwWFMw2s5icZRhFcv+6IkqwyKWYnMYuPwnjITd4cBmd6OiSkdumYShCmx2LZUmT0wWNwTc8FG5M2fEWPn9JJPJbhvXtNBoQUEBKSkpmM2Xz3Xfs2fPa9mMTPavV2at4JOUleSaitEpNUyud88Vp7qx2+wsm/Mje9YfBEClVlK/bT1MrYPYIZbipRCo6+PDY53aUc/H56JDjpIkYXMYMNoyKDIfoMi0H4tYdtntCoICrcILrdIXrcoXSXQnOdfG2SJIzRcoKFcjOtTO8hqVkobBAXSNCqRdVBjBnh5UVlYw54r2ViaTyW6uqwqwjEYjDz74IGvXrv3bsoIgYLfL3fsy2dUqs1bwXtJ3lFgNeKjdmBo9jFDXKxuyL8op4csXl5F+PBOFQqDfhF60uKc1XxxJJDEnF0EhEFcviikd2jlXXD/HIdkpt5yk0LSPQtNebI6aq62rFC54ahqiVfmiVXihUXqjUXqhUXijVXqjVrhTVFnF4cw8jmfnsy8tE6v9z7WuFIJAhK8X0YG+tKwTTMvwkMv2mslkMtnt4Ko+xV566SXWrFmDSqWicePGeHl5yVcPyWQ3gNFu5uOUlZRYDQTovJkaPeyKrhQ0GqqI/24nW7/dganSjKu7CxPmPIA90pMXtm2l0mJBrVQyvk0s/RvEON/HkiRRZc8mv2oHuVXbsIkVzjoFAbRKX7y1TfFzaYe3tikKQV1juyarjRM5BSRmnuZwZi65ZYYaj0f5+9CjYV2iA3yJ8PVCo5IDKplMdme5qk+1NWvW4O7uzt69e2nYsOH1bpNMJgPMopX/pfxInqkYL43+ioIrm9XGlm+2s/GreOdq6lHNwpkwZxSpdiP/3bwN0eEg2s+XJ7t0ItTTA0mSMFjPkFHxE0bbWUz2P6/c0yg98NXF4u/SES9twwsCKrPNzq6UsxzOzCWnzEBmSXmN9DkKQSAm0I9mYUE0CwuiUbC//KNMJpPd0a4qwCooKKBv375ycCWT3SA2h53PU38i3ZiLq0pX6+BKFEUObEhk3WebKM4pBaoXAO3/cC9a9WpGSnEJb23Zgehw0Dkygumd21Fi2cnhol1UWs/WGP5TCCq8tI0IceuNr641wl8WL3U4JPIMFWw7lcqm46cxWqw1Hg/w0NOiTjAt6gTTNDQQN+2FKXBkMpnsTnVVAVbTpk3Jysq63m2RyWRUD899nb7Buc7VY9H3Euzi97fPO7bzFCveW0tBRhEAXgGeDJnaj7b9WqJQKKiwWHj7tx3YRJE2YcGMaaPkcNELVNlznXUIgoIAl44EucWhV9VBrax5xZ7JauNoVh4Hz2aTcDaHsiqT87FAT3e61Y8kOsCXEC8PAj30ci+VTCb717qqAOuFF15g6NChLF68mHHjxl3nJslk/26/5O0hoTQJhSAwqe4QIt2CL1veXGVh9Ue/8PuK3QC4ebrS96E4ut3XAa2LFgCHJPH+9l0UGo3U87PQt8lmTpWmA6BWulNHPwhvbVPc1GEXDP8BFFZUsnz/MXampGO1/5nqSqlQUD/Qj7tbNqJ1RCgKhRxQyWQyGVxlgDVkyBDee+89Hn74YT777DNatmyJn9/Ff2ELgsCrr756TY2Uyf4t9hWf4OecXQCMCO9NQ4+IS5Y1VZr4bfkedvy4h5K8MgB6PtCFQY/2ReeqrVF2WeIREnMyaRJ6jO4xZ6myK1EpdITpBxCmH4hK4XJB/Va7yIH0LLYnp3M4MxfbHzlEAzz0tIkMo3VkKA2D/NFcQ65Bi2ih0l6JSTRSJVZhtBsxikYqbRVUiUYq7ZUY7ZUUlRVdcd2iKGKz2a66bTKZTPZXarW61lksrmqh0dOnT9OzZ0+ys7MvXfG/LLnzX8kLjcquVHJFBp+cXokoOegd2IZ7wrpfsqzJaOa9if8jOyUPAN9gbx58eRgN28XUKFdltbEk4RC7zu4jNnIHMf429Bot/i7tiPEaj0ZZc16XJEkk5xcRfyqN3WfO1phX1TA4gNEdW1I/0O9vh/7sDjsVdgMV9goqbAYMdgOVtgoq7AYq7ZVU2iuotFdic1gvW8855koLr7d/s9bvp8rKSrKysq4pQb1MJpP9lSAIhIWFodfr/7bsVfVgPf3002RnZxMWFsbdd9+Nv798RZBMdi1yTUV8fuYnRMlBrHd9Bod2vWRZh8PBly8sIzslD3cfPf0n9KTD3W0u6LXKr6hk5qbNuGgP0q3BQXxdNfi4BBLtOZ4A1w41yhZXVhGflMpvSWk1llTw1bvRvUEUbSJDqefv6xwClCSJSnslxdYiiiyFFFuLKLWWUGmvwGAzYBKrar3vGoUGF6UrripXXJVu6FV69Cp3XFVu6JV63FR6HFUOXufNWtUniiJZWVm4urrKn00ymey6kSSJwsJCsrKyiImJ+duerKsKsHbs2EGdOnU4duwY7u7uV9VQmUxWzWAz8r+UVZhEK3X1IYyJ7I/iL1fsnSNJEivfX8/x3UmoNSoee38cEY0vXNE9ITuHeTt+IyYonnDfDALc9IS5t6WB9+QavVYmq42fjyax8sAx5xCgVqWifd06dG9Yl6YhgQgClNpKOGI4RFZVJoWWfIosRVgdlsvul1JQ4aH2wF3ljrvaA3dV9d96lTt6tbszkNIo/v7qQoNo+Nsy59hsNiRJwt/fHxeXC4c+ZTKZ7Gr5+/uTnp6OzWa7MQGW3W6nbdu2cnAlk12jc8sxlFgN+Gu9eKTeENSKi78tbVYb372xmt3rDgAw9tURFwRXDknihyPH2Jb6C62jDuDrZiTEw4f63mMIdbvL2Ztjstr49VgyPyWepNJcHSjVD/Knd+N6tIkMptxRRLYpjVU5v5FZlYHRXnP1dgABAW+ND75aP3w1fvhofPBQe1YHUmoPdArdTe09knuuZDLZ9XYlnytXFWC1bduW48ePX81TZTLZHyRJ4vuMzaRV5uKi1PBo9FD0KteLljWUVPDZf74m9ehZFAqB+/4zhNjezWuUyS438MWBrWi0q2lXNxcPnY5g9zCa+T6Jp/bPNeuOZ+fz3sYdGEzVOUSDvNzp2coHnVcZqabN7E7LQ5IcNepWCkpCXEKp4xpBkC4YP60/3mofVJcIBmUymezf7qo+HV999VXi4uJ4/vnnef3111HJaS5ksiu2Lmcne4qPIwgC46MGEajzuWi53WsP8OO8dRgNJlz0Oh5+40Ead6hfs8zZDBYn/EzzOhtw0Zjxd/Ogke9gItyH1FjL6nBmLnPXx+NwOAjyU9G8EZi0KZywl0Ppn/W5qtwIdQkjxCWMcNcIQnShcjB1DdLT06lfvz6NGzdGEAQcDgceHh7873//o2nTpje7ebJbVHp6OnFxcaSnp9e4PzIykvj4eCIjI6+67sWLFxMfH8/ixYuvqY2yS7uqT8wjR47Qt29f3n77bb744gtiY2Px8fFBrb5w/RxBEFiyZMk1N1Qmu5McLDnFr3l7ARgZ3pvGnlEXLbfhy62s+d+vAARF+jP5nbEERvyZ6Nlss/PlgYMk5Gynbd149FqJOh6NaBv0PC6qwBp1lRir+HDzLiSVkbr1S9H7VlAgCGAHrUJHY8+mRLpGEeIShqfa844YYpMkCau5dlcqXi2NTlOrYxUSEkJiYqLz/wsWLGDSpEns3r37BrZOdjUkScIi2m/oNrRK1R3xHpNd2lUFWNOmTXMuw1BcXMymTZsuWVYOsGSymgrMpSw9uxGAvkHt6OzX/IIyoijy82eb+eXLrQD0G9+TgZN715hUmV5axtu/bccmnaB9vd/wcdUQ5RVLc7//oFLUHGqsNFuYs34TFs9T+AYUofd2RykoqKuPpplnCxq4N7oje6isZitPdpt5Q7fx/u+znQu6Xonu3bvzzDPPkJaWxpQpUygoKECr1fLuu+/SqVMnxo0bh5eXFwkJCWRkZPDII4/w4osvsnjxYtauXUtZWRkpKSk88cQTZGRksGXLFnx8fNiwYQMuLi689NJLbNmyhbKyMoKCgvjuu+8ICgoiICCABx98kO3bt2M2m1myZAmtW7e+AUfm9mUR7dz303c3dBvLh4xEp7qwU6K27HY7kyZN4tixYxQUFNCsWTOWLVtGQUFBjV6vWbNmOf/9+uuvee211/D09CQiIsK51MChQ4eYMWMGFRUVeHl5MX/+fDkV3nVwVZ+oixYtut7tkMn+FRySg6Vnf8XqsBHtHsbAkM4XlCnKKWHJ/33HmSNnAbj70b70f7hXjTK5FRXM3baCYK9EovxTCdS7UcejI419Hr9gJfbssjLe2f09ZX4ncVE7CPT0IMa9Pr0C++KvDbhxO3uNHA6JKrOVSpOF3PwrX2j0VuZwOPjqq6/o1KkTY8eOZd68ecTGxnLmzBn69OlDcnIyUD1EFB8fT35+PtHR0Tz22GMA7Nu3j+PHj1NSUkJUVBQbNmxg3rx5xMXFsXHjRpo0acKJEyfYtWsXCoWC8ePHs3TpUp5++mkKCwvp0qUL77//Pu+//z5z585l5cqVN/NwyC4jJyeHli1bXnBfTk4OKpWK3bt3I0kSvXv35pdffrlksJyTk8MzzzxDYmIi/v7+DBo0CL1ej81mY8KECaxevZqIiAh27tzJmDFj2L9//z+wd3e2qwqwxo4de73bIZP9K/xemMiZymy0SjVjIvqh/MtyDIe2HuXr2csxGy3oXLWMfH4o7fq3qlHGIUksSVhMm6gNuGogxMODILdONPR+DIXw51u61GhiUcJGjpp2IriaUAoCTfzqMrjO3dTV1/tH9vd8dtFBcZmR/NIKCksrMZqsWG12LDYRq81e/bfVTonBRHGZEUOVmXPrhFottV9X63wanYb3f599Hffi4tuojfO/KC0WC02aNOGzzz4jJiaGCRMmOMtZrVYyMzMB6NevHwqFguDgYPz8/CgvLwega9eueHh4OBdd7dWrOgCPjIyktLSU6Oho3nnnHT7//HOSkpLYsWNHjfk6AwcOBKBly5asWbPmmvb/TqRVqlg+ZOQN30Zt/HVoGapf5/DwcKZMmcInn3zCyZMnOXXqFJWVF17te86uXbvo1KkTQUFBAIwaNYotW7aQlJREcnIyQ4YMcZYtLCzEarWi0cgJ2q/FnTcmIJPdogotZazJ3g7APaHd8NXWXEV999oDLH19BQ6HRN1mEYx7fSR+IRdOfF996mv8vdahEASifToQ7XU3vrpWCOcFa+tO7ePHtHXgWoqgBb3KjcHhA+gZ1uWSa2xdC9HhoMpkxWi2UmW2YTJX/51fXEFmfhmZ+WXkFRsQHVe+srpOo8JD53ZV7RIE4aqG726Ei31RlpeXo9PpatyfnZ1NcHB1/kmdTue8/9y0DOCCL76/Xmi0f/9+HnjgAZ555hnuu+8+VCpVjVXtz9V7fp2yPwmCcE3Dd/+E1atX8+WXX/LUU08xYcIEiouLndlTzn9NbTYbarX6gvvPnTOiKFK3bl3nOShJEtnZ2XJwdR1cdYCVnZ3N0qVLSUlJwWw2X7KcPAdLJjt/aNBOjHudGvOu7DY7K95b50zW3GFgax78v2EXXcRuR8ZySq3LAAh07UP7oCdrBFYn8rNZdOIHihWp4Ao6lZpO/p0YXm8QOqXugvqulCRJFJRWkpxRSPLZAlIyiyguN2K21m5CsFqlIMDbnQAfPR5uOrRqFRq1Eo1ahVatRABsFWZUdgmlzYHDZKXKYCbrbM41t/1W5OnpSUxMDEuWLGHs2LHs2LGD4cOHk5GRcU31bt++nR49ejB58mSKi4tZv349995773VqtexWsHXrVkaMGMG4ceNIS0sjPj6e3r174+XlRXFxMfn5+Xh6erJhwwbuvvtuunTpwtSpU8nMzCQ0NJTvv/8eLy8vGjZsSGlpKfHx8cTFxbFs2TLeeecdDh06dLN38bZ3VQHW4cOH6dq1K0aj8W9//cgBlkwGO4qOkFKRhUah4sGIvs5epPIiAwuf+8Y532rgpN70n9gLhaJmL5MkSfyW8RGp5T8DEjg60K/un8GV1W7nw70/ctyyC0FZvSJ7tEtjHm0+Ap9LLP9QW+WVJlIyizh4MpOjZ3Ipr7z0DyqdRoWbiwYXrRoXnRpfTzfCA70JC/QiLMATHw83TEYzZ0/lUFpgoKywgrKiSopLKinJL6cgqwTpIr1cVvult3m7W7p0KVOmTOHdd99FqVSyYsWKa+49GDFiBEOHDiUmJgadTkebNm1ITU29Ti2W3QrmzJnDyJEj+frrr3Fzc6Nz586kpqbi6enJc889R/v27QkLC6N9+/YABAYG8vHHH9OnTx/0ej2NGzcGQKvVsnz5cmbMmIHJZMLNzY2lS5fezF27Y1xVsuc+ffqwZcsWunXrxj333IOXl9dlLzf9N87ZkpM9y84ptpQz58QSrA4b99XpSfeA6jlVpQXlvDfxfxTnlqJz0zL+tQdo1rXRBc+3OSrZkfkpaeWbcEhgt/bg4dinUf8xh+NowRkWnlhGhVAAgK/anwej76dlwJVfBeRwSOQWlZOaXczpzCKOpuRQXF5z/pNKKRAV4kv9cH9iwgMI8ffATafB1UWD8o/AUJIkqirN5KYVknUmn6LcMkoLDJQUGMhNK0R0iDhU4FCCQynV+Fvn7YJ7gBtqvRqVqxqVmwpJLfLKA2Nq9X4ym82kpaURFRVVY4hNJpPJrtWVfL5cVQ/WwYMHadCgAVu3br3gl7ZMJvuTJEk1rhrs6t8CqA6u3h7/CWUF5fiH+TL1g/EEhPtf8PxySzJ7c98my5BZvTaP+W4mt30MlULB8fwMFp9cTrGQDgIIkpLeQb25v0F/lMLlc2T9VX5JBb/uPsX+4xmUG2v2FgkCBPm60zwmlFYNQokO80NSSBSaKygwGzhcdZa0U7lkZRRQUFhGlcmM0WTB7hBxqCREDdg1EnY/cARLOGJBpVWi0qhQqhQoVSqUKiUqlQK1Ro1ZpaAMB2D54wY2o+lqDr9MJpPdNFcVYCmVSho1aiQHVzLZ39hRdITkikzUChWjwquHBgsyCpk35XPKCsoJCPdj2kcPX3Qye1blBk6VLCG7ooxKsx5BvIsp7R9GpVAQn72Db06vxCFUz33ykcJ5rMUo6nqH1rptosPB4eRsth44zdGUXOcVe1qNiqhgHyJDfKgf5Y+Hv4YCu4Hk8jy+zN5K9qlSyi1V2Kx2bFY7dqvd+Vzc/rj9QalSoNGpUWtU6FRKVGolao0Klbo6ABQQ0ChVaBRKNAoVGoUKrUKFWln9r0ahQqtUIbqZkRcSkMlkt5OrCrD69u3Lb7/9hslkkrPVy2SXUGwpZ3X2bwAMDu1CgM6bopwSPnr8i8sGVxaxhKTSzyk2J5JXYSCzOBxj1UBeu2sgSkFgS95mVqavxyHYcXH4MLb+CNqGNKr1qtAOh8TOI2ms3naEwjJj9X2CgzoNPYhs4IVKD+V2E3tKTvDDmSKsp+zYLHbMVVYc4p85CpV20FYKuFYpcBM0BAf5EhTsg6enOx7urnh6uuGq1eKm0qJX6dCrteiUamcQpVWqUAnKWrXbYDDwVG0PvEwmk90CrirAeuutt2jbti3Dhw9n3rx5xMTEXO92yWS3tXNXDVpEG/X0oXT3b0VeegEfTl1IWUE5fqE+PPXZo3j4utd4XqFpL6fLvsQiGsg1VHA4syn55W14b1AvlAr4JW8dW7K2Y7bbkYojmdl7EoFXMMcvp7CcT3/cRVpOCWadBWsdC24hSmyuds5g4HheKpYqC+YqK3Zb9WR5lRV0BgV+JQq8KrTUcfclMiiQiPBAgmP98Av2xj/UW077IZPJZOe5qgArNDSUF154gSeeeIINGzag0+nw9fW9aFlBEDh79uw1NVImu93sPG9o8MGIuyjMKOb9RxZQUWokuG4gj3/88AXBVYn5MCdKPkSSHGSUuLD5ZGfsYgAze8eh1yn5LmMpCQXHKDWaMOdGMa3tsFoHVw6HxOZ9SXy/6RDlmirK65Wj8gOtQkGJyYq51IJUKuJWIqA3KPA2KdCZVdT3DiY80B/fUC9iBkQQ1TgUpVKeGiCTyWR/56oCrG+++YYZM2YA1ZN4TSYTWVlZFy0r/6qV/dsY7WbngqJDQruirVTyzvRPqSg1UqdBCI9/PBG9V82FMwuqdnGqdAGSJFFUEcPqxGjUSg0ze3XHx0Nk4ZlPOVV8liqziCmrPoNiutIpOqJW7TmRmsfSDQc5W1hCYUAJVX5G1HYJc44NVYYC3xwFbkVKNFUqQqICaBgbSYPYSOo1rYPWRV5sUCaTya7GVQ8RSpLE9OnTefDBB/H395cDKZnsD5vy9mISrYS6+NHWtSEfTP6M4pxSAur4Mu2jh2sEVw7JxtmKVWRU/IQkSYj2aL47EIMkKXisQ1sqVKdZdvIXCisqsFtVWLOa8UiHHvRo+PepbvKKDXy38RAJp7IwupkoiilBUthwGKy4n1ESfFyLv6s7DWIjafBAFA1aReDho7+Rh0Ymk8n+Na4qwEpJSaFjx47MmzfvOjdHJru9lVkriC+sXgH5Lp/2zJv0Kdkpebj76Jn20cO4e/8ZwNgcFRwunEOlrXrVboXUgk92hGN3OOgeE0ym8neOnU2isNKI3eCNvqIZ/zewF3X9L79wqNFkZc3vx9i09xQGrYmSyFIELxGp0oKqyEG9A1ru7tSejpNbEBTuK/84+gekp6dTv3595+KO53z//fcEBQUREhLCs88+yyuvvFLj8S1btjBz5kyKiopQqVR07tyZ//73v/j4XPwc6NixIxUVFc40KJ9++int27dn7dq1vPrqqxiNRvr27csHH3xwY3ZUdt1MnDiRAwcOYLVaSUlJcZ47kyZNYurUqTe5dbLauKoAy9vbm4CAgOvdFpnstvdz7m7sDpF6+lAOzz9EdkoeHr7uTPtwAn6hf85TtDuqOFL0JpW2DNQKPe7K4fx3azk20UqzCBWiz15OlBooNJgw50XRM6wLYwe0Rn2R9DnnVJosbNh1is37TlGkrKAs2IDFy4zS5sBebMP/tIpG2b6M+89g6res3fDi7U6SJKxm2w3dhkanrlWQerFchAALFixgwIABLFy4kJdfftmZIik+Pp4JEyawfPly2rVrhyiKvPnmm/Ts2ZN9+/ZdsNq7zWbj7NmzZGVl1VhCJzU1lUcffZS9e/cSFBREz549Wb9+vTPhs+xCkiRhEWuX/ulqaZWqy543CxcuBKqD87i4uIueO7Jb21UFWEOGDGHZsmUUFxdfcnK7TPZvk2cuZnfxMQDqpvrx6y+bUCgEHnlrDGH1Q5zlTPZ8jhTNxWQvRK10J1j3FK9uOkaV1Uq9MCsOrxOklVRRadBiympGXN2mPNyl7SU/jB0Oid8SUvh+awK56lJKQwzYtFYUVhHB4MDzjJKQEy506dqcof/XE1f9v2d1c6vZxjND3ruh23j7p6euaa7al19+yezZs0lLS2PdunUMGTIEgNmzZ/PKK6/Qrl07oHr9wRdffJHVq1ezYsUKRo0aVaOeo0ePolKp6NmzJ2VlZUyePJkpU6awatUqRowYQVhYGADfffcdWu2tkQD7VmUR7dy/+esbuo0feo+5qoTSkZGRxMfHO/+dNWuWM4+gt7c3J0+eZPHixWRlZfHqq68iSRLNmzdn0aJF8uv+D7uqAGvOnDls3bqVuLg4XnvtNdq3b4+Pjw9q9cVPFnlBUtm/wbrsnUiShH+ZO5tmbQZgwMTe1G3+Z2+RTTRwtPhtTPZCtEpvwtym8tqmU5SbzIQFG5HcT5NbbsZW6o85N4qBzRvzUMfYSwZXJ1LzWLbhIEmGPPKCC7GpbSisIqpyCd90JRGFntzVrS2dnmyJl7/7Reu4FTgcDkS7gxJjFSlFxaQXF5NRXkZuZQVFJiOFZSU3u4nXLCcnh5YtWzr/f++99zJs2DDOnDlDr169OHbsGAsWLHAGWPv37+fjjz++oJ5u3bqxd+/eCwKs8vJyevbsyYcffojNZiMuLo769euTkpKCVqvlnnvuIS0tjbvvvpvXXnvthu6r7OZo0qQJq1atIi8vj3vuuYcDBw4QFhbG5MmTWbFiBQ8++ODNbuK/ylUFWHfddReSJHHixAmGDRt22bKCIGC339iuVpnsZjtrzCOx7DSiXSRvXhqCQ6LDwNbcNaGHs0yp+SinSv+HRSxDq/SmvudMXt10gILKSgICS8A9jTKTDWtxIJ29ezOsZ1MCPC4+6dxuF/ly3R5+PX0Cg3slhvBKBKuIrhQCT6mINnrTZ3B7OvVvgUZ75b+SoTrosZrtmE1WTFVWzCar82+LyYq5yoapyoLZZMNsql43y24TsdlE7DZ79f/tDkw2KxVYMSisGJQ2ytU2KjQiFpUDm8KBTSUhqkBUSkiX+C0mXmWyZ41Ozds/3dglSjW62h3fiw0RPvXUUwwfPhy1Ws3IkSN5/vnnnXnOJEm66GenxWK56I/WHj160KPHn+fbww8/zPr167Hb7Wzbto3ff/8dd3d3Bg8ezJIlSxg3btwV7ee/iVap4ofeY274Nq63Tp06AbBz5046derk7LX89NNPr/u2ZH/vql7hAwcO1LrsVeSSlsluK5Ik8VP27wB4pKipyHNQt1kEo2cOd34RlpqPcqT4v0iShKs6hGiPabwVf5iMslL0vjkI+myqrA5sxSGMa3gfvRtHX3J7ZouN15dvIF48jiXYikJ0oDRJ+Kcq6WyJYMDozjRuW/dve45Fu0hBbjm5mSXkZhaTk1lCaVElxgozVUYL5irL5Z+vlKhydWDVSNg0Eja1hFXjwKKRMGslLK4SVrWEXS0hAY5azqUXHKCyCmhsAlqbAhebElWlwJnaPb1mXYJwyy41YbPZ+Oabb1Aqlfz6668AqNVqPvvsM9544w3at2/Prl27aN68eY3n7d69myeffJIFCxawYMECAB599FFiYmJQq9V069YNAFEUUalUBAUF0atXL+e82aFDh7Jv3z45wLoMQRCuavjunyAIgvN71WarOb/Q1dUVAJWq5vyuoqIibDYbwcHB/1xDZVcXYDkcjr8vJJP9SyRVnCW5IhOHzUH5ogIUwOCpdzkDnGLzIU6WfFw9fOjSjgZej/Lejv2cKihA45WG2j0fmyhAcRTPtR9F09CgS26rsLSSOSs2sNclCatgw6US/DIURFV48eDQXrTu0fiyE2eNFWYO7TnDsQPppJzMwWK2/u3+KRQKdC4aRC8FFb4OKtxFSl1tlKptiEg4AAcSolR9O/fhX90MBQKglATUdiVqUYmHUou/1g1/Vz2+ri746/UEuesJ8fSgjrc3AR56lKqaKXQMBgOebz9fi1fj9rF27Vq8vLxISkpy7uvKlSt57LHHePXVV5k9ezYjRowgNjaWdu3a4XA4mD17NlarleHDh6PVann00Ued9f3www+89957/Pbbb1itVhYvXsxnn32GQqFg9OjRlJaW4uHhwa+//srdd999s3Zbdo18fX05cuQIUVFRrFq16qJl2rVrx7Rp08jLyyMoKIjnn3+e5s2bM3369H+4tf9utQqwjhw5go+Pj7O78WplZWVRUlJywS8ymex25ZAcrMneAYDLQTCVQ/OujajfunqdquzKX0kp/wpJkvDSNqShz2NsT81mZ/pZFJ5JuHqWIiAQ7mjDtL7D8dO7XXJbicnZvP3LJlJ9c7A6bHjlC/TMqsPA+zrTpF091JqLv50tZhtHD6RzcEcyJxIzavxA0uo0BNfxcd78gzxx1etwc9diVNpJNhWRUlFMQkE26YZSLDY7Fpsdq706wbPKoUDtUKJ1KFA6FKgcStSSAm+tK8Fu7oR6ehLp7U2krw9BXu4EeOnRqmu2U5JEkAzgKAfHWXCUgbkUyVGK5CgHyYCjrOAaX6lbz6JFi5gyZUqNQHLo0KE8//zzzonp3377Lc8++ywFBQXYbDa6devGtm3bLjpZ+f777+fgwYO0atUKm83GtGnT6NixIwAvvPACXbt2xWaz0atXL8aPH/+P7afs+po9ezaPP/44r732Gv37979omeDgYD788EP69euHKIq0bduWKVOm/MMtlQlSLcbwFAoFY8aMYcmSJde0sTFjxrBs2TJEUbymem4HBoMBT09PysvL8biCXHGy28vBkiQWpa3DYRIRXyxCbVHw0ndPEhwVSI5xK8ml1ZdaB7p2oYH3JEqqrExdvRaTy1G8fMpQoaC9ex8eib37slcJrtyWyKJTOynyKUWyingWCvTKrMOMuaNwcbvwqkBJkkg/nc+uzSdI2J2C1fLnUEJohB+xnWJo3CqckHAfFAoFFtHO4eIcjhTncqI4n7SyEgpNlVhsIhab3dkr5WrT/HFT46twIybAjxBvDwK93Qn2difQS0+Apx61SgmYwVF63q0MHCVIjjKQykAsRbQX47CXIop2RIcDh+hAdIjY7SKiXcQuioiiSFm5lVY9Dtfq/WQ2m53zmHS6f88VkzKZ7Ma7ks+XWg8RynOpZLKaRElkfe5OQEK93QYmgU5D2xEcFUiZ5SQpZYsAiHAfQqTHfTgkmL0pnlLFSQK8S1ELKoYED2dw/W6X3IZddPDmml/51XCEKk8LCrNISLKSDhVhTH/jgQuCq0qDid83HGXvb0mUFBqc9/sFetKmSwytO8cQFFa9SKXJbmNjdjK7ctPZl5tJudmMyWJDPK+Hy9WmxtfmirtDR2PvIBqFB1AvyId6gXoC3csRpCxEaxqVhkxs1gIcZaWUlZaiwACS5c+gSRSx2+3Y//hXtIuIDhHJUT0/S5IkyiugrFyipEyipAxKSqHUIFFugKJSeVqCTCa7vdQ6wFq1ahXh4eHXtLHS0tJrer5MdivZXXSMAnMpjnIR+9pyXFy0DHykNzmVmzldvhhJcuDv0o5Ij/sRBIEPft/BkfKDhIQX4KJSc3/kMPrUuXRwZTRbmbZ2GcdtGYiCA10l1N2v4d72HRk0rluNIcGSwgq2rktk1+YT2GzVV56pNWpatq9L596Nqdsw2NlDVmW3sjz5CN+dTqS4yojZakOSqJ4fZdXhZtcQ6eFN48AgGgf7Uz/IQbBHIQoxHUPZb1iMpxEKC8nOtmA2m7FarEh/zL06FywBSBKYTBLFZVBS+mfgVFr+RwBVBiVlEuUVKqosLqhUOtQaHSq1FrVah4urC+56d9zd9fiGqoAbu56VTCaTXU+1DrCMRiNGo/GaNyin5ZDdCURJZEPenuqg4mcjCptA34fjEDwKOV34JZIEfi6xNPCejCAI/Hj4OGvStxISnoubWs3QqP70Ce1+yfrPlBbw1KYfyLYW4xAlAlKUxGZ5M37GYGJaVP/QEe0ixxLOcnhvKgd3nnbOrapTN4CeA1vQrG0U2vOWEJAkiR9PH+Xjwzsp+uO9rBGVBJjdidD40L1uGB1jLET4lKEmC0vVdkyVyViKDWRmVVFlMiOKYnUAJUF5BaRnSWTnOSgtV1Bh1GIwaqg06ag0ulBldkGUXKsDJo0Wjc4VD70HPj7eNGwTRHCwH/5+vvh4e6J30+LqqkXvqsFsslFSVEFRYQWFBQYMBhNJJzNu4Kspk8lk11+tAqy0tLQb3Q6Z7LZyqDSZMmsl1kIzqh1mvAO96PlgF46XzUGSIMC1A428H0cQBOKTUpm3bx1h9XLRKVXcV28AfYLuumi9kiTxXeo+5h/cQpXZCjaov0fDowP60PWVWJSq6jQqRw+k8cPC3ykrqXQ+t0HTMPrcE0v9ZmEX/JBJzMnh9d2bSaqoniyuEZU00wRzf+MQ2kbko7LsB/uXWCorSM+twGazYbfZkQCLVSItQyIlTSI9W0GJwZeSSn8kRSCe3sF4eAWid/fEP9iDJv7u+Hi74a7X4e6mw9PDBR9vN3y83HBz1aJQCM79NBotmM02sjKKKc4zcDijmORTuZSVXfhDzmq9/JIRMplMdqupVYAVEfHvyFsmk9WGJElsLTiIaBexbaxALQrc8/gASsSdGKwpqBQ66nmORhAE1h0+xXv71hJS9yxqpYL+Ed3oE3TXRXty7Q6ReQm/siLpAFa7A02hkpZJ7syYMoSGsVEAWK12Vn+1i+0bjwLg7ulK87ZRdOjZiMjowBr1maw2Nh1J5uuTB0m2F+IQJARJoLPeh5c62nF3bKai7DgFyeXY7NUT2YtKJE6lSKRnQXqGREGZNxYpAk/vMMIjo2nUvgEhQV74eLnh4+2G7x/Bk6eHqzN4uhiz2UZmRhF5ueUkHjrLieNZ2KwXLqIpIWHXCvjU8UTtpUbjrcWqcmARzPDVtbxqMplM9s+6/kvJymR3uFRjDhnGfAx5BvQHJaKaRdC8VyQHCqrTmkR6DEer9OFQRg7zD/5CYN00VEqBTkGtGFpn6EWDq1xTGXN3rmFPTiqiA9xOaHkouDljPuiDzlWDJEkcPZDOysU7nJPXewxsyd0PtL9geYazBaVsPnKaVaePkaUtQ1Q4QIAWnkpmtTKjNy+l5GwehRYLDofEsVNw8KiCE6k+FBsCqN+wKY0bN2ZYXCTR9cII9Pcg0N8D3WVWhHc4JIoKDRQVVlBaaqS83ERJSSUFeeXk55dTXlaFQ5CwqiQsagcmVwcmLweiRgBXBSp3NXYNSBoFWq2KPIUJMFVXLoHNaLo+L55MJpP9Q+QASya7QlvzD2AymhH3mFCZ1Qx/6m5SDd9gc1Throkk1O0uMorLeGvrBjwjTqNSCjTzbsLDMeNQKf66BpTExoyjfLDnV/LNRhDB54SeOfcNoX37GADyc0pZuWgHJw9Xz0Py8tEzakoPGrX486ITk9XGrpNn2Xw0mQNlWRS5VmJ3caBRKegbbGFKAyOelv3kZOZgsFpIToW1myGjoD6xbfvS//4ePBUTSmiwN2q18pL7brOJzrlRhX8EVIWFBrKyiimqMGLWOLCoJSwqB9Y//rV4SVj9q4MptVqJRqPCzU2HWqNEdV6weW6rCkHAV+eKr0v1zc/FFZ0o8ut1ev1uhvT0dOrXr0/jxtULwTocDjw8PPjf//5H06ZNa5Rt2bLlBSl1auOVV16hd+/edO3albi4OGbNmkVcXNxVt3nNmjXMnDkTgJSUFIKCgtDr9QQGBjpXnq+N69GWf7vFixcTHx/P4sWLb3ZTABg3bhxxcXE1sgHUpo0zZ86kTZs2DB48+MY38hYgB1gy2RXIMxdzpDwFY5kR9wQl3YZ3xDO6jLNFuxAEgfpeEzmZW8ycX37FFnwUnRJ8VaE81WzSBcGVwWrizV1r+C3jFCZJQlGhIPKsP+88cR8RdfwQRQcbVh5g06oERFFEqVLSc1BL+g6NRfdH+pfUvGI2JZ5m96mzlGAk292AVW8nzN3O4LBc7gkrxNVWTF5WPulGIwlHHaz8RU1A+N08+cIjtGxWD5WyZkodh0OipKSS/NxyCgrKKSgwUFxUSV5uGQVFBsxqEbPGgUktYdY4MGscVASIiMGgUilQqRQolQqUSiVqtQa9WoVarUShEFArlPi7uhHspifM3RMfFxe8tS546Vzw0urw1unw0OpQ/KWXz2AwcDUkScJqubG5UDVaVa0u3vlrLsIFCxYwadIkdu/eXaPc1QRXAL/99luNXITXavDgwc4vwn9bkCRJEhbHjT1vtIranTd3ktmzZ9/sJvyj5ABLJrsCm/P2I4oOhKM21CUK2g9uwemyeQCEuvVDI4Tz5i8rMQcexsXVgovCjf+0mIhKUXN4Lb2ikOe2fktGcTFWQcAlVUdrfRRzZt+D3kVL+ul8flyyg7TkPAAat4pg2NguBIR4AVBSUcXnG/eSmJqDXXCQrzdQqbcQ62dgcGg6XXwKkMx2CjIKSCmqZMsOiQ3xEBzRhw/nv0RMvTpAddLo9LRCUs8UkJZaQHZ2KYUFhup1qgSJKq0Dk8aBSStSordT5etAUAioVEpUKiVqtRKVSoOvWolOqybQTY+/qxv+rq74ubg5e6D8Xd3wc3HDXaP5R79UrBY7/3nosxu6jXe+eqTG1Zq11b17d5555hni4uLw9vbm5MmTLF68mI4dOyJJElVVVUyfPp1Dhw5ht9t5/PHHmThxIikpKYwdOxaj0YhSqeSjjz4iKSmJAwcOMHHiRFasWFFjO++99x5Lly7FbrfTrVs33n//fV5//XWqqqp46623AJg2bRqtWrXi4Ycf/tt2GwwGHn74YbKyssjLy6Nnz54sXLiQ8ePH065dOx577DEABg0axJNPPlnjuW+++SZLlixBqVTSt29f3nrrLTIzM+nbty+BgYEIgsDvv/9+xcfyerM47IzftfCGbmNRp4nolFd23qSlpTFlyhQKCgrQarW8++67dOrUiXHjxuHl5UVCQgIZGRk88sgjvPjiixc9Vzp16sShQ4eYMWMGFRUVeHl5MX/+fBo2bEhcXBwdOnRg+/btZGdnM2vWrKvKWfnbb7/x0ksvYTKZKC8v5+2332bo0KHOnq8RI0YwZswYzpw5g8Vi4YknnmDy5MkUFRXx6KOPkp6ejiRJzJo167ZO6yQHWDJZLZVZK9hfcpLKMiOueyC4biCO4D2YKgrQKr2J9BjOvtRsDB4ncXUzolW48ETjKYS5B9So51BBOs9v+45yownRrMA3xYsuDRvwzNheqASBNUt3s+mnBAB0LhpGPhJH687Vw4WSJLEnKYMvNu2nxGakxL0Kla+FXkFZ9PRLpq5LFY5KCzlpZSQcMbFuk4NdB6BJi468/t8Z9O7RlqKiCn5adYDTSXlknC2qXjVdkDC4ihi1IsYAB1UuDmyuAiq1AtUfQZRe5YK3RombRkOI3oNgvSv+bgp8XSRC3F0JctOjUiionqoOIAEiUIGEAYMoUV517n7+KCGd9+95ixlL5z8iUVH559WSdwKHw8FXX31Fp06dsFgsNGnS5IK8cnPnzqVp06YsXLgQo9FI165dadeuHYsXL2bEiBFMnz6dX375hZ07d/LMM8+wZMkSZs2aRcuWLZ11bN68mV27drFv3z4UCgWTJ0/m008/Zfz48XTp0oX//ve/2O121qxZwxtvvFGrtq9fv54WLVqwfPly7HY7jRs3JiEhgQkTJvDcc8/x2GOPkZ+fz6lTp+jZsyevvfYaABs2bGDlypUcOHAAjUbDsGHDWLBgAQMHDuT06dP8/PPPREdfOsm5DMaOHcu8efOIjY3lzJkz9OnTh+TkZKB6GDo+Pp78/Hyio6N57LHHmD9//gXnStu2bZkwYQKrV68mIiKCnTt3MmbMGPbv3w9UL8m0c+dODh06RO/evS8ZYM2cOZN58+Y5/19SUkLPnj0B+Oijj/j8889p1KgRv/32G9OmTWPo0KHOsps2bcLhcHDo0CGys7N54YUXmDx5MjNmzGD06NHcc889FBUV0aFDB9q3b+9MVH67qVWAlZGRgV6vx8fH50a3Rya7ZW3I24PNbsN2tAp9noJur0WSWfkjADFe41EpXFifdBBXv3wUCgX9g4bQ1K9ujTpOZWfx/KZllDssOMpUhGT706VlfR4f2RVzpZUP3lhH9tkiAGI7xXD3A+3xC/QEIL2glK+3HeRERj5lWhNiaBEjo9Lo5JOCXiEiGEVyUkr4dauZNZscZOYqadWyNatXvUTr1i1ISc7j0/lbOJJ4FofkoErroNTDToWXhNkT1FoVGq0WrQa8NDbUagveOjOBegV6rUiAmwK91gGYMDsqsTmql04oB8qNcPLal8m7JFPF3yelvhiNVsU7Xz1ynVtz4TZqIycnxxn8nAuqPvvsM8aOHUunTp0uKL9hwwaMRqNzTovBYODo0aP079+fUaNGsW/fPvr378/jjz9+yW1u2LCBvXv30rp1a6A6zYdarWbq1Kk0aNCALVu2YDAY6NGjB+7u7rXajwceeIBdu3Yxb948Tpw4QWFhIZWVlXTv3p3i4mJOnz7NmjVrePDBB2v0Vm7ZsoVRo0bh6uoKwIQJE1iyZAkDBw7E39//lgqutAoVizpNvOHbuBKVlZXs2bOHCRMmOO+zWq1kZmYC0K9fPxQKBcHBwfj5+VFeXn7RcyUpKYnk5GSGDBnirKewsBCrtfo9NnDgQKB6LmBJSckl2zN79uyLzsEC+Prrr1m7di3Lly9nz549VP7lB1KbNm14/PHH6d+/P/379+ftt98Gqs/Xo0ePMmvWLABsNhunTp26swOsqKgoRo8efc25CGWy21WBuZSdRUcpL6rA9TeJqLYeKJv9jF1y4O/SHj+XNpzOLyLZfgA1oLOFcG9MzVXafzt+jFf3/IhJEHFUqYjMD6VHxwZMGtqR5COZfDN/KxXlVbh7ujJ8QldiO1Z/4ZisNpbGH2LrkRREyUGhRyUt6qUyNuIgHgoRlVUgNcXMsh+L2PibA5XKjSFDhvDIxDEEBIRxcH8qr89aRW5OdSaFYr2NonoCah8L/t7lBGvNaNUmPHRW3LUSWpUVrVKJVqlCqRCAP9auAir+Mi1FKSjRKT1QK3R/lBIQqDkEWP0lW/P+P/8W+PM7+M9t/bWs0W6+iletettXM3x3I/x1Dtb5zgUd5xNFkW+++cYZHBUUFODp6YlWq+XEiROsX7+e77//nsWLF7Np06aL1iuKIjNmzODpp58GoLy83Bn0TJgwgWXLllFeXs706dMBavR+XaqtH3zwAStXruTRRx+ld+/eHD9+3Ll6/7hx41i2bBlr1qxh+fLlF7Tl/IBLkiRsNtsl9/9mEgThiofvrrft27dTr149QkJCkCQJd3d3dDpdjdclOzub4OBggBp58QRBQJIk+vTpc8G58s4771C3bl1nPZIkkZ2djUajqVHP+a/VgAEDyMnJAeDnn3/+27Z37tyZPn360L17d3r37s2oUaNqPB4SEsKpU6fYtGkTGzZsIDY2luPHjyOKIlu3bsXX1xeA3Nxc/P39r/DI3TpqFWCdS4Mhk/1brcvZgc1qw37IhDZHQbu5FdilKjw00TT0fhSbKDJvx3o0PqUIgoIh4f1qTNRes2cv7x7/BZsggVFNZGEIXVrVY8xdsaz+aie/bziKJEkEhngz5cVB+AZUJzROyS3i4/W7yC+twKYQUdU1MClqH63c0xCqRE4lwRfLKtm+pwJXFy397+rNSy++SHZWFb+sO01y0s7qnDWAUqPE3laJa/BZWnkU4KqtwEWlxk2txk2tQaU4dx2fC2pBg1apx1MdgJvKG53SAxelOy4qD1yUHmgVbuiUejQK139kTlX1JPfnbvh2biU9e/bkk08+4YsvvqCoqIjY2FjWrVvHp59+SqtWrXjkkUfo2bMnrVq1AkClUmG32y+o4+WXX+aRRx7B1dWVkSNH0q9fP5544gnuvfdeZs6ciU6no3v36qwCtZlgv2XLFiZPnsyoUaM4ePAgiYmJiKIIVA9hdenShcjISOrWrdl727NnT2bPns2kSZPQaDQsWrTIuV3Zhb788ktiY2N5/PHHOXLkCDExMcTExLBkyRLGjh3Ljh07GD58OBkZl85yMGXKlAvOlYYNG1JaWkp8fDxxcXEsW7aMd955h0OHDl2yntoEVeeUlJRw5swZdu7ciU6n48UXX3SeH+csW7aMX3/9lSVLljBgwAC2bNlCZmYmPXv25OOPP+aVV17h9OnTtG/f/s7vwZLJ/s0yjHkklCZTVmDAfYdAq2F6JM9TKAQVjXymolRo2XDkBCX6RBSAiy2c/tGtnM9fuHkjS9J3IgqgqtARVhxCgzqBDGnbiLefW05JUQUAHeIacf/E6hyDNlFk1a5jrN57HIfkQPCCtk1O0M//ADos2Iqq+PLrcn5YBzqNhkYNopg+7QkEKZj339mKqerPlc/rRQcS0dqX/bptqHSnUAgi3jodvjpfglyi8dGGoVf5olf5olPq0at90Sn0/7ornG41r7zyClOnTqVZs2bY7XZefvllWrZsydNPP81DDz3E/PnzUalULFiwAKge2pk8eTKLFi1y1nH33Xdz5MgROnTogCiKxMXFMXXqVKC6p6Jr165ERUVd0Ws9Y8YMJk2axJw5c/Dx8aFz586kpqbSq1cvQkNDiYyMZPz48Rc8b9CgQSQmJtK2bVvsdju9e/dm+vTpzp4RWU0vvPACY8aMYf78+dSpU4fvv/+ee++9lylTpvDuu++iVCpZsWKFs+fpYi52rmi1WpYvX86MGTMwmUy4ubmxdOnS69ZuHx8fHn74YaKjo3F3d6dHjx6YTKYaw4T33nsvP/30E02aNHHOx2vWrBkfffQRkydPplmzZkiSxBdffHHbBlcAglSLrimFQsHo0aP56it5KeXaMhgMeHp6Ul5ejoeHx81ujuwafHR6OUcLUjD8UkTIfpGB84tRakXquA+inucorHaRx9Z/QJXHaQSHjsfrT6dDnSgcDgezl3/PpspTALga9QQWB+HvqWdYbENWf7kDi9mKb4AHIx+Jo2Hz6iv7SiqqmLdmB6dzCrEq7HjHGLi/3jYidIVINgenj5h5c14JWXla7uoTR4cOcVRVenLiaK6zp9nX1532naMRoqs4adlOmf0UgmBHKQjU9YihY+Bd1HFtik6pv2nH9UpcyfvJbDaTlpZGVFRUjWETWU1Go5GOHTuybt06wsPD//4JtVBYWEjHjh05cuTILTfsJ5NdD1fy+SL3YMlkl5FckUGS4SyluWV471bQ4ekylFoRD009Ij2GA/Dj4QOY3VMRgCCpJe3DIgF47Yfv2WSsDq6CjX64FHvhotHQJSyY7+dvBSC6cSgT/9MPN331GzUxNYf5P++iwmTB5ibSqPFp7g/dhRorxiKRhV9U8uM6I54eeoYPfQCHrQ77dxmB6hnmMQ2DCe+kJ9v1BDtMi1FXFQMgCKAV/BkSOYqm3m3l3ql/ub179zJgwACef/756xZcLV++nKlTp/L+++/LwZVMxhUEWKtXr75gTL02BEHgzJkzV/w8mexW8HPubirLqlDttRMSZca3cSUKQUNDn8dQChoKDJX8nPsLDjcRh9mTcS3vQpIkPlyzlo1/BFethXqUFStRCNCpTjDxK6qXYIgb0IIhD3ZEpVZiFx38sOMwa/edwC6IWEOqGNpwPx08k3FY7CQdg5dm52GoVNMgJoqWze6myuAOWFGplMS2q4u9iZkzjs2UqLPBDmo1KAUFXqpGdAjoQ7uA1igUisvsrezfon379hQXF1/XOu+77z7uu+++61qnTHY7q3WAVVlZecGllrUh/1KW3a6SKzJILs+gPK+cgASBNv+tQKlSEqrvj6uq+sqdj3f9guRWgIBAPXV7mgUH8fQ3i9hjSQegqSKM8rNKQKKei56D66qTNHfp05R7x3ZGEASKDUY+WLuT0zmFGDRmXCPLebzebwSrC7EUGln6nZFlqwXc3fT069MbF20zbBYJnauGjkObYA2o4HDZr2iV6aiU1e85d2UkTbzb0jmoM54av5t0BGUymezfq9YBVp8+fXjxxRdvZFtksluGJEmsyd5OeaEBXSI06WlCH2RDo/Qkwr16wbzk/ELS2IeIhKMyhEmd49i8N8EZXHXU1qM0XY3DIeJtEyg4mQ3AkNGd6HV3SwRB4Eh6Lh+v24nBZKbSw0JYVBYTQn/HxVJG8dkqXn/fQlqGC62aNcLbswlqIRy7VcI/2h1L52QOarahNlnQakEpCIS7tWBQ+CgCXEJv0pGTyWQyGVxBgBUYGChfUiv71zhclkJKWRaVhUbCT4k0eLsYBAVRHvejUrggSRKLjq1C0hrBoaaddzfqeHjw3M4t4AlN1MFYct2wWKoQyiw48s2olCpGT+1Fmy4x2ESRpfGH+DUhCZtCpDLITJeIE9zttQuptJKk01bemq9AqQylX+/BiLbqRX7d3V2IHezHUbcfUSsqUAgCOqWGQJf69Au7nxDXejf5yMlkMpkM5EnuMtkFRMnB2pwdlBcZ0B9U0PbBUrR6BZ7a+gS5xgGw+fQRchRHcSBhK6vLmLvasHz5NrI9KlEoBbSVPpSUGanMNRBaCTqdlkn/6UeD5nWosth4d/VvHM/Io1RnwhFk4oGwPbTWnUIsrmDbTokf1nrROrYndksdRJsrKpWSuD6NMDVO57hxKQJ2lOgZEj6eZj6xqBSXvlRbJpPJZP88OcCSyf5iV9FRsgz5mPJMxBRWEdSmAkHQEuM1HkGoniQeX7gVO3YsRk/ujuiGraiKr8/sQgoGX3wozbFQmmegTiUEBnrx8NP9CIv0w2S18d8V20jOKaDQ04g+oJRJQVsIdeRgK7awZLmS7MK2tGraHoXDFY0aGrQMxrebkUTLV0jGMgBUUhhTmzyPn4v3TTxSMplMJrsU+ZIimew8VXYz63J2Ul5owGOPQOsxBjQ6DUGucejVEQAUWgrIFdOQAKGiHsObNuGjz36kLFhE6aJGleZCYU4ZwZUSgX4ePDHrnhrB1Ym8PNJ9Swj2TeM/Pt8RYkqnvNDKfz92obCkL4E+3VEoXPHydqXhGJGi9itJsq5GEspA0lJf358XW70uB1e3kfT0dCIjI53/F0WRkSNHMmjQIPr371/rxTb/Ws/VuJILj9LT09FoNLRs2ZJWrVrRokULunbtyrFjx66pDbLaSU9PRxCEGvkHAfLz81GpVM6cfdcqJyeHAQMGXJe6rofzz7sWLVrQqFEjJk2ahNl8dSmzAOfK9f+kWvVgvfLKKzRv3vxGt0Umu+k25O2htLIca7qZGKEc3wY2lAo9UR5/Xn6+MWcTVtGOodSd0Y3as2fNIQ675oFSwLXMnbL0KgKsAsFeHjz20t14+eoxWW28uSKe47l5pHuWUF+ZxDTfeDR2G+kZSlb80gCdrh0e7sHYXR1EDLAh+h2gkDwAFLgS5tKB4fWG4a31ujkH5zYkSRJWq/3vC14DjUZ1RUGLKIqMGTMGq9XKjz/+eNmVuG8Ff82huGDBAiZNmsTu3btvXqNuMEmSsDpsN3QbGoW6VueNn58fGzZswGazoVZX50f84YcfnPn6roeQkJArSofzTzj/vJMkiXvuuYdFixYxZcqUm9uwK1DrAOtW99JLLzF37tyLPubm5lZjiYnCwkJmz57NunXryMvLIyIiggkTJvDUU0+hUl14SLZv387s2bNJSEjAZrPRtm1bZs6cKU/6v8MUWcqIz0+gJK8M750CzR8rQ63VEq6/G43SC4B0YxoJxYdxSBKlhcG0bubH22u/ojzOgeCiRUpUoLOLNA8NZPqse3DT6zBZbby1Mp5D+Vmke5bQtGof0xsfROMQOJ6kY8fB4Xi6h2FTOXB0z8C7bgZmVXVme0lSEunahzENRqBV3tpfxLciq9XOk9NubAaK9z9+CK22domBzwVXDoeDH374AZVKRWRkJPHx8cTHx7N27VrKyspISUnhiSeeICMjgy1btuDj48OGDRuA6pWkR4wYwalTp6hbty5ffvkl3t7eHDp0iBkzZlBRUYGXlxfz58+nYcOGxMXF4e3tzcmTJ1m8eDFQ/YVVr1491q1bR+PGjbFarURHR3P8+HHc3d0vuw/du3fnmWeeASAtLY0pU6ZQUFCAVqvl3XffpVOnTowbNw4vLy8SEhLIyMjgkUce4cUXX2Tx4sV/u48uLi689NJLbNmyhbKyMoKCgvjuu+8ICgoiICCABx98kO3bt2M2m1myZIkzGfb1ZHXYeDrxo+te7/nebfl4rd7Tbm5utG7dmo0bNzJw4ECgelHXe++9F4Dff/+dGTNmYLPZCAsLY+nSpbi7u/Poo4+yY8cOQkJCUCgU/N///R8As2bNIj4+HqhOzh0XF+e8paenX/a1++WXXzAYDJw5c4YWLVqwdOlSNBoN3377Le+++y52u50mTZqwYMEC3NzcmDp1Krt27cJms3H//fcza9Ys9uzZw/Tp0zGbzbi7u7No0SLq169/2WNgsVgwmUwEBQUBcPr0aSZPnkxRURFubm58+OGHtG3blnHjxlFUVMSZM2d47bXX8PDw4Mknn8TFxYUGDRo464uLi6NDhw5s376d7OxsZs2axbhx46iqqmL69OkcOnQIu93O448/zsSJE6/4tT2nVgHWV199Rb169ejcufMVVT537ly2bNnCli1brqpxVyIxMRFBEPi///u/C34VnP8LsbS0lO7du3Pq1CnuvfdeoqOj2bhxI8899xz79u1jxYoVNZ67bt06hg4dire3Nw8++CCiKLJs2TJ69uzJjz/+yJAhQ274vsn+GWuyd1CYW4yQZKN+vVK8w5Vold6E6as/1BySg415P1NaZaK40JsYj3DWfrKFzEYWBBcV6kIt9iI7UXYNo6f2wk2vw2y18/aP8ewpOEu6Jo9WGZuY0T0btULgxGlfNu8citLdB2OEAf/2qXh5lAKgU3oQpG1B79CBRHjUuZmHRXadiKLIQw89xPfff8+RI0cu+mNu3759HD9+nJKSEqKiotiwYQPz5s0jLi6OjRs30qJFCwoKCpg2bRpdu3blmWeeYfbs2bz11ltMmDCB1atXExERwc6dOxkzZgz79+8HoEmTJqxatcq5HUEQGDduHF9//TVvvPEGa9euJS4u7m+DK4fDwVdffUWnTp2A6uTO8+bNIzY2ljNnztCnTx+Sk5OB6mGe+Ph48vPziY6O5rHHHqvVPjZp0oQTJ06wa9cuFAoF48ePZ+nSpTz99NMUFhbSpUsX3n//fd5//33mzp3LypUrr8vrcysbMWIEP/zwAwMHDiQjIwMXFxcCAwOxWq2MHDmSn3/+mZYtW/L666/z2Wef4ebmhsFg4OTJk2RkZNCsWbMr2t6lXrtdu3Zx7Ngx9Ho97dq149dffyUmJob58+ezY8cOdDodc+bMYfbs2YwZM4a9e/dy+PBhjEYj48ePx2w289Zbb/Hyyy8zePBgFi9ezJ49ey4aYOXk5NCyZUskSSIjI4PIyEj69u0LwOjRo/nPf/7Dfffdx549e7jvvvtISkoCwMvLi5MnT2KxWIiIiGDz5s00bdqURx55pEb9RqORnTt3cujQIXr37s24ceOYO3cuTZs2ZeHChRiNRrp27Uq7du2uegSvVgHWuHHjGD169EUDrJ49e9KnTx9eeOGFCx47efKkM1K+0RITE6lbty6vvvrqZcu9+uqrnDx5kvnz5zu7GufMmcP999/PypUr+fHHH52/DMxmM5MmTcLT05ODBw9Sp071F91TTz1Fu3btePTRR+nTp4+cFuIOcNaYx+9pCRjLqghLgFavW1CpVUR5jECp0AJwqPQg6RVZVFkkCnMDuMvHlSPFpzC0lHAICtTHFQTZlfQb1Io6Uf5/9FxtI77oDJm2LDok/8iTw2yoFAoOnwjl98P3Y2pehmeLo0T7liAIElqlmvZ+w+gZ2h+lIF+Dcq00GhXvf/zQDd9GbWRlZTl7eR588EH27t2LVqutUaZr1654eHg48y326tULgMjISEpLq4Pv6OhounbtCsCYMWMYO3YsSUlJJCcn1/jBV1hYiNVa3RN6LiA637hx4+jWrRtz5sxh8eLFPPXUUxdt97kvOqjuSWjSpAmfffYZlZWV7Nmzp8b8IKvVSmZmJgD9+vVDoVAQHByMn58f5eXltdrH6Oho3nnnHT7//HOSkpLYsWNHjXln53pxWrZsyZo1ay57zK+WRqHm3ZaP35C6z99GbQ0aNIinnnoKq9XKd999x8iRIzl79ixHjx4lKCjI+fq8/PLLAAwePJiJEyeiUCiIjIx0HuPautRr17lzZzw9PQFo2rQpJSUlbN68meTkZDp06ACAzWajXr16REdHY7PZ6NatGwMGDOCtt95Cp9MxZMgQJk2axNq1axk4cCB33333Rdtw/hChzWZj1KhRTJs2jY8++ojk5GRn1oAOHTrg7e3tDLDOnetHjx4lJCSEpk2bAtXvlXO9eFDzPCopKQFgw4YNGI1GZ0+vwWDg6NGjNzbAupz4+HjCwsKutZprUlRURE5ODsOGDbtsOavVyueff06dOnWYPHmy836lUsm7777Ljz/+yIIFC5wB1sqVK8nLy+Oll15yBlcA9erVY/r06cyaNYvVq1czatSoG7Njsn+EJEmsTN9GWUE5rqcEBk5To9GDXh1OoGsXAEyiifjCLRRUGMnL8cdX7UH6t0fI6m1D0qnQZGnQGxTU8/Gi/31tMVltzF2xhQ3lSeRlnKB7xVaevF9Cp9Fw+FRzVmR3wq1vEvXqFKBUCuhUKkJcGjAkYhw+2pCbfETuHIIg1Hr47kYLCQnhiy++AODnn3/mP//5Dx99VHMY6q/zsS7Wy6VUKp1/OxwOVCoVoihSt27dGnNWsrOznfVd7EdgeHg49evXZ/Xq1SQlJREXF8eaNWuYOXMmUP0lPWHChAvmYJ1TXl6OTqer8Vh2djbBwdVZDs5PhCsIgjMR+d/t4/79+3nggQd45plnuO+++1CpVM7nnl/v+XVeb4Ig3FJD8q6urnTt2pWNGzeyatUqNmzYwPvvv49KVXP+X0VFBSUlJTXOEfjzwoa/HjOb7eLzzC712l3sflEUuf/++53nstFoxGKx4OrqyqFDh9i2bRu//vorHTt25LfffmPs2LH06NGD9evX8/7777N+/XruvvvuC86786nVakaPHs2LL76Iw+G4oL2SJDn35dy5/td9/et5dv55dI4oinzzzTfOYeeCggJnQHk17oirCA8dOgRAixYtLlsuISGBqqoqevTocUFOtsjISOrVq8fvv/+OKIpA9dwr4KLR/7n7tm7des3tl91cJwzpJGScxGEV6RJZhFt0BoIA0V4POZdl+L1wG/mVpZRVKCkt8qG5QUtuQyumYCWSKKA8riTUpmTkI3GgFHhjxVbWlxwjfdMGOuZt4KkREi4aHTuT27LQ1IyI3oeoF1GAi0ZFQ892TG7wGuNiXpCDqzuYWl09qVkQBBYvXsyyZcv46aefrrie5ORkDh48CMCiRYvo06cPDRs2pLS01DlisGzZskv2DJxvwoQJzJgxgwcffBBBEBg8eDCJiYkkJiYye/bsyz7X09OTmJgYlixZAsCOHTto3bo1dvu1XVSwfft2evToweTJk6lfvz7r1693fib/m40cOZI33niDkJAQ55d+gwYNKCws5Pjx4wDMmzePDz74gN69e/Ptt98iSRI5OTnEx8cjCAK+vr6cPn0ak8lEcXExv//++zW3Ky4ujlWrVpGXV31BzpNPPslrr73Gjh076NevHz179uSdd96hcePGJCUlMWDAAE6dOsWUKVN47bXXSEhIqNV5t3XrVlq3bo2Hhwf16tVj+fLlAOzZs4ecnBxnT9U5zZo1o6CggISE6tyvy5Yt+9t96dmzJ5988gmSJFFYWEhsbCwnT5686mNzR4xBnPsFVVFRwaBBg9i3bx9VVVW0bt2aF198kbvuugvAeaDq1bv4atf16tXjzJkzpKWlER0dfdny5+47derU9d4d2T9IkiSWp2zBUFJJU0sB0d1MCIIrDbwm46VtDECBOZ99RXspqDCSnRlKmIcn5XuzyOpkxyGo0B7XUsekpmOXBjRsXoeZK39lTdERMtesoUdABi+M1+LqomdzdnN+9/SkbePjuGqVBLkGMyBsAnXcmtzkoyD7p4WEhLBgwQImTJjgHH6prbp16zJ37lySk5Np2rQpn3/+OVqtluXLlzNjxgxMJhNubm4sXbr0b+u65557ePjhhxk7duxV7cfSpUuZMmUK7777LkqlkhUrVlzzVZEjRoxg6NChxMTEoNPpaNOmDampqddU552gX79+jB07lieffNJ5n06nY9myZYwfPx6LxUJUVBRfffUVLi4uHD58mGbNmhEcHEx4eDguLi40bdqUwYMH07RpU6KioujWrds1t6tFixa8+uqr9O7dG0mSaNSoEe+99x5ubm40atSIpk2b4uLiQmxsLP379ycgIIDHHnuM559/HrVazXvvvXfRes8NTQuCgCiKRERE8PnnnwPwzTff8OijjzJ79mw0Gg0rVqy4YLj93OT7cePGoVKpiI2N/dt9eeWVV5g6dSrNmjXDbrfz8ssvO4dfr4Yg1aKPVaFQMHr0aL766sKrcS732JgxY1i2bNkN//UxatQovv32WxQKBf3796dJkyakpqby008/Ybfb+eijj5g6dSrvv/8+Tz31FB999BHTpk27oJ5zEwn3799PmzZtaNGiBUeOHKGiogK9Xl+jrMlkwtXVlSZNmlx0TRiDwYCnpyeZmZnOuQYAWq32ghNBdvMcLjvNG78vQiwzcG9EKsH1PKnv9TAh+t5AdQC2LOMrducc5myeityzkdznWof4/ASKIsC11BWfvRrqa/W8/P4D/JaWzoyfvqTg5810jyzh1Ud1uHl6E18WyTGFBg+9iI+rC82829AtcDQ65eUnFcuqnXs/lZeX13g/XYzZbCYtLY2oqKgaQxqyC23bto25c+eyadOmm90U2XX0yy+/IIoigwYNorS0lFatWnHw4MHrurTDv9WVfL7cET1YarWaiIgIPvvsM+dVBlA9JNi1a1dmzJhBv379nEs1XCrAOXf/ucXMLlf+r2Uv5fy5W1AdIV+vxeFk10aSJH48vY0qg4kOqmz8wlzRq8MJduvpLJNSmcyJ0iTKTBZyMkNp7R/I2RUnKB7sAKUS9UklwXYlQyd1otJhZ+b6H8heupK4Zg5ee8wFlac7iXZfUl0l/LUQ6RlBr+AxhLg0uqK1k2Sy623GjBmsWbOGtWvX3uymyK6zhg0bMmbMGF5++WUcDgezZs2Sg6ub4I4IsM7NAfir2NhYZsyYwdy5c/n++++d0ea5K2v+ymKxADh7q84vf26Bt0uVvZSL9WDJbg1Hy8+QnHcWX00lMRFGNDo/6ntPdM67ckgOtuRvJs9QQX6+N3qVJyEHDByOsOJQKVCUKggrU9O4aR1ad63Pw199R8r6NcQE2ZnzhCdaPzfO4sIRizvB7u60DehBW79haBRyr4rs5ps3bx7z5s272c2Q3QBRUVHs2LHjZjfjX++OCLAup127dgCkpqbSsWNHAMrKyi5a9tz95yYQ+vj4OO93c3O7bNlLOf9yZNmtQ5Ik1pzdjtFQRRu3HDx9PQhy7YGHJsZZ5qThOEkl6VRZJUoL/emn9yMv9STZQ0QQBNwzNEQH+zL+qbv4fvdhNm1agba8gDdmu+Dir6NQoWZ7eSCN/RvRO3QMgbqLz/2TyWQy2Z3ntr+K0GKxsH//fvbs2XPRx41GIwAuLi40atQIgDNnzly07JkzZ3BzcyM8PBzgsuXP3de4ceNr2wHZTXGsPJWUokz8NBWE+JnRubgQ4T7U+bjdYWdL3mZKqqooyPchTO+LcV0q6U3sSFoFQomCumddGPdEX7LLK3hz3XeU7T3ArMlq6jXQIWoFdlSE0SG4EyOiXpSDK5lMJvuXqXWAtXTpUpRK5QU3QRAu+VhtLou8VpWVlbRv35677rrromt6nLsMtV27dsTGxuLu7k58fPwFa2mkp6dz5swZOnbs6FxD5FwqnIstxbB582YAunTpcl33R3bjSZLEz7m7qDKYaKrNxc3dhSC3HuhUfs4yO4p+I92Qg9mqoLzYn7pnbFTaLRQ3cOBwSAQlu9KtW2O8gzx4fsVq0jasZcJgJd3au6BxV7GlNJw+UfczoM5jqBS3zno6MplMJvtn1DrAkiTpqm43mq+vL71798ZgMFwweXzz5s0sXLiQsLAwhg8fjk6nY9SoUaSlpfHhhx86y4miyNNPPw3A1KlTnfcPGTIEPz8/PvrooxqXCZ85c4aPPvqIwMDAv13cVHbrOVyWwtmKXNzthfi5VeDm7k6E+z3Ox/PNeWwv+J0iYxVZGUEEO9yw7s8npZUDSSmgLlPQzObDPQ925NPNe9i+8TvaRRp5eKgGjwA18eWB1PEcSVu/e1EKt8YilzKZTCb7Z9VqDlZaWtqNbsc1+eSTT+jSpQtz585l+/bttG/fntOnT7N27VpcXV35/vvvcXFxAeD111/n119/5cknn2Tr1q00btyYTZs2kZCQwP33318j1YRer+eTTz7hgQceoE2bNowaNQpJkvj2228xGAz8+OOP8mXgtxmH5GB97k4qy4200uag0agJ9+mLVunjfHxt9moyy8ooLnHDZPAiYEcRhV4SxmgHksNBZJIHD0yK42huIZ+uX4ZHQTKvzNLg4a/jmNmbVHMMrza79ybvqexWMnHiRA4cOIDVaiUlJcU5tSA7O5upU6fe8CuL7XY7c+bMYdmyZWg0GtRqNVOmTGHSpEkAzu3PmjWLli1bXnTldtk/Lz093ZmE+XznEoSfn0JIduupVYAVERFxo9txTWJiYkhISGD27Nn8/PPP7N69G19fX0aNGsXMmTOJiflz4rKfnx+7du3i//7v/1i3bh2bNm0iKiqKt956iyeeeOKCS+fvv/9+vL29ef3111m8eDEajYZWrVoxc+ZM5xCi7PZxsDSJXFMRLlV5+OorcffyI9z9z6B6b9FuDhckYzCL5GUGU79YibrKQW5vBQ7Bgb5ITbfQGPzq+vLY+x9RsGMjC55R4xfoQonald0lYYyt/xRKhfIyrZD9UyRJwmq9tpXF/45Go/rbJTcWLlwI/PmFeS6A+aeWbJk8eTIGg4F9+/bh6elJfn4+Q4cOpbS0lGeffbZGWTm4+iP1inTxNDLXi1pQy0u13OGu+CpCm81GSUkJfn5+F+Q7uplCQ0P59NNPa1U2ODjY+YFXG3369KFPnz5X2zTZLcIsWlmd9RumShPNhAwUgkC9oIHO3qsSSzHLU9dQajaTmxlEHZU3vgfySI1QYA62gF0i+rQ79/1fV15c9j0Hl3/Jyw9JNIjSovTWsqkklGbe9xLjHXWT91R2jtVqZ9oL397QbXz8xgPXlO9w//79dOrUidzcXPr168f//vc/AN58802WLFmCUqmkb9++vPXWW2RmZjpX4k5ISKBVq1b06NGDRYsWUVxczKpVq2jSpGZmgPT0dH744Qdyc3Ody8oEBgaycOFCOnbsyPTp02uUFwQBm81GeHg4Bw4cICQkBKPRSL169UhNTWXXrl28/PLLWK1WQkND+eyzzwgODiYyMpJ27dqRmJjI1q1bb3qO2mthk2y8fWrODd3GMw1fQiNc/fxMu93OpEmTOHbsGAUFBTRr1oxly5ZRUFBA3759CQwMRBAEtmzZwqOPPsqOHTsICQlBoVA4kx4/88wzSJJETEwMX3zxBdOnT+fQoUPY7XYef/xxJk6ciMFg4OGHHyYrK4u8vDx69uzJwoULGTZsGCNGjGDEiBFA9Zzl119/nbCwMKZMmUJBQYEzuXmnTp1Ys2YNs2bNwmq1EhISwjfffENAQMB1OZa3qlrPwTp79izDhg1Dr9c7cyFNmDCB4uLiG9k+mey6+Tl3F+W2SlyLs/FxNaL38CTKp3ooT5Ik/nf8a4pMlVQYXNFYwgjbUUqxi0B5Gzui6MA/R8vQbu2xa2HFss+5p5Od/l11eAS5sLE8BDvRDI++5+bupOy2k5uby5YtWzhx4gRr1qzh+PHjbNiwgZUrV3LgwAEOHTpESkoKCxYsAODo0aM8/fTTHD9+nH379pGWlsbu3bt54IEHLvrD8eDBgzRq1OiCNfsaN26MWq2+aK41lUrF/fffzw8//ADATz/9RL9+/TCZTDzzzDP88ssvJCQkMHLkyBoBWt++fUlOTr6tg6tbzbmUMeffcnJyyMnJQaVSsXv3blJSUqioqOCXX34B4PTp0yxatIjff/+dBQsWYDAYOHnyJIsWLWLfvn3OupOSkti0aRPffvstc+fOpWnTphw8eJBdu3Yxf/58jhw5wvr162nRogW7d+/m9OnTbN++nYSEBB566CG+/bb6x0tWVhZZWVl06dKFsWPHMnfuXBISEvjmm28YPXo0drudWbNmsXjxYo4dO0bv3r2dOYTvZLXqwSooKKBTp07k5eU5J65XVVWxZMkSdu/ezf79+/92wU2Z7GbKNhWyrSCBKkMVrexnUQgC9cOGoFV6A7AtZxcphhRsokRVURStizSUlFnIi1VgdbWjNQu0LQ7jrqdb0+epJ/C15zLtAS16X1f2mHzIF32Z1GA6SsVtv/LJHUWjUfHxGw/c8G1ci/79+zvniEZHR1NUVMSWLVsYNWoUrq6uQHVS5iVLljBw4ECCg4Np3bo1UJ0p4lzi+aioKGey5/NJknTJBMyXWnQZqlOdTZ06lRkzZvDtt98yY8YMdu/eTXp6Oj169ADA4XDUGMno1KnTlR+AW5BaUPNMw5du+DZqIyQk5IJh28jISMLDw5kyZQqffPIJJ0+e5NSpU87sI/7+/kRHRwOwadMmJk6ciEKhIDIy0nm+QPWK797e1Z+BGzZswGg0snjxYqA6PdXRo0d58MEH2bVrF/PmzePEiRMUFhZSWVnJgAEDmDp1KuXl5Xz//feMGjUKo9HInj17mDBhgnMbVquVzMxMhg4dyqBBgxgyZAiDBw/+V4wK1erb4N133yU3N5devXpx5MgR50Fs06YNycnJfPLJJze6nTLZVZMkieWZW3E4HHifzcPT24i7txfR/sMBMFgrWJG6GqskUloQTEe3SCp/zyLDQ4k12o4gSoSddmHcxN58vXUT+35ZywsT1Hj6uFKg0nLc4kfP4LFEeoTe5D2V/ZUgCGi16ht6u9Z5NOdniRAEAUmSEEWxRr2SJDmXoflrMmWVqmaAd+DAAWdPx8SJE2nXrh3JycmUlJTUKHf06FGg+kv2Ylq3bk1lZSUJCQkcO3aMHj16IIoiXbp0ITExkcTERA4cOMCGDRuczzkXEN7uBEFAo9Dc0Nu1njerV69m9OjRuLm5MWHCBLp16+bsADn/dfjrVJ7zt3t+OVEU+eabb5yv7Z49exg+fDgffPABzz//PAEBAUyfPp3GjRsjSRIajYYhQ4awevVqvv32W0aPHo0oiuh0OmcdiYmJ7N27l4iICP7v//7POef52WefZc6cGzsEeyuoVYC1YcMGAgMDWbt2rTMzdrt27fj555/R6XSsW7fuRrdTJrtqB0pPkVKRSXlOGXVVaShVChqEDUWjrF6F/6PEr6mwGzFV6fA21aXiu1MUuCoQG6qxqm3orAr6RbTAK8SV/7z4HPd0F2jdQouLj5LtFcF4KtvSK6zHTd5L2Z2kZ8+eLF26lKqqKux2O4sWLar1RTVt2rRxfrktXLiQ8PBwHnroIcaPH4/BYACqhyUnTpzICy+84Ow9u5jRo0czadIk7rvvPhQKBe3bt2f37t2cOnUKgLfffptHH3302ndYdsW2bt3KiBEjGDduHN7e3sTHxyOK4gXlevfuzbfffoskSeTk5BAfH3/R4K5nz5588sknSJJEYWEhsbGxnDx5ki1btjB58mRGjRqFxWIhMTHRuZ2HHnqIDz/8EKVSSYMGDfD09CQmJsaZvm7Hjh20bt0au91O06ZNkSSJp556iieffJKEhIQbe4BuAbXq2z7XJfzXPHq+vr506NDB+UtIJrvVmEULq7J+o7KsipCUDDyaG/ELDqaub/Wq7Xuzj5JcdRwRicq8SHw35mGw2jGEuGCMqEQlQp0sPcOf7EK/xx7GR13K1FEuePrq2FXhT46xIS/FTrrJeym70wwaNIjExETatm2L3W6nd+/eTJ8+nZycnKuq7+OPP+btt9+mQ4cOKBQKFAoFU6ZMYcqUKZd93oMPPshLL73EokWLAAgKCmLRokWMHDkSURQJDAzk66+/vqo2ya7NnDlzGDlyJF9//TVubm507tyZ1NTUGkOAAI888giHDx+mWbNmBAcHEx4ejouLC1VVVTXKvfLKK0ydOpVmzZpht9t5+eWXadmyJTNmzGDSpEnMmTMHHx+fGtvp0KEDFRUVTJs2zVnP0qVLmTJlCu+++y5KpZIVK1ag0Wj473//y3333YdGo8HV1dV5McedTJBqsRqoWq1mxIgRfPPNNxc8NmrUKFauXOlMfiyrZjAY8PT0pLy8XM5FeBP9mBXPrxl7UGeeoq1PKt4BnrSsO4lw98GIDpHHf59FmVREZakvnr8F4X6qktwId+wxAvmBhbhYFLwYPICTZSd5aebzfPKihvatvSh31bG2PIoWHjO4v2Hbm72bd7wreT+ZzWbS0tKIioqS16mT/ev98ssviKLIoEGDKC0tpVWrVhw8eBBfX9+b3bTb0pV8vtSqB0sURRSXmLyrVCovOYFSJruZck1FbMs/iMKQQpvAVFy1OmLqDKCOfhAAGzPjMUjFiHYlmow6eJ4sJS/QBbdAd9L9slE5oH6pH/XvCuT+/qN4+B4VrZq7oXOHNeWhFFbUIzam7s3dSZlMJruMhg0bMmbMGF5++WUcDgezZs2Sg6t/yLVd/iKT3aIkSeK71E1U5afR3jsFtVlB/YhBNPSejCAoMNor+TlnIw4kSnIDidxaSqlOQBnkjsGrEofCitqiYFrvvgye9hht65sYO9QFL28Vu41h5JqCqTA2IsrT+2bvqkwmk11SVFQUO3bsuNnN+FeSrymX3ZH2ZR+mtPhHOoYeRmd2EOzfgmbBUxCE6lN+Y+5GSi0VmKp0aI56oLCCMcwDq5+dkoASBAnaE8m3v2/AnH+I/3tEjd7LlWSTDxlCKGcLm9MuOFxelkEmk8lkF1XrHiyj0UhGRsZF7wfIzMy8ZHLn8PDwq2yeTHblREnkt/Q3CPfKQ21SEFOnB7FRT6D4Y92ZrKoMtubsxCFJ5KYF0uKYiQI/HYQpyAnJQyVK+JW7MqhDc4Y9PJz5z6vx8nOlQuXCaTGK41n1sDu09ImMvsl7KpPJZLJbVa0DrNWrV7N69epLPn6ppJOCIMhztGT/qGV73sHHIwdEaO7+H1pF3+18zO6ws/zsKkpNJkqLvNAnayjX2BH83cgLKEApSgSV6nn33tHc9fBDTLvfRt1IHVp3HXtNMVQpwikxBtLCP4im/oE3cS9lMplMdiur9fiGJElXdXM4HDey/TJZDbuOLcXiWr0um1TQklaN767x+LaCLZwoOYPNpqAsI4iQdCulXhpMgWYktR21TcFb94zi9S++oJH/SQZ2U+Hho2NPZThKfRA7UqsXEx3dpOU/vWsymUwmu43UqgdLDpJkt4OU9G0kmT8FDZQU12FGz7drPJ5uTOXnzM2YbHZyMsIIz1VToLOi9dJS5F+MUoIe+gYcTT9Lwo4v+Ph5NTp3F5Is/tj0wexKqYvo0DCgbn0a+vrfpL2UyWQy2e1AnqEruyOIDis70+chaiRyKwK4r/mbaNR/rlFSZa/i86SvKTQaKSrwxM0QhDWtEotKgSXMAkoRN5uGdsFhPPvyY7z2GOjc1JSqvEhXRHCmOIqiKldivH15uHmbm7insttReno6Go2Gli1b0qJFCxo1asSkSZMwm83ExcVdNIfgPyEpKYmhQ4fSrFkzmjdvzrBhw8jOzr5o2YkTJ3LgwIEL7h83bpwzf935Zs2axaxZswCuOS3Mv9X55835t6SkJMrLy3Fzc+PVV1+94Hlbtmyhc+fONGjQgCZNmvDII49ckCrpHEmSePbZZ2nSpAlNmjThueeeu6DMf/7zH8aNG3e9d++OJy/TILsj7Er4H3aPEix2NREeo4nyreN8TJREPjmxmLOGfEwmNY7CujTJFkjUKNB4q6n0K0MA2lq8GPvIOF6bbiPQX41V50WCOQKrzoPjeX54anS80KE7mr/k9pLduiRJwmK7sXNAtWpVrQKI85P2SpLEPffc41wh/WbIzs4mLi6Ozz77jLvvrh5K//jjjxkwYACJiYkX7NPChQtvRjNvCkmSsEuXToR9PaiE2uUjvFiyZ4AFCxYwYMAAFi5cyMsvv+zMORgfH8+ECRNYvnw57dq1QxRF3nzzTXr27Mm+ffsuyGW5YsUKDh8+zOHDh5Ekib59+7Jq1SqGDq3OdrFlyxZnonHZlZEDLNlt78CxJaSaVyJ5QGZpfV7ufJfzMUmSWJj0DYdLjiGKYMyOZmr9Vsz/PR6UAtpoiUpBws+sY8kXnzNumJW2rVxQunmypyoUydOFA2mRKFDyXIeu+Lu63bwdlV0xi83OI3N+uKHb+Oyl+9Fp1H9f8DwWiwWTyURQUJDzPrvdzpQpUzh27BgFBQU0a9aMZcuWUVBQwJAhQ4iNjSUhIQGdTsd3331HVFQUhw4dYsaMGVRUVODl5cX8+fPRarV06dKFjIwMlEolBw4c4Mknn2T79u012vC///2PXr16OYMrgGnTpuHn54fFYuG///0vu3fvJisri0mTJrF69WpmzZpF9+7defrpp1m7di2hoaGIokhcXBxQnZvw008/xd/fH29vb9q1a1djm1VVVUyfPp1Dhw5ht9t5/PHHmThx4hUe8RvPLllZlv7MDd3GqMi3UQvavy94CV9++SWzZ88mLS2NdevWMWTIEABmz57NK6+84jz2SqWSF198kdWrV7NixQpGjRpVo5569erxxhtvOJOGN2nSxLliQElJCS+99BIvvvgihw8fvuq2/lvJQ4Sy25rJWsqpvG+wu0rkGvzoGD4SverPDPG/Zm5nR94+RAcUn63LvIEj+GnFAawK8PbWUepeXp0EdcNu2jYqYkR/DTq9J4dKQ1B4+JJaHECVxZvxzWJp5h90mZbIZJeXk5PjHCIMDg6msLCQvn37Oh/ftWsXKpWK3bt3k5KSQkVFBb/88gsAR48eZerUqRw+fJgOHTrw8ccfY7PZmDBhAl999RUJCQm89tprjBkzhqioKBo0aMDmzZsBWLJkCePHj7+gPYmJicTGxl5w/8iRI50pQKqqqjh+/DgzZsxwPr5y5UoOHjzIiRMnWLFiBWfOnAHgwIEDLFy4kEOHDrFly5aL5k2cO3cuTZs25eDBg+zatYv58+dz5MiRqz+o/wLnzptzt9mzZ3P8+HHOnDlDr169GDlyJAsWLHCW379/Px06dLignm7durF3794L7o+NjXWeB0lJSXz//ff069cPgMmTJzNnzhy8veUFla+G3IMlu63tOjAfu85Mud2Ncpc47grv6Hxsc+ZOlp75AREHZXnBzO05km0/JpBmqEShEPCJUpGvkjAfzUBRlsAzU9VoPDxIKgjFFOSLXeHK2aJowt09GRLT6CbupexqadUqPnvp/hu+jdo4f6jHZrMxatSoGklyu3XrhpeXF5988gknT57k1KlTVFZWAhAQEECbNtVz/1q2bMnvv/9OUlISycnJzp4LgMLCQqxWqzPw6tGjB2vWrOGNN964oD0KheJvc6l17Njxgvvi4+MZNmwYarUaPz8/+vfv77x/4MCBuLu7AzBs2DBEUazx3A0bNmA0Gp1ztgwGA0ePHqV58+aXbcc/TSVoGBX59t8XvMZt1MbFhgifeuophg8fjlqtZuTIkTz//PPO/HiSJF10aSSLxXLJlHcAhw4dvsgtpgAARd5JREFUYsiQIbz77rs0aNCAhQsXUqdOHXr16nXROXayvyf3YMluW2fzdpJr2YToBhmm+vQL64ROWd3l/lv2HpacWYqIiLHUm5fbjaEqpZSVO44D0LFhOKkuhdjMZsp3bGfOE2pcvd0odbhTGOKHUqvkYEYEDknFyEbN5Um6tylBENBp1Df0djXnhlqtZvTo0ezbt8953+rVqxk9ejRubm5MmDCBbt26ORdvPj8QEgQBSZIQRZG6deuSmJhIYmIihw4dYu/evWg0GoYNG8a2bdv48ccf6dGjB3q9npkzZzp7QdasWUPbtm1rbP+c4cOHk5aWBoCrq+sFj5/b/jnnhpYudf/5RFHkm2++cbZ5z549DB8+/EoP3w0nCAJqhfaG3q72M8Vms/HNN9+wZs0aIiMj6dKlC2q1ms8++wyA9u3bs2vXrguet3v3btq1a8eCBQuc58G5nq/Nmzdz11138f777/PQQw8B8P3337Nx40ZatmzJzJkzWbNmDdOnT7/KI/rvJAdYsttSVvFOdp16DbtGJNMYiItnQ7r5twLgbEU2X55ehihJGIr9eLXtVNwKbLz5+a+ISNTx98SiqsLiJlK0I4H/myji56fCrtNzTIhAoXZlT1p9Sox+tA0Ko0tYxE3eW9mdaOvWrbRu3brG/0eMGMG4cePw9vYmPj7+gh6g8zVs2JDS0lLnFYjLli1zzqdycXFh8ODBPPvss87hwdmzZzsDm8GDBzNp0iR+/vln1q5dC1TPV3z77bc5c+YMERGXPud79+7Nd999h8ViobS01DmM2atXL9asWUNZWRlms5lVq1Zd8NyePXvyySefIEkShYWFxMbGcvLkySs7cP9ya9euxcvLi5ycHNLT00lPT+ebb77hyy+/xGq1Mnv2bF5//XVn8HwuwbPVamX48OE8+uijzvPg0Ucf5eTJk4wcOZJVq1YxbNgw53Y2bdrEsWPHSExMZPbs2QwePJgPP/zwZu32bUkOsGS3nVPZ37P9+Exs9iryHR7kK2PpH9oJjUJFqamCmXvnYZNsVBn0vBA7AXeDg9nz1lClAC9PN8bd3ZGj6hwqi4oZHJRE02gB3NzYUxGGTaPj15MNKar0o1VAMM+06yL3Xsmui3NzaVq1akXz5s1JTU3lrbfecj4+adIkli1bRsOGDRk+fDidO3cmNTX1kvVptVqWL1/Oc889R/Pmzfn4449ZunSp8/EHHngAtVpNt27dLvr8oKAgNm7cyAcffECzZs1o0qQJBw4c4Oeff77sUNKQIUPo1asXTZs2ZfDgwTRp0gSoHrp86qmnaNu2Ld27d79okPbKK69gs9lo1qwZXbt25eWXX6Zly5Z/d+hk51m0aBFTpkyp8bk0dOhQPDw8WLVqFZ07d+bbb7/l2WefpXHjxjRo0IDMzEy2bduGVnvhpPrXX38du93O1KlTnT1bn3zyyT+5S3csQbpUAsFrZDKZ2L9/P8Al3+B3MoPBgKenJ+Xl5Xh4eNzs5twxiiuPsSlhBlaLlayiUDIiGhPiGcpLjcdSYTHx5PY3sKhKsFnVDA8cSzttEK/M+oFMhYirXsebzwzlqy838nvDs3js+ok5Iw2oXLQcUtSjyMWPU/l1KTRE0i8qhkdatEUtL8lwS7iS95PZbHbOR/m7OUZ3KkmSePXVV1Gr1bz00ks3uzky2R3jSj5fbtgk94yMDOLi4lAoFHIuQtl1YXeY2H7kdawWKyUpweTEtkalEhga2h2zVeSZ+A+xaEtwiEq6eg7E87iZOd9+Q6a7Eo2Lhhnje1GUUsxxzzzE9GT+M6AcQaEgxeFPkdaXnAp3Cg0RTI3tQL+omJu9uzLZVYuNjcXLy8s5/CeTyf55N/wqwhvUQSb7l5EkicS0T6moysFSqsXapDeoDMS410Fv82b6pi8w+WWCJNBQ2ZP6Z/Ss+Wo7Z71UuLq70K9HU9o0qMNL//cV+a0qmCgdwMdToNCu56QmCIsocbawGaMatZSDK9lt79ChQze7CTLZv94Nm4PVoEEDHA7HZSdpymS1lVGxltT89UgSWAq6k+FmQBBgaEh33t2xBpPPMQTAx9GQQUJD1n+1nUx3Je5BHjRrFs7ofq35ct6vJEWX0a1qG21iRGySkv3KSKwaJbll0XQMbsjIRs1u9q7KZDKZ7A4gT3KX3fLM9mKOpC3CbLSQvTkKS5coAGK9GrJiVxJFromgcOAiBTKosh1fzV1DoU6B5OeGj58HEwa147P//syuqnR8PE4wslkBACsyo7G46LCJroTp2vN0287yhHaZTCaTXRdygCW7pdlEA0cL38VQUkpFujv1OtxPmpiHAGQnK9lVtBeFxoJS0tKvsjc/z4+nUi1gDNHjE+DB6P6t+fXr3exRnMXaNoPpkftQCLAlyQtbQCCCSkFFVV2eatsV5WWunJLJZDKZ7Epc9Rwsk8nE2rVrSUlJwWw2X7KcIAgXzfYtk/0dm6OSw0Vzycw6jLVKoHR3S6zPVlBeZMZU4EpuaTqayLOolUpCrE3Z/fkebAowRvvg7eVCq3ohHF1/nM1iMuUNcnjZZxMuSpEjqUo22rvTxTcPESWtfLvjpXO52bsrk8lksjvIVQVY/9/efYdHVeWPH3/f6amTSkgIISH0lgCClNBRcWl2iiCIBbCAixVRQFlB9GdZXRSVBbEgghQBAWGFKG1FpGMCSUgoSUjvk8m0+/uDb7JEWogJoXxez5NH595zzz1n7jD3M+ece05ycjI9evQgPT0duPBA9vJZfSXAEtWVmL+YzNx48k7biFvQlgHTB7MwczP5JVbccgMwNYpDpwel1AfrwkIcZQ4KG/tg9HGjnrcHp7YnkRyUR5p/Ci+5/wcfvYuUNHgvuQ933mrBpVXIKQzl6c5RdV1VcYNLSUmhd+/epKSkVNoeHh5ObGws4eHhdVIucX04duwYLVq0YNGiRYwZMwa4+Gdn3bp1HDt2jClTptRBScW5qhVgPfvss6SlpdGsWTMGDBiAj4+PjF0RNSq/LI60gp/JTcsn/ovW9Bw4kF908eTllaIvNlOvaSpWjRPV7o55RSDOvFIKg9xRAtzRaTQUn8nkyC0ZFGac5GnPWBoFquSW6Hj79G20qO+Pb2gKJU4NDUwxBHl41nV1hRDXEFVVcalltXoOjVL15XIWLlzIfffdx/z58ysCrIvZs2dPTRRP1IBqBVg7duwgLCyMvXv3XnCtKiH+ihL7aQ7nvE1+ZgEZv/lTz7cVDe6O5NOD20CFsAAnJZo8VKeOZgntOZNyAjXQA2cjHwDcc0r5rV48iQs38/zQEqIjNVhdet5JG4iXM5hOHY5T5HKQVRjO021vqdvKilqlqipl9tp9ktmo1/6lH5gOh4PHHnuMw4cPk5mZSdu2bVmyZAmZmZkMGTKENm3asHfvXtq3b0+fPn1YtGgROTk5rFq1itatW7N7924mTZpEaWkpAQEBfPLJJzRp0oTevXvTpUsXtm3bRmpqKjNnzmTs2LE1V/EbmEstY1vauFo9R4+QhWiVy0+E63Q6+fLLL9m0aRP9+vXjwIEDREWdbXV/7bXXOHDgAAaDgU8//RRFUSrWFwwNDWXkyJFMmjSJffv24XA4ePrppxk7dizBwcEkJCTg4+ND37596d69O7NmzWLDhg18/vnnfPvtt7Va95tFtQIsm81GTEyMBFeixqmqi6N5n2ApKSDzDy0p68N5ccHdvBa3AqfqIlDnhkWfDi5okBbNmRUncChgjfBBRUXNKeFQ8AmOLlvLmNvs9O9iQHEz8eHRnhhTIujWrQCLqRCb3URL79tpExhU11UWtajM7uThf9buzWLR5GGYDJf/Ki1fKufP29LS0tDpdOzatQtVVenfvz8bNmygY8eOHDp0iEWLFhEdHU2zZs0IDw9n165dzJgxgwULFvDWW2/xwAMPsHTpUrp06cLy5csZMWJExSoaJSUl7Nixg3379tG/f38JsK5DGzZswN/fn9atW1e0Yn388ccAREZGsmjRItavX8+YMWPYt28fEyZMAODRRx/llVdeoU2bNixYsICSkhJ69OhB586d6d+/P7Gxsdxxxx0kJiZis9kA2LhxY8V6luKvq1aAFRMTw4EDB3C5XJdcs0qIK5VaspHswjjSE/I5+lVbOvS8hURTLqm2dBRUPDzysTpUypKDKPw6HQXw6h5BsdOBtaSIJK+9pCz9ib4dHDx0lxt6P18+PdaB4oTmdO1mwBIch6qq2K238ni3rnVdXXETCQkJYf/+/ZW2hYeHExYWxsSJE5k3bx5xcXHEx8dTXFwMQHBwcMWC0A0bNqRfv34AREREEBsby7Fjx/Dx8aFLly4A3H///Tz++OMUFBQAMHDgQODsOoG5ublXo5o3BI1ipEfIwlo/R1UsXLiQESNGADBy5EgGDBjA22+/DcC4cWdb2f72t78xatQo8vPzKx27ceNGSkpK+Pzzz4GzS04dOnSIgQMH8tNPP+Hh4cHQoUNZt24dFouF//znP0yfPr1mKiiqF2C9+eabdOnShfHjx/POO+/IWnuiRpQ6MkjKX0p2ag7J6xoR2qgZgyffycQ981EVCDFpsTrLKCnQ471Sh1arodXQaLanZ1JWaicl/zcSf9pA22ZaXnzMHZ2vmY2JLcne2Ypm/VMpCzgJgIlWTO02Fne9oY5rLGqbUa9l0eRhtX6Ov2L16tUsXLiQKVOmMG7cOHJycioeHDIYKn9GdbrKX9lOp/O87klVVSuWJytfK03GyF4ZRVGq1H1X27Kysvjhhx/YvXs3n3zyCXD2Cf7yRb2156yVqqoqer2+0vFOp5OvvvqqIkjPzMzEbDZTXFzMm2++iaenJ3369CE3N5evv/4af39//P39r1LtbnzVan5q3bo177//Pv/+97+pX78+rVq1omfPnhf869WrV02XWdyAHC4LcbnzKMjOJTfeA9uJpjz54Tg+PLSVYqUQkxZ0hmIcdhe2XT4E6NwYO+te9uXlU2a1k597koTtPxEarDDnJR9Mgb7sTw8jYX9XGgxOwDPgJIoCkZ4xvND+BQmubhKKomAy6Gr1768GL1u2bGHYsGGMHTsWX19fYmNjq7wCRvPmzcnJyeG///0vAMuWLSM0NFRukjeIL7/8kp49e3L69GlSUlJISUnhzTffrBhntWTJEgBWrVpFy5Yt8fDwQKfTVQTYffv2Zd68eaiqSlZWFh06dCAuLg5/f3/MZjMrV66kV69e9O3bl5kzZzJo0KA6q+uNqFotWBs3bmTixInA2ZWl4+PjL5pWfjmJy1FVFwez3yS3JJ68MyUkrWzHg88OYm/6GfaUHETRQ6iXlkKrnaIMN4IPmhj3j7v5dk88JaU2MjOOc2DfMnw97Lw3zRu/+p6czvfh19Jg6v1tGxqNC51iYGDoBG6pd2tdV1eISt544w2GDx/Ol19+iYeHB927d+f48eMV3YGXYjQa+fbbb5k8eTIlJSX4+PjIAOUbyKJFi3j99dcrbXv88ceZNWsWZWVlJCYmEh0djaenZ0U3YJ8+fRg1ahT+/v7MmDGDJ598krZt2+JwOHjllVcqxgEOHDiQZcuW4e/vT9++fXn00UclwKphilqN1Zi7dOnC7t27ueuuuxgxYgSBgYGXDKRuxlaswsJCzGYzBQUF0oV6GaeKfiCp4CsykwvYN68hQeYOPP3RY0xY+wWnTccI8tSgVQuwWh3YVzZgbLfeWEI8WfPLESxFJfz80/s4SvP5eKY7Ldv5kVdiZmNJCHqzHUVR8DXU465GjxHh1aquqyqq6Ur+PVmtVpKTk4mIiKjoIhNCiJpwJd8v1WrBOnz4MFFRUaxcubJaBRSiXJ71MMcLlpCTlscfS+pTlOzLmIUDeO2HTaTqktFpXJh0FopLHBQk+dDHFEZY18a8/dVW7DYHx/duwlKYz4sT3GjZzg8rRrbYA9GbHSi4cV+jp2nrFyUtqUIIIa6qao3Bcnd3p3HjxjVdFnGTUVUniQWfU1xQzIlf3MneG8Tfnh3IxwcPsM+xF3R26nlbsZTasOQbqR/rx4PPD+bfa37FbnOQ8t+tJCTt4s6eWoYM8EZvhN02M6qbglHjxQMRk2jnHy3BlRBCiKuuWi1Yt99+O5s3b6a0tBQ3N1nDTVRPuiWW3IJkMo8Xk7w6mgHjb2ejI58TShJ4Wgg1a7CV2bDbVNgayMMP3camfYkkHz/J3s3LyS9OJqIJvPCkL1o3IwcsXmS4vGno0YrRTZ/GXSdds0IIIepGtVqw5syZg6IoDBo06Lx5XYSoCoerlOSCZeSeyefU5ga07twWa7t6nCpLw+WfQ7CPO6q9CLvNRXG8H6PadSGgdQjrYveyY90C8kqSMflrefP1YDx8TeS6tMQ7Amnt14pHW7wowZUQQog6Ve21CMsXmuzYsSNGoxGz2XzeHBxw9inCEydO/OWCihvLqeK15OWmU5SmpTg+nAZTW7L0t33YGqbh525E4yyguMxGWZGRnnltGDC+B9Pn/8B/f/gSizMXXT0P/vHPxoQG5ePSONleEErzgFAGNZiIVqnWx1oIIYSoMdW6E3333XeVXlutVqxW6wXTyvgX8WdWRzYnC9ZSkFXIiY1NCL63ExvjErH5Z+Hu4UJRzlBS6sJpV/D8pT4TZgxl6aa9/LR2Obm5KSi+Osa91o5bg1Ixah38WBBKmF84d4W+jLvOXNfVE0IIIaoXYCUnJ9d0OcRN5HjhN+Rn55KX4Ema0oyjjkJcplLcgorRG7JRbS4cJTpMa+sz+aF7SDiTw/yP55N4cBsuLxc9J3RmbPPTeOjs7LfUw8s7lL71x0hwJYQQ4ppRrTFYjRo1uqI/IcoVlB0jNe8XCrKLSdgcQV6rAFBUApoVo9UVonE5cZVoCVzZkJlTHiE8Kow5H33D0T1bcZpcRNzXkdfvPIOvsZQ81QeLe1NigkbRwF3muBLXrpSUFAwGA9HR0URHR9OuXTvCw8OZMWNGXRftslJSUggPD6/rYtyUUlJSUBSlYs3BchkZGeh0OmbOnHnRY3v37k1sbOx5+V3oWs6fP79idvgryU9cmgxWEVeNqrpIzF9MTloumb8HkNm4JXoPI74RJRQrZ9BrC3GUaDBt8WPcI3fTsFkw4559g5++W4RD68Sza2PmjLFQ31hCqcudPLc7GeB3L/VMEXVdNXGNUlWVMkfVlp2pLqNOW6WhEH9e7DktLY2mTZsybNgwWrWSHwjXElVVLzrspaaYTKYqfW4CAgLYuHEjdru9Ypxz+QzsNWXChAk1lpf4n2oFWH379q1yWkVR+Omnn6pzGnEDyS+L52TR96SmH6C00EXC4ZaUdfZCcSuh0PM0Bk0OTquC7qgnd0T0IDqmOdP+8R7ff7MAu92J6ZYQnp/sR7RXCqpLi8N7PLf5jZExfuKSyhxORn9Wu0vHfPnYMEz6K/8qTU9PR1VVvL29mTt3LosXL0ar1XL77bfz1ltvcerUKYYMGUKbNm3Yu3cv7du3p0+fPixatIicnBxWrVpF69atWb58Oe+++y6lpaXYbDY+/fRTYmJi6N27N126dGHbtm2kpqYyc+ZMxo4di8ViYdKkSezbtw+Hw8HTTz/No48+yueff86GDRsoLCwkKSmJqKioikWFy61Zs4apU6eyefNmfHx8GD9+PPv27UOj0fDcc8/x0EMP1dTbWqesVis9evSo1XNs27atStMceXh40LFjRzZt2sTAgQMBWL58Offcc0/F/1/o+pfLzs6mb9++vPzyy3Tp0qVi+7nX8tNPPwVg5syZ1KtXjwcffJBt27ZhtVpZvHhxxWLRf85v+PDhNfJe3KiqFWBVpZlQURRUVZUb4E1OVVWOF37DycK1WAosFGQXkrS2CQXtm6LRg9IwE62SieoAzUk32h1rx91v92PJivV88tG/sNud+PZoz8Bn/Hmg4V4UF+Trh9BWgitxnUlLSyM6Ohqr1UpWVhadOnXi+++/5/Dhw6xYsYI9e/ZgMBi49957mT9/PgMHDuTQoUMsWrSI6OhomjVrRnh4OLt27WLGjBksWLCAd955h48//pi1a9cSEBDA4sWLmTt3bsUNtqSkhB07drBv3z769+/P2LFjmT17Nm3atGHBggWUlJTQo0cPOnfuDMDOnTs5fPgwnp6edO7cmR9//JG2bdsC8NNPPzFt2jQ2bdpESEgIL774ImazmcOHD5OdnU3nzp0ruj9FzRo2bBjLli1j4MCBnDx5Ejc3N4KCgnC5XJe8/gUFBQwcOJCpU6cyfPhwUlJSgPOv5bmysrKIiYnhvffe47333mP27NmsWLHigvmJS6tWgLV169YLbnc6neTm5rJjxw4+/fRThg0bxgcffPCXCiiuX6rq4kTRKo7nrCL7dA6pO/xI/7Utaa3b4nTTQVAW6M+gVRxosg10y+7GI+/cx7vzPmPuW29RVmbHvWU4TR9twjPhP6OokOlsTnSjVyS4ElVi1Gn58rFhtX6OqijvInS5XDz33HMcPnyYvn378tJLLzFy5Ejc3d0BGDduHIsXL2bgwIEEBwdXtB40bNiwYgHoiIgIYmNj0Wg0rFy5krVr13Ls2DFiY2PR6f73tV7e4hEdHU1ubi4AGzdupKSkpGJx4MLCQg4dOgRA9+7dMZvPPizSpk2bimOys7O56667mDZtGg0aNABgy5YtfPbZZ8DZbqyhQ4cSGxt7QwRYJpOJbdu21fo5qmrQoEFMmTIFm83G0qVLGT58OCdOnLjs9R8/fjwBAQE88MADFdsudC3/7NzPzZo1ay6Zn7i4agVYl1u8+b777uOuu+6ib9++dO3alccee6xahRPXL5fq4HDOO2QW7iEjJYvkNQ3JTmxOSUxD7F5atB5lWM3pmPWlKBYtbVOiefjpe1n2/QbmvvUWtjIHHi0jCZvUnn+02IW7xkFemZmoxotknitRZYqiVKv7rjZpNBreeustoqOjmTt3Lk6ns9IPBlVVsdvtABgMhkrHnnvzBCguLqZTp06MHTuWXr16ERUVxb/+9a+K/eU38XPzdzqdfPXVVxWBW2ZmJmazmW+++abSTb+8F6K8zGvWrGHYsGGMHDmSsLCwS5b7eqcoyjW1Som7uzs9evRg06ZNrFq1io0bN/Lee+9d9vq/+OKLbN68mX/+859MmTIFuPC1/LNzPzfln4GL5ScurlpPEVZFr1696Nq1a6WLLW4eJ4pWkVG4hzPHczm2thG/cwun7mhEgbcOo0GDNiwDd0M+ODT4H6/HpKfGEZ94nOdeeImyMgc+Ya1o/PwtzIz6nVCDBbtTj3+9uei0HnVdNSH+Mp1Ox//7f/+P2bNnEx0dzddff43FYsHhcLBo0aLL/ogtd+zYMbRaLVOnTqVPnz6sWrUKp/PSg/r79u3LvHnzUFWVrKwsOnToQFxc3CWP8fPzo3fv3kyZMoWJEydW5FPegpWdnc2qVavo2bNnlcotrtzw4cOZM2cOISEhFa2Ml7v+7du3Z968ecyZM6eie/BC17KqLpSfuLhaC7AAgoKCSEhIqM1TiGtQoS2JlPyVZJ3MZv+qSHYQhSbSD71OS5MgX4xNs7GoGeg1TvS5Oh7v+TD7Dx3g3uGjKSosxBhYD+9nOzA24jBt3ApwOXQYPd8g1Ny1rqsmRI0ZMGAA3bp1Y+vWrQwZMoROnTrRunVrQkNDmTRpUpXyiIqKon379oSHh9O6dWsCAgJISUmp1OrwZzNmzMBut9O2bVt69OjBK6+8QnR0dJXON2XKFE6ePMmSJUuYPn06+fn5tGnThh49evDSSy/RqVOnKuUjrtyAAQM4cuQII0aMqNhWlesfERHBs88+y/jx4yvld+61vBIXy0+cT1Ev9S/xLygoKKBp06bodDrS0tJq4xTXtMLCQsxmMwUFBXh73zzr4rlUO3sypnLyxCGO7fVmfUIXgiLqERboywNd2vKvxBUUko6PWx66Yg1dS7rTrXknBt8zjLz8QlwmI01mDeDx6EQG+KSiuDQ4lfE0biSPEd/MruTfk9VqJTk5mYiIiCsa5yKEEJdzJd8v1RqcsHDhwovuczqdZGZmsnjxYnJycnj44YercwpxnUouXEZ2biI5WU42Jkbh18CPLk3CaBoWwBtHluAy5OPnVoC+SIN/egAd2rblnmGjyM0rxOBbn/rPd+OlTgfp4pENLoVie09aNpFfSkIIIa4v1QqwHn300cs+xaWqKmFhYcyaNataBRPXnzzrIU4UrCU3I58t+ztgMgfQp11TSnV2Pj3+PaqpED9jAaZCMOW48WjXR3jw4XFkZOagNwfi/9RtTO+2i1s9ssGpxakdQ8smk+SJQSGEENedagVYDz300EVvehqNBk9PT6Kiohg2bBgeHjIo+WZgcxYQnzef/Ix8jhxrwOn8UJq3DeRA3hkyjEfBkEuAoRBTkYLOomN8xwnMff9DEpJS0Jg88fn7nUzscpBbPbNBVcD0dyKCR9d1tYQQQohqqVaAVT5/ihAAOaV7OZr/GXm5aaSfgF/iWuMR6kWWy4JddwqtIZsAjyKMRRrcSt15qMXD7Nn3B6u//x6H4sJ/TC+e7/47d/qmAlCqvZ/mElwJIYS4jtXoBDEulwtFUaRL5ybhcJWSVPAFaUVbyc8sICPBxYbfb8Ho6wPeOkrdTuLtmY63eyluFgNtGrZiTMuHOXz4FNOmz8DmcODZP4oZ9yVzm28aClCs6UuLBi/XddWEEEKIv+SKpmkoKytj3rx5zJs374L7f/zxR4KDg5k5cyYWi6VGCiiuTUW2ZPZkvkBK1ibSj2eyf7MvS2N7YHEPxuGrR3XPwjfoNGb3UjwdbtzerB+Pt5nAzj0nGDVuAiVFRWiD/ZnxrIvbfM8+ZWrTjaRl6HsSoAshhLjuVTnAyszM5JZbbmHSpEksX778gmm2bNlCZmYms2bN4pZbbuH06dM1VlBx7Shz5nEo520yM1JIiCth5X9uYXNWR7yahODZwBuDhw2v+ifw0NvwUt15JGosgxvew1frfue5F18hOy0FVa/nydnhDKp3tlvQYRhNZMiLdVwzIYS4tpSUlPDMM8/QpEkToqKi6NKlC6tWrbqiPMLDw0lJSWHNmjVMnz69lkoq/qxKXYQ2m41+/fpx5MgRmjZtetGpF1599VVatGjBnDlziI+PZ9CgQezZs+e85R3E9cvhsvBHzvtkpKdw/LTCytieGD3NRLYIoGloILszTmEKSsDbzYrRpefRNo8QYAtlyMiJ7N+zE0txIS4XjHq9HY+3PQ5Aov0W+oY9V8c1E6L2pKSk0Lt37/Nmv46Ojmb//v11UiZxfRg6dCgtW7bkyJEjGI1GEhMTGThwIDabjWHDrmydzSFDhjBkyJBaKqn4sypFPp9++ilHjhzh9ttvZ+XKlRWLkv6Zt7c3jzzyCPfccw8DBw7k119/ZeHChTz++OM1WmhRN3Ks+zia9wn5eWdIzbezflc3vP0DePxv3cl1WFkbF0+ZexLB3sVoXApDGw7hwMZEps0YS0F+Hi5Vxc1Dz1OvNWFkzxQ0iso+S336Nn6/rqsmblCqqlLmuPTSMX+VUaetdre2BFfXprPzb5fV8lmMl/3c/PLLLyQmJrJp0yY0mrMdTk2aNOG9997jmWeeYcOGDfTu3ZuxY8cC/1s7MDc3l1GjRnHq1ClatWqF1WoFzj6gFhsby+eff054eDgPPfQQmzZtIicnhw8//JABAwbUao1vNlUKsJYtW4bJZGLhwoUXDa7O5evry9dff02zZs1YunSpBFjXuRL7KeLzPqbIlkxJYSkJx+385/dbMJmCmTbyDtYdO8ah1DMUc5KQ+mfQotJEF8lnz3/Jz9t2YXc60fn4cuvd7fn7vamE++di0DrZW+qP0es5vAxedV1FcYMqczgZvuTbWj3H0pHDqr2gdPkNcebMmaSmppKUlERKSgp33nkn8+bNw+FwMHHiRA4fPkxmZiZt27ZlyZIluLu789FHH/Hhhx+iKAp33HEH7777Lg8//DDZ2dkkJSUxa9YsIiMjeeaZZygqKsLHx4ePPvqIFi1a1PA7cCMqQ80ZWatnUPyXAJeeCfy3336jc+fOFcFVuZ49e5KQkEDLli0veNz06dOJiopi/fr1bN++nWXLll0wndls5r///S+rVq1i2rRpEmDVsCp9Kxw+fJiOHTsSEhJS5YwjIiK49dZbOXjwYLULJ+qWw1VKpmU7xwu/wWItIjOrkN8PB7PrYHNMbu5MGdGTD3f+l/SMPJymTEKbp2PQOvHT+nBg/jG2/LwTl1aDuWcXHhrtzv3NEtHrHKg6F+sKG5CrxjAtpH9dV1OIa8L+/fvZvn07drud5s2bM2HCBPLy8tDpdOzatQtVVenfvz8bNmygcePGvPfee/z22294e3szZMgQtm3bBoCPjw9xcXHY7XY6d+7M6tWradSoETt27GD06NH89ttvdVxTUVWqquJwOM7bbrPZLnlcbGxsxRqDMTExNG7c+ILpBg4cCJztqs7Nzf2LpRV/VqUAq7S0lODg4CvOPDQ0lN27d1/xcaLu5VkPE5f3Lyy2PDKy8kk45cXWnd2xWk0EB/ky7LZbWLBzN2npefgE5hHa6gwGowuz3ouCpWVs2LAFh0FD60du5+WBJ4k0n0KvcZHidOPXfH/sNODvLZ6SJwZFrTLqtCwdeWXjVKpzjprQr18/jEYjRqORJk2akJubS69evfDx8WHevHnExcURHx9PcXExW7ZsYfDgwfj4+ACwbt064OwyZt26dQPg6NGjHDt2jKFDh1acIysrC5vNhsFgqJEy37iM/9fCVLvnuJxbb72VDz744LxrtmPHDpo0aYKfn1/Fws52u71if3nLaLmLjYMuX0vvz+lFzahSgBUSEkJqauoVZ37mzBk8PT2v+DhRd8qceZws2Ehc9nJyC4rJLjBwLKkRB440JkDvxiO3daBR61BeX7WJvPxi6oXmUr91FnojBJoC0Wx2Z+GXC7BrVe59tgOT7jiCr6kUVaPyS0k9UuzeKIo7YyKeJcB08yyCLeqGoijV7r672s5dOLb8hrd69WqmT5/OlClTGDduHDk5Oaiqik6nq/TjJC0treL48mEcTqeTxo0bV4zzUlWV1NRUCa6q4Ox7W/cLhffo0YO2bdsyadIkPvjgAwwGA0ePHmXKlCm8/vrr/P777xW9ROc+Wdi/f38WL17Mu+++y2+//UZiYmJdVeGmVqVpGlq2bMnBgwfJy8urcsYFBQXs2bOH5s2bV7tw4upKyt3B6rhH+Tnx36Tl5HPoWD1WrOtOyr4mPN2zK4tmPsJJDyfTV20kL7+Y0MgzNIjKwuimoYFHA3x3NGDe2//GrnHxzMxmTBt8inoexWSrelYUhJNsD8Fd14RhjabSzDu8rqsrxDVvy5YtDBs2jLFjx+Lr60tsbCxOp5OePXuyfv16ioqKcLlcjB07lu3bt1c6tkWLFuTl5REbGwvAkiVLGDx4cB3UQvwVK1aswGw207ZtW1q3bs2oUaOYM2cOI0aMYOLEiWzbto127dqxc+fOip6m1157jZSUFFq3bs2bb7550S5CUbuq9NNu9OjRrF+/nlmzZvHuu+9WKeM33niD0tJS/va3v/2lAora53Kp/Bi3mZPF76C67GTleBN/oBFuqRHMGdKD5rc2YVNiEo98vYLMzHycZQ4im6ViblGMVqvBN8+fIx+cYtOPC3Hg4oXpYTzQrwgPg409Fn/2WUNo5DmIpxvdhae+7n8VClEXTp48WalFv0OHDpc95rHHHmP48OF8+eWXeHh40L17d44fP84jjzzC5MmT6datGy6Xq+Lx+5UrV1YcazQaWb58Oc888wylpaV4eHjw9ddf10rdRO0xmUzMnTuXuXPnnrcvMjKSPXv2VLx+//33gbNP9J/7WSg3duzYiicOz50ypHyeLFGzFLUKHa82m40OHToQFxfHtGnTmDZtGkbjhfuPbTYbs2fP5vXXXycwMJA//vgDf3//Gi/4ta6wsBCz2UxBQQHe3tdmV5jLpRKbuJ7Dmesw6JJAdXAm2Z/S7T0Z+WA/HI3MbIpP5D+Hj1KQW4LL5cJc4iSswxn0zYopOlVI9oY8Dv+YSHGZHU9PlVdeDaVPjAsvk5Vfiutx0tmJURFP08jzysfwCVHuSv49Wa1WkpOTiYiIqNTtJoQQf9WVfL9UqQXLYDCwbNkyunTpwhtvvMHChQu56667uPXWWwkKCsLhcJCZmcmvv/7KunXrSEtLw83NjbVr196UwdW1zOZwsvfkafad/oUix3/x90nAqHOiulTy4n2J9hpP8bgA/vH776T9XIDVUoYKmAtVGrmXYrw7C5fRyh/Lj3B87UlK8hScqPS8rSEvPqHBP9CBh7GMn4qCOG5vztQ2r+Khc6vragshhBBXVZVasMolJiYycuRI9uzZc8Gnv8qz6tGjBx9//DGtWrWquZJeZ661FqyU7DzWH4zjeP4vhAQexNstC6fThepSOXasASeOh6IJaEqmtYySIisulwu9HQJyXTQ3GvEbbiPVlERxdglHvj3CydgMSksUfFs158mJZv7WJh1Fq2LTufjZEkiGI5BxkTNpYW5U11UXNwBpwRJCXAtqvAWrXJMmTdi9ezfbt2/n22+/JT4+nvT0dHQ6HcHBwXTs2JGhQ4fSqVOnv1QBUTPsTicHTqbz45FjpBb+RrOw32kemovqcGEr0nDsdAPi0xtQZA9G722gKDMfXCo+BS4i7Cbu6NKMwk6Z7LP8xs7/JpK+N53Tv56hLF+HQ9XSeWw3Xrw/hwYeaWh1Lv4o82K/xRun4k5H39ESXIk6JY+dCyFq2pV8r1Tr+eWYmBhiYmKqc6i4CnKKLfxwMJ6tccfR6NJoFrqH6HppKGVOXLkajiY05Le8ZmDwQaMomDPLMGcW0NAO7SJDGTS2Cwn1j/Ldb0s4/uVxTu06RUmmBXupDkepDvfgBoyfHMLorim4GWyUobC1uB6pTg9QjGiV3tzbqFddvw3iJqXX61EUhaysLAIDA2WuNSFEjVBVlaysLBRFQa/XXzb99TFBjLgsu9PJ0TNZxMYfZ+vR4ziw0qrRfhoHHUUtc0AJHE5qxN6Mljhxx+FyEnDcQqNTTvRO8PLzoP/ETiQGHuGFTX8nYXsC2UezUVVwlOlQXb6YI1oxaKg7d8dk0Mj3JG56O4lWL36x1KMMIxZnPYyaKJ5r8wA6Tc1MvijEldJqtYSGhnL69Gl5MkoIUaMURSE0NBSt9vL3OAmwrlNFZWXsS03nx7hjHD6TSXphETaXE6eqEuKTRb8W+/AylOBwQmJ6MHuOtqTY6oHiUvHLsxKc4cK/TENYn/pYYnI5Yz/Oq2u/5diPCbjsLlTA6dBhqNec0NZh3NZXT7/IU4R6nsFktKFqVTYX1WdvSSilzggcLn8GN7yFuxq2R6+Rj5WoW56enjRt2rTS7NZCCPFX6fX6KgVXIAHWNc/udBKfmcWBMxlkFZeQV1rKqfwCkrJzKbRacbr+1x9s0DiIifyD1iHHUZwuivNNbN/WksysQIwGPeF5DhqW6mnfuQluw1T+k76Jb/esJmNmBoUnC1BRUVUFfWAgbpEt6NHLn9sis4gOTMCkt6PVunBpYHexH3E2b05amqDRNOPesFvoE9RC5rgS1xStVlvlL0IhhKhpEmBdo/ampvHjsUQOpp/BYrdTZndgsdkpsdmwOZwAGBQNvoqeSLWASL+9BNbPRKe3o+aqpGwLIO3nloS6edNIq6Fdt8Y0+JsPa+PW8u5vX5HxTRr2Ujso4HJpcDh0+IbXo/vfmtO1rUJMg9N4GU+g07rQalyk29yIL/Emye5JvsOLfFs4DT3a8myrO/EzetTxuyWEEEJcWyTAqqJFixbx4YcfcuzYMdzd3bn99tt54403aNSo5p6Uc6kq+9PS+SH+KLtPpWIps2Ox2bA7nJjQYtBo8VeMgAu/Eqif8wdhTRPwaVIAqKiAJddEwprmWArrE9DXgzyffI6cjGP9b9+QtzQNVXWdPZmqENLQnV59gri1nYnIEBVfDxtGXSI6rRMUKHTqOWDx4ajNi5RSf0qdfjhUfxTFl87+jZnYvC8m7eUH+gkhhBA3myuaB+tm9dJLLzF37lxatWrFoEGDOHnyJMuXL8fX15fdu3cTERFx3jFXOg9WSm4e72/byb60dCy2sy1WPjoTHqoW1epAKXXglmnFLTuNRg1OU69NLl6hFtCCYtRwJs+fBFsQuRqVwlNp5B5JI+tQBmWF1opzKApEd/GjW4wfHSKNNAksQ6dzotO50CpnW6rynAZSyjxIsHpxoKg+xY5AVMUHo9aTEHcfonzDuCOkDcFuPjX5FgtxSdfavHJCCHE5EmBdxv79+2nfvj0xMTH89NNPFSvRr169mrvvvpvBgwezZs2a84673A3B5nRyMO0Mqw/9wW+nU8ksLsHhcqGo4ObQoC2yY8iyok8txi2/BJ+wPMJ65xHWLhcMoBhA1aocSTFx7JgTy/E8TJZi9CUl+HiCn1nBy12Dp6cWvwYe+Aa6ERmswdtNRat1otWebck6bXfneJkHqXY3ilx6EvKDKCgLwmT0wdvgTgtzME29gugc0Jhwz4DafbOFuAgJsIQQ1xvpIryMefPmATBjxoyK4Argrrvuonfv3qxbt47U1FQaNGhw2bxsDiebjyXyn4QkDp3JIKfEgs3uwOV0oaoqOouDgKI8AvzzMDe2UK9vEYF+RQS5W3BTHGB1UJZbRlG6C6fFhdFho5+Hyoi2GgwdABVU3FC0OrQmPXo3HQY3DXqtiqI4QAGbquGEzY0TpR4cL/Uk3+5OkdUfJ544lUCa+jYkyjeM5ub6NPcOli5AIYQQohokwLqMbdu2odPp6Nmz53n7+vXrR2xsLFu3bmXUqFEXPP5wWgZrNm/n95OpnLFacKguFI0Ns3cxDesX0sg3l4bmXIIMBXhTgtFhQ+dwYlKdeOlV3FwqzjwVp0PF5QJVo6D+X0OSqiooigZFr0Vj1FGiGCnTGlDcdJShYHVpKbNpsKkaylxazpR5cKzAH4vdjJsSRLugNvRs0IgW3sH4GT1x0+plUkYhhBCiBkiAdQlOp5Njx44RHh5eqfWqXGRkJADx8fEXzWPZrnEEe1q5r5EVb60NL50DD72Kp1HF3ajgcqq4HCqcM13P2T5bBcqgtAyKSyGvUCW/0EWxQ4dNb8RuMqF6uaEL9sKiMWJx6XChgFNBKQOnU0NhiRmrzRub0wcVH1r5NOSh5k1p4xdKPZO3BFNCCCFELZEA6xIKCwtRVRU/P78L7vfx8QEgPz//onncX/8Enh6aC+5zlKk4XJCT7yI330VeMeRbNRQ7tFgwUKQYKdG7ofdxx8vfDc9mJvQ6LQoKWhS0Gg12hw69y4P6Tn88NT4EetQj0r8tkfVbYzQY/+pbIIQQQohqkADrEoqLiwEwGi8cqJRvt1qtF9wPkJqt4syHYpuGYqfu7J9qwoKJMo0bLoM7Hu5uuNc3YTKaMGj1BOgNuOmNmHQGTHoDBoMBk96El5sfngZf3HXeuGnNeOh88TWEoFFkMkUhhBDiWiIB1iWYTGdnJrfZbBfcX1ZWBpxdluNiuvXZVempJ6PReNGATQghhBA3BgmwLsFsNqPRaC7aBVi+3Ww2XzQPb29veaxcCCGEuMlceHCQAMBgMBAZGcnJkycvuGhsUlISAK1atbraRRNCCCHENUwCrMvo1asXNpuNHTt2nLfvP//5D4qi0L179/P2lXcflv/3eldWVsbMmTNvmPrAjVknuHHrJYQQ1xMJsC5j3LhxALz88suUlpZWbF+9ejU///wzQ4YMITQ09LzjbsQA67XXXrth6gM3Zp3gxq2XEEJcTyTAuoyuXbvy5JNPsmvXLqKionjhhRcYOXIk9913H0FBQbz77rtVzqt8Vvir9bo28vzss89qNf+rUYerXafayLMq56zt/Ou6TkIIcU1TxWW5XC71ww8/VNu0aaMajUY1JCREffDBB9WkpKSLHnPq1CkVUE+dOlWxrWXLlpXS1PbrmsyzoKBABdTmzZtft3X48+urVafarMOFXpfXq6CgoNbOV9t1+PPrC9VJCCGuZfIUYRUoisJTTz3FU089VeVj1P9bQ7uoqIjCwkLg7Mzw5f9/NV7XZJ43Qh3qqk5X4xznvv7zf2+kOqmyNr0Q4jqhqPKNVSuOHz9esZSOEKJmnDp16oJjHoUQ4lojAVYtcblcpKWl4eXlJWv+CfEXqapKUVERISEhaDQydFQIce2TAEsIIYQQoobJT0EhhBBCiBomAZYQQgghRA2TAEsIIYQQooZJgFUNKSkpKIpCeHh4XRelRsyaNQtFUXB3d7/owtbXu796zWbOnImiKCxYsKBmC1ZFp0+f5oUXXiAqKgqz2YyXlxdt2rRh4sSJHDp0qEbOsXLlSg4ePFgjeQkhxM1OAqybnKqqfP7553h4eFBaWsrixYvrukjiTxYuXEjTpk15++238fDwYNy4cTz++OOEhYXx2WefERUVxcsvv4zL5ar2OV566SXuvfdeMjMza7DkQghx85IA6yYXGxvL8ePH+fvf/47JZOKTTz6p6yKJc3zxxRc88sgjBAUFsWPHDnbu3Ml7773HO++8w/r160lISKBDhw7MmTOHSZMmVfs8Z86cqcFSCyGEkADrJrdw4UIA7r33Xu68807i4uL4+eef67hUAiArK4snnngCb29vfvrpJ7p163ZemoiICGJjYwkPD2fevHls2bKlDkoqhBDizyTAqiEul4t///vf9OnTB39/f/R6PYGBgQwaNIjt27dXSls+nmfPnj3MnTuXZs2aYTQaCQsL49lnn6W4uPiqlLmwsJCVK1cSEhJCVFQUI0aMAGD+/Pnnpe3duzcmk4ns7Gweeugh/Pz88PHxoV+/fmzdurVS2vLxTk899RSvvfYaPj4+eHt789JLL12VelVFeRljYmLO2xcbG4uiKIwaNaoOSvY/n3zyCSUlJUycOPGSqwJ4enoye/ZsAP71r39V2qeqKp999hldunTB29ubwMBA+vXrx+bNmyvSKIpS0TV82223ycS4QghRA2Qtwhry8MMP88UXX9CuXTtGjx6NTqfj999/54cffuDHH39k9+7dtG/fvtIxTzzxBHFxcdx3330MGTKEFStW8O6775KamsrSpUtrvczffPMNFouFiRMnoigKgwcPxsfHh5UrV5KVlUVgYGCl9C6Xi/79+5ORkcFDDz1Ebm4u3333HbfddhtfffUVw4cPr5T+u+++w2q1MmbMGHJycujatWut1+lGsmnTJgAGDRp02bRDhgzBZDLxww8/YLVaMZlMAAwbNozly5cTFhbGiBEj0Ol0fPPNN9xxxx0sWbKE4cOHM2PGDFavXs2BAwcYPXo0jRs3rtV6CSHETaGOFpm+riUnJ6uA2qhRI1VVVXXPnj0qoPbv3191Op2V0r744osqoD733HMV22bMmKECqr+/v5qcnFyxPTc3V/Xz81O1Wq2anp5e6/Xo3LmzCqj79++v2Pb444+rgPrmm29WSturVy8VUBs3bqxmZWVVbP/9999VDw8P1c/PTy0oKFBV9X/vD6D++OOPtV6PqvjzNSt/3b179/PSbt26VQXUBx98sGJb+TX77LPPrlaR1YCAABVQs7Ozq5S+efPmKqAmJiaqqqqqS5YsUQG1X79+amFhYUW6xMRE1dvbWw0KClLtdruqqqo6ZswYFVA3b95c8xURQoibkHQR1oD69evzxRdf8P7775+3Tlrfvn2Bs+Np/mzkyJGVpg3w9fUlJiYGp9NJcnJyrZb5jz/+YPfu3bRt25aoqKiK7WPGjAHg008/Rb3AKkqzZs0iICCg4nWHDh0YP348ubm5rF27tlJaHx8fbrvttlqqwY2voKAAALPZXKX0/v7+wP8+a1988QUA77zzDl5eXhXpIiMjee+993juueeuWne0EELcbKSLsAY0aNCA0aNH43K5OHLkCPHx8SQnJ/PHH38QGxsLgNPpPO+4Zs2anbfNx8cHAJvNVptFrhjc/udxRt26daNp06YkJCSwadMm7rjjjkr7+/Xrd15e3bt3591332Xv3r08+OCDFdsjIiJkPM9f4OfnR0ZGBhaLBW9v78umLyoqAqgIgPft24eHhwft2rU7L+24ceNqtrBCCCEqkRasGrJ48WKaNm1KmzZtuO+++3jllVc4cuQIHTt2BLhga1D5OJlzlQckF0pfUxwOB1999RUAL774IoqiVPpLSEgAzh/sbjAYCAoKOi+/8pv/nycpdXd3r4XS3zzKB7bHx8dfNq3NZiMhIQG9Xk9oaCgAOTk5eHl5SZArhBB1QFqwLiE9PZ0tW7bQqFGjSk+blU/o6ObmBsDq1asZO3YsERERfPPNN3Ts2JHGjRuj1WrZuHEj3333XZ2U/2LWrVtHRkYGzZo1o0+fPuftV1WVBQsWsHbtWlJTU2nQoAEAdrsdu92OXq+vlD4vLw/gvEHxdaGq16w86LjQ5JwlJSVXoaSXd88997Bz505WrFhB586dL5l2/fr1WK1Whg4dWhG4e3l5UVRUhKqq5wVZVqsVvV6PVquttfILIcTNTFqwLmHXrl2MGjWKJUuWVNpeHlCUd8WUP+L+73//m+HDh9O0adOKG9eRI0eA2m2RulLl3YOvvPIK8+fPP+/vk08+YcCAATidzkpLw6iqyu7du8/Lr3waii5dulydClxCVa+ZwWAA/tetdq7yFry6Vj4dxrx58y7ZimWxWHj55ZeBs0+mlouKiqKkpITDhw+fd8xLL72Em5sb27ZtA5BWLiGEqGESYF1Chw4dUBSFzZs3VxoTtWbNGoCKiR/LW0UyMjIqHX/48GHefPNN4Gzrz7UgIyODDRs24Onpyb333nvRdI899hgACxYsqDR+bOrUqZWCkt27d7NgwQIaNmzIgAEDaq/gVVTVa1avXj38/PyIi4sjMTGxIl1WVtZ5c0nVlcDAQObPn09JSQn9+/dn586d56U5efIkt99+O3FxcUyYMIHbb7+9Yl/5AwsvvPACFoulYntKSgpffPEFZrO5Iigub5W8Vj6nQghxvZMuwksIDw9n5MiRfP3113Ts2JEBAwZw/PhxVq1ahZ+fH5MnTwZg7NixLF26lHHjxrFhwwZCQkI4evQo69evrxi0npOTU4c1+Z/FixfjcDi4//77LzlGatCgQdSvX5/Tp0+zbt26iu0HDx4kKiqKQYMGkZ2dzcqVK9FqtSxatOiCY8qutqpeM61Wy4QJE5g9ezbdu3dn+PDh2O12vvvuO1q3bk1SUlId1+Ss+++/n2XLlvHwww/TvXt3YmJi6Ny5Mzqdjvj4eDZt2kRZWRnPPfdcxWSj5caMGcP333/P6tWriYqKYsCAAdhsNr799luKiopYv359RWAVFhYGwPTp0/nll1+YPn16xQ8HIYQQ1VCHU0RcF8rKytRXX31VjYiIUPV6vVqvXj11xIgRalJSUqV033//vdqlSxfVbDarZrNZbdeunfr888+rubm5amRkpGo0GtW8vDxVVS89p1L5fERbt26tlfq0bNlSBdTY2NjLpp06daoKqAMGDKiYB2vr1q3q/fffr3p5eal+fn7qPffcU2keLVW99BxTV0NVr5nD4VBnz56tNmnSRDUYDGp4eLj66quvqtnZ2dfEPFjnSk9PV1977TW1Y8eOqp+fn+rh4aG2bNlSnThxorp3796LHudwONR//vOfanR0tGoymVQPDw+1X79+513/nJwc9c4771Td3NxUs9msHjlypLarJIQQNzRFVa+hwUHimtW7d29+/vlnEhISaNKkSV0XRwghhLimyRgsIYQQQogaJgGWEEIIIUQNkwBLCCGEEKKGyRgsIYQQQogaJi1YQgghhBA1TAIsIYQQQogaJgHW/ykuLubll1+mRYsWmEwmvL296dWrF6tXrz4vbVZWFk8//TQRERG4ubnRokUL3nrrLRwOx2XPM3/+fBRFqTR7+LksFgtTp04lMjISg8FAYGAgw4YN4+jRo3+1ikIIIYS4SmQMFmfXo4uJieHgwYN06NCBXr16UVBQwIoVKygoKGD27NlMnToVOLumXffu3YmPj+eee+6hSZMmbNq0iX379nHvvfdecmHnn376icGDB1NaWnrB+aTsdju9evVi165dtG/fnr59+3LixAlWrlyJh4cH27dvp127drX6XgghhBCiBtTlLKfXildeeUUF1AkTJqgul6ti++nTp9Xg4GBVq9WqCQkJqqqq6uTJk1VA/eijjyrSORwO9Z577lEBdcWKFRc8x8cff6wajUYVUIGK/M61cOFCFVDvvvtu1el0Vmz/5ptvVEDt169fTVVZCCGEELVIugiBZcuWoSgKc+bMQVGUiu0NGjRg4sSJOJ1O1q9fj81m47PPPqNhw4aMHz++Ip1Wq+Wdd94BznYBnisuLo4ePXowceJEGjZsSNOmTS9ajl9//RU4u7ahRvO/SzN8+HDMZvMFF/sVQgghxLVHAixg8uTJ/OMf/6hYmPlcRqMRONuNuHfvXiwWC3369KkUAMHZRYYjIyP55ZdfcDqdFdt//PFHfv31VyZPnsy+ffsICQm5aDkCAgIASElJqbQ9Ly+PkpISAgMDq1lDIYQQQlxNurouwLXgiSeeuOB2VVVZuXIlAO3atSMuLg6AyMjIC6aPjIwkKSmJ5OTkivFVffr0ISEhgUaNGl22HGPGjOH999/n9ddfJzw8nH79+nHq1CmeeuopHA4Hzz//fHWqJ4QQQoirTFqwLuHjjz/m119/pXHjxgwYMID8/HwA/Pz8Lpi+vAWsPB1AVFRUlYIrgKZNm7J9+3aCgoIYOnQonp6etGzZkl9++YVFixbx1FNP/ZXqCCGEEOIqkRasi1i2bBmTJk1Cp9OxePFi9Ho9xcXFwP+6Df+sfLvVaq3WOfPz83n55Zf5448/6NmzJ506deL06dOsXr2a559/nuDgYO64447qVUgIIYQQV40EWBfw8ccf89RTT6EoCl988QUxMTEAmEwmAGw22wWPKysrA8DT07Na5x09ejQbNmzgnXfeYcqUKRXb//jjD7p3785dd91FQkICoaGh1cpfCCGEEFeHdBGew+Vy8eyzz/LEE09gMBhYvnw5I0aMqNhf3jV4bhfgucq3m83mKz53Wloa69ato2XLlpWCK4BWrVrx4osvYrVa+fLLL684byGEEEJcXdKC9X9sNhsjRoxg5cqV+Pn58f3331e0XJVr2bIlAElJSRfMIykpCQ8PD8LCwq74/CdPnqx0jj9r06YNACdOnLjivIUQQghxdUkLFmdbru6//35WrlxJREQEO3fuPC+4AujQoQNeXl7Exsbicrkq7UtJSSEpKYmuXbui1WqvuAz169cHuOiSOMeOHQO45DQPQgghhLg2SIAFzJkzhzVr1hAWFsa2bdto3rz5BdOZTCZGjhxJcnIyH3zwQcV2p9PJs88+C8CTTz5ZrTKEh4fTtWtXjhw5wkcffVRpX3JyMnPnzkWr1TJs2LBq5S+EEEKIq+emX4swLy+Phg0bUlJSwtChQ4mOjr5gup49e9K3b1+ys7Pp1KkTKSkpDB48mFatWrF582b27t3LAw88wNKlSyvNBv9nvXv35ueff77gWoRHjx6lZ8+eZGZm0rt3bzp37kx6ejorV67EYrHwz3/+k6effromqy+EEEKIWnDTB1ibNm2q0tQH06ZN4x//+AcA6enpvPrqq6xbt46CggIiIiJ4+OGHmTx5MgaD4ZL5XCrAgrOD3d944w1++OEHUlNT8fT0pEuXLjz33HP069evepUUQgghxFV10wdYQgghhBA1TcZgCSGEEELUMAmwhBBCCCFqmARYQgghhBA1TAIsIYQQQogaJgGWEEIIIUQNkwBLCCGEEKKGSYAlhBBCCFHDJMASQgghhKhhEmAJIYQQQtQwCbCEEEIIIWqYBFhCCCGEEDVMAiwhhBBCiBr2/wEingYDT0bWBAAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Visualize and analyze the results.\n", - "viridis = cm.get_cmap('viridis', len(pet_df.columns))\n", - "colors = [viridis(i) for i in range(0, len(pet_df.columns))]\n", - "colors[-2] = \"k\"\n", - "\n", - "fig, axs = plt.subplots(2, 2, figsize=(6,5), layout=\"constrained\")\n", - "axs = axs.flatten()\n", - "axs[3].axis(\"off\")\n", - "\n", - "pet_df.plot(color=colors, legend=False, ax=axs[0], alpha=0.8, drawstyle=\"steps-mid\")\n", - "axs[0].xaxis.set_major_locator(mdates.MonthLocator(interval=3))\n", - "axs[0].set_ylabel(\"PET [mm/day]\")\n", - "axs[0].set_xlabel(\"\")\n", - "axs[0].set_xticklabels([])\n", - "\n", - "handles = pet_df.cumsum().plot(color=colors, legend=False, ax=axs[2], alpha=0.8)\n", - "axs[2].set_ylabel(\"Cum. PET [mm]\")\n", - "axs[2].xaxis.set_major_locator(mdates.MonthLocator(interval=3))\n", - "axs[2].set_xlabel(\"\")\n", - "\n", - "sns.boxplot(pet_df, ax=axs[1], palette=colors)\n", - "axs[1].set_ylabel(\"PET [mm/day]\")\n", - "axs[1].set_xlabel(\"\")\n", - "\n", - "axs[1].set_xticklabels([])\n", - "\n", - "for i, letter in enumerate([\"a\", \"b\", \"c\"]):\n", - " axs[i].text(0.05, 0.9, \"({})\".format(letter), transform=axs[i].transAxes, fontsize=12)\n", - "\n", - "plt.tight_layout()\n", - "\n", - "axs[2].legend(loc=(1.05,0.1), ncol=2, bbox_transform=axs[0].transAxes, fontsize=8)\n", - "#fig.savefig(\"figure1.png\", dpi=600, bbox_inches=\"tight\")" - ] - }, - { - "cell_type": "markdown", - "id": "bf7f5fd0", - "metadata": { - "tags": [] - }, - "source": [ - "# Example 2: Estimate PET for gridded data\n", - "\n", - "Data source: E-OBS https://www.ecad.eu/" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "d31888e0", - "metadata": {}, - "outputs": [], - "source": [ - "# Load E-OBS data\n", - "wind = xr.open_dataset(\"data//example_0//fg_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", - " engine=\"netcdf4\")[\"fg\"]\n", - "tmax = xr.open_dataset(\"data//example_0//tx_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", - " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", - " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"tx\"]\n", - "tmin = xr.open_dataset(\"data//example_0//tn_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", - " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", - " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"tn\"]\n", - "tmean = xr.open_dataset(\"data//example_0//tg_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", - " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", - " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"tg\"]\n", - "rs = xr.open_dataset(\"data//example_0//qq_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", - " engine=\"netcdf4\").sel(lon=slice(wind.longitude.min(), wind.longitude.max()), \n", - " lat=slice(wind.latitude.min(), wind.latitude.max()))\n", - "rs = rs.rename_dims({\"lon\":\"longitude\", \n", - " \"lat\":\"latitude\"}).rename({\"lon\":\"longitude\", \n", - " \"lat\":\"latitude\"}).sel(ensemble=10)[\"qq\"] * 86400 / 1000000 # concert to [MJ/m2day]\n", - "rh = xr.open_dataset(\"data//example_0//hu_ens_mean_0.25deg_reg_2018_v25.0e.nc\", \n", - " engine=\"netcdf4\").sel(lon=slice(wind.longitude.min(), wind.longitude.max()), \n", - " lat=slice(wind.latitude.min(), wind.latitude.max()))\n", - "rh = rh.rename_dims({\"lon\":\"longitude\", \"lat\":\"latitude\"}).rename({\"lon\":\"longitude\", \"lat\":\"latitude\"})[\"hu\"]\n", - "elevation = xr.open_dataset(\"data//example_0//elev_ens_0.25deg_reg_v25.0e.nc\", \n", - " engine=\"netcdf4\").sel(longitude=slice(wind.longitude.min(), wind.longitude.max()), \n", - " latitude=slice(wind.latitude.min(), wind.latitude.max()))[\"elevation\"].fillna(0)\n", - "lat = tmean.latitude * np.pi / 180\n", - "lat = lat.expand_dims(dim={\"longitude\":tmean.longitude}, axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "e54b4c53", - "metadata": {}, - "outputs": [], - "source": [ - "# Estimate potential Evapotranspiration\n", - "pm_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", - "makkink = pyet.makkink(tmean, rs, elevation=elevation)\n", - "hargreaves = pyet.hargreaves(tmean, tmax, tmin, lat=lat)" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "9e2d1d81", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vmax, vmin = 7, 0\n", - "fig, axs = plt.subplots(ncols=3, nrows=3, figsize=(16, 8), sharey=True, sharex=True)\n", - "\n", - "for date, i in zip([\"2018-6-6\", \"2018-6-7\", \"2018-6-8\"],[0,1,2]):\n", - " pm_fao56.sel(time=date).plot(ax=axs[0,i],vmax=vmax, vmin=vmin, add_colorbar=False)\n", - " makkink.sel(time=date).plot(ax=axs[1,i],vmax=vmax, vmin=vmin, add_colorbar=False)\n", - " im = hargreaves.sel(time=date).plot(ax=axs[2,i],vmax=vmax, vmin=vmin, add_colorbar=False)\n", - "\n", - "for method, date, i in zip([\"pm_fao56\", \"makkink\", \"hargreaves\"], [\"2018-6-6\", \"2018-6-7\", \"2018-6-8\"],[0,1,2]):\n", - " for j in (0,1,2):\n", - " axs[i, j].set_ylabel(\"\")\n", - " axs[i, j].set_xlabel(\"\")\n", - " axs[i, j].set_title(\"\")\n", - " axs[2,j].set_xlabel(\"Lon. [°E]\")\n", - " axs[i, 0].set_ylabel(method + \"\\n\\nLat. [°N]\")\n", - " axs[0,i].set_title(\"date=\"+date)\n", - "\n", - "cbar_ax = fig.add_axes([0.91, 0.11, 0.01, 0.77])\n", - "cbar = fig.colorbar(im, cax=cbar_ax)\n", - "cbar.set_label(\"PET [mm/day]\", labelpad=10)\n", - "plt.subplots_adjust(hspace=0.05, wspace=0.01)\n", - "#fig.savefig(\"figure2.png\", dpi=600, bbox_inches=\"tight\")" - ] - }, - { - "cell_type": "markdown", - "id": "84918f2b", - "metadata": { - "tags": [] - }, - "source": [ - "# Example 3: Calibration of PET models\n", - "\n", - "Data source: ZAMG - https://data.hub.zamg.ac.at" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "93b91863", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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stationstrahlrelttmaxtminvv
time
2000-01-0116412300.080.0-2.70.5-5.81.0
2000-01-0216412250.086.00.22.5-2.11.0
2000-01-0316412598.086.00.63.6-2.41.0
2000-01-0416412619.083.0-0.54.5-5.51.0
2000-01-0516412463.084.0-0.15.4-5.51.0
\n", - "
" - ], - "text/plain": [ - " station strahl rel t tmax tmin vv\n", - "time \n", - "2000-01-01 16412 300.0 80.0 -2.7 0.5 -5.8 1.0\n", - "2000-01-02 16412 250.0 86.0 0.2 2.5 -2.1 1.0\n", - "2000-01-03 16412 598.0 86.0 0.6 3.6 -2.4 1.0\n", - "2000-01-04 16412 619.0 83.0 -0.5 4.5 -5.5 1.0\n", - "2000-01-05 16412 463.0 84.0 -0.1 5.4 -5.5 1.0" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Load station data\n", - "data_16412 = pd.read_csv('data//example_1//klima_daily.csv', index_col=1, parse_dates=True)\n", - "data_16412.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "d37c6693", - "metadata": {}, - "outputs": [], - "source": [ - "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", - "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \n", - " \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", - " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", - "\n", - "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", - "\n", - "lat = 47.077778 * np.pi / 180 # Latitude of the meteorological station, converting from degrees to radians\n", - "elevation = 367 # meters above sea-level\n", - "\n", - "# Estimate evaporation with all different methods and create a dataframe\n", - "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax,\n", - " tmin=tmin, rh=rh)" - ] - }, - { - "cell_type": "markdown", - "id": "a6f6cd92-16c0-446f-9343-d26671613614", - "metadata": {}, - "source": [ - "## 3.1 Calibrate alternative temperature models to Penman-Monteith" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "68610698", - "metadata": {}, - "outputs": [], - "source": [ - "# Calibrate alternative temperature models to Penman-Monteith\n", - "methods = [\"oudin\", \"hargreaves\", \"mcguinness_bordne\", \"hamon\", \"blaney_criddle\"]\n", - "\n", - "# Define initial values for calibration for each method\n", - "params = [[100, 5], [0.0135], [0.0147], [1], [-1.55, 0.96]]\n", - "\n", - "# Define input for each method\n", - "input2 = ([tmean, lat], [tmean, tmax, tmin, lat], [tmean, lat],\n", - " [tmean, lat], [tmean, lat])\n", - "\n", - "# Define function to simulate the models and use required input\n", - "def simulate(params, method, input1): \n", - " input1_1 = input1.copy()\n", - " method = getattr(pyet, method)\n", - " for par in params:\n", - " input1_1.append(par)\n", - " return method(*input1_1)\n", - "\n", - "# Define function to estimate residuals \n", - "def residuals(params, info):\n", - " method, input1, obs = info\n", - " sim = simulate(params, method, input1)\n", - " return sim - obs" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "f0aadada", - "metadata": {}, - "outputs": [], - "source": [ - "# Calibrate the models to Penman-Monteith\n", - "obs = pet_df[\"FAO-56\"]\n", - "sollutions2 = []\n", - "for i in np.arange(0,len(methods)):\n", - " res_1 = least_squares(residuals, params[i], args=[[methods[i], input2[i], obs]])\n", - " sollutions2.append(res_1.x)" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "f7e8589e", - "metadata": {}, - "outputs": [], - "source": [ - "# Create DataFrame with PET estimated with default (params) and calibrated parameters(sollutions2)\n", - "pet_df_def = pd.DataFrame()\n", - "pet_df_cali = pd.DataFrame()\n", - "for i in np.arange(0, len(methods)):\n", - " pet_df_def[methods[i]] = simulate(params[i], methods[i], input2[i])\n", - " pet_df_cali[methods[i]] = simulate(sollutions2[i], methods[i], input2[i])" - ] - }, - { - "cell_type": "markdown", - "id": "d156c21f", - "metadata": { - "tags": [] - }, - "source": [ - "## 3.2 Hindcasting PET for Graz, Austria" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "1ebebb9b", - "metadata": {}, - "outputs": [], - "source": [ - "# Load Spartacus dataset\n", - "spartacus = xr.open_dataset(\"data//example_0//spartacus-daily_19610101T0000_20211231T0000.nc\", \n", - " engine=\"netcdf4\")\n", - "spartacus_cali = spartacus.copy()" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "c794bad9", - "metadata": {}, - "outputs": [], - "source": [ - "# Define new input\n", - "tmean_spartacus = (spartacus[\"Tx\"] + spartacus[\"Tn\"]) / 2\n", - "tmax_spartacus = spartacus[\"Tx\"]\n", - "tmin_spartacus = spartacus[\"Tn\"]\n", - "lat_spartacus = spartacus.lat * np.pi / 180 # from degrees to radians\n", - "input_spartacus = ([tmean_spartacus, lat_spartacus], \n", - " [tmean_spartacus, tmax_spartacus, tmin_spartacus, lat_spartacus], \n", - " [tmean_spartacus, lat_spartacus],\n", - " [tmean_spartacus, lat_spartacus], [tmean_spartacus, lat_spartacus])" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "2659c0bc", - "metadata": {}, - "outputs": [], - "source": [ - "# Estimate PET and add it to the xarray.Dataset\n", - "for i in np.arange(0,len(methods)):\n", - " spartacus[methods[i]] = simulate(params[i], methods[i], input_spartacus[i])\n", - " spartacus_cali[methods[i]] = simulate(sollutions2[i], methods[i], input_spartacus[i])" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "8c8299db", - "metadata": {}, - "outputs": [], - "source": [ - "# Create DataFrame with PET estimated with default (params) and calibrated (sollutions2) models\n", - "df_def = spartacus.to_dataframe().reset_index(level=[1,1]).drop(columns=[\"y\", \"Tn\", \"Tx\", \"lambert_conformal_conic\", \"lon\", \"lat\"])\n", - "df_cali = spartacus_cali.to_dataframe().reset_index(level=[1,1]).drop(columns=[\"y\", \"Tn\", \"Tx\", \"lambert_conformal_conic\", \"lon\", \"lat\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "11a79765", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - }, - { - 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "figw_1c = 8.5 # maximum width for 1 column\n", - "figw_2c = 17.5 # maximum width for 2 columns\n", - "\n", - "fig, axs = plt.subplots(ncols=6, nrows=2, figsize=(figw_2c, 5), dpi=300)\n", - "for i in np.arange(0, len(methods)):\n", - " axs[0,i] = scatter_1(axs[0,i], obs, simulate(params[i], methods[i], input2[i]), label=f\"{methods[i]} - default\")\n", - " axs[1,i] = scatter_1(axs[1,i], obs, simulate(sollutions2[i], methods[i], input2[i]), label=f\"{methods[i]} - calibrated\")\n", - " axs[0, i].set_xticklabels([])\n", - " axs[1, i].set_xlabel(r\"$PET_{sim}$ [mm/d]\")\n", - " axs[1, i].set_xticklabels((0,2,4,6,8,\"\"))\n", - "for col in (1, 2, 3, 4):\n", - " axs[0, col].set_yticklabels([])\n", - " axs[1, col].set_yticklabels([])\n", - "plt.subplots_adjust(wspace=0.1, hspace=0.1)\n", - "for row in (0, 1):\n", - " axs[row, 0].set_ylabel(r\"$PET_{FAO-56}$ [mm/d]\")\n", - "\n", - "viridis = cm.get_cmap('viridis', len(df_def.columns))\n", - "colors = [viridis(i) for i in range(0, len(df_def.columns))]\n", - "df_def.resample(\"y\").sum().plot(ax=axs[0, 5], legend=False, color=colors)\n", - "df_cali.resample(\"y\").sum().plot(ax=axs[1, 5], legend=False, color=colors)\n", - "axs[0,5].axvline(pd.Timestamp(\"2000-1-1\"), color=\"k\", linestyle=\"--\", lw=1)\n", - "axs[1,5].axvline(pd.Timestamp(\"2000-1-1\"), color=\"k\", linestyle=\"--\", lw=1)\n", - "#pet_df_def.cumsum().plot(ax=axs[0, 5], legend=False)\n", - "#obs.cumsum().plot(ax=axs[0,5], label=\"pm_fao56$ [mm/d]\", color=\"k\", linestyle=\"--\", )\n", - "#obs.cumsum().plot(ax=axs[1,5], label=\"pm_fao56\", color=\"k\", linestyle=\"--\", )\n", - "#pet_df_cali.cumsum().plot(ax=axs[1, 5], legend=False)\n", - "for i in (0,1):\n", - " axs[i,5].yaxis.tick_right()\n", - " axs[i,5].yaxis.set_label_position(\"right\")\n", - " axs[i,5].set_xticks((pd.Timestamp(\"2016-1-1\"), pd.Timestamp(\"2018-1-1\"), pd.Timestamp(\"2020-1-1\")))\n", - " axs[i,5].set_ylim(600, 1200)\n", - " axs[i,5].set_ylabel(\"Cumulative PET [mm]\", fontsize=14)\n", - "axs[0,5].set_xticklabels(\"\");\n", - "axs[1,5].set_xticks([\"1960-1-1\", \"1980-1-1\", \"2000-1-1\", \"2021-1-1\"]);\n", - "axs[1,5].set_xticklabels([\"1960\", \"1980\", \"2000\", \"2021\"]);\n", - "axs[0,5].set_xlabel(\"\");\n", - "plt.subplots_adjust(hspace=0.05, wspace=0.05)\n", - "axs[1,5].set_yticklabels([\"\",800,1000,\"\"])\n", - "axs[0,5].legend(loc=(-3.65,1.05), ncol=7, bbox_transform=axs[1,5].transAxes)\n", - "#fig.savefig(\"figure3.png\", dpi=600, bbox_inches=\"tight\")" - ] - }, - { - "cell_type": "markdown", - "id": "6f46ea03", - "metadata": {}, - "source": [ - "# 3.3 Forecasting for Graz Austria" - ] - }, - { - "cell_type": "markdown", - "id": "ba18d232", - "metadata": {}, - "source": [ - "$$ PET_{CO_2} = f_{CO_2} PET $$\n", - "\n", - "Data source temperature: https://climate-impact-explorer.climateanalytics.org/impacts/\n", - "\n", - "Data source $CO_2$ levels: https://tntcat.iiasa.ac.at/RcpDb/" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "a85f2efd", - "metadata": {}, - "outputs": [], - "source": [ - "# Load increase in temperature for each RCP scenario\n", - "rcp_temp = pd.read_csv(\"data//example_0//tasAdjust_AUT_AT.ST_area_annual.csv\", \n", - " skiprows=4, index_col=\"year\").loc[\"2020\":,:]\n", - "rcp_temp = rcp_temp.loc[:, [\"RCP2.6 median\", \"RCP4.5 median\", \"RCP6.0 median\", \"RCP8.5 median\"]]\n", - "rcp_temp.columns = [\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "dd58ca5e", - "metadata": {}, - "outputs": [], - "source": [ - "# Load CO2 data for each RCP scenario\n", - "rcp_co2 = pd.DataFrame()\n", - "rcp_co2[\"rcp_26\"] = pd.read_csv(\"data//example_0//co2_conc//RCP3PD_MIDYR_CONC.dat\", skiprows=38, \n", - " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]\n", - "rcp_co2[\"rcp_45\"] = pd.read_csv(\"data//example_0//co2_conc//RCP45_MIDYR_CONC.dat\", skiprows=38, \n", - " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]\n", - "rcp_co2[\"rcp_60\"] = pd.read_csv(\"data//example_0//co2_conc//RCP6_MIDYR_CONC.dat\", skiprows=38, \n", - " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]\n", - "rcp_co2[\"rcp_85\"] = pd.read_csv(\"data//example_0//co2_conc//RCP85_MIDYR_CONC.dat\", skiprows=38, \n", - " delim_whitespace=True, index_col=\"YEARS\").loc[\"2020\":\"2100\", \"CO2\"]" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "7c1bf22a", - "metadata": {}, - "outputs": [], - "source": [ - "# RCP scenario 6.0\n", - "co2_600 = 600\n", - "pet_300 = pyet.pm(tmean, wind, rs=rs, elevation=elevation, lat=lat, \n", - " tmax=tmax, tmin=tmin, rh=rh)\n", - "pet_600 = pyet.pm(tmean, wind, rs=rs, elevation=elevation, lat=lat, \n", - " tmax=tmax, tmin=tmin, rh=rh, co2=co2_600)" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "3f14c72c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([-0.00015543])" - ] - }, - "execution_count": 55, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Compute the sensitivity of PET to CO2\n", - "def residuals_co2(S_CO2, PETco2, PETamb, co2):\n", - " fco2 = (1+S_CO2*(co2-300))\n", - " return PETco2 - PETamb * fco2\n", - "\n", - "res1 = least_squares(residuals_co2, [0.02], args=[pet_600, pet_300, 600])\n", - "res1.x" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "ea92559e", - "metadata": {}, - "outputs": [], - "source": [ - "# Define input for each method\n", - "inputamb = ([tmean, lat], [tmean, tmax, tmin, lat], [tmean, lat],\n", - " [tmean, lat], [tmean, lat])" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "a45ef088", - "metadata": {}, - "outputs": [], - "source": [ - "# Define function for input\n", - "def input_rcp(tincrease):\n", - " return ([tmean+tincrease, lat], [tmean+tincrease, tmax+tincrease, tmin+tincrease, lat], [tmean+tincrease, lat],\n", - " [tmean+tincrease, lat], [tmean+tincrease, lat])" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "0a3a04ed", - "metadata": {}, - "outputs": [], - "source": [ - "# Compute PET for each year for each RCP scenario with 5-95 percentile\n", - "dpet_rcp_et = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", - "dpet_rcp_et_5th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", - "dpet_rcp_et_95th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", - "dpet_rcp_etco2 = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", - "dpet_rcp_etco2_5th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", - "dpet_rcp_etco2_95th = pd.DataFrame(index=rcp_temp.index, columns=[\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"])\n", - "for year in rcp_temp.index:\n", - " for rcp in [\"rcp_26\", \"rcp_45\", \"rcp_60\", \"rcp_85\"]:\n", - " df_rcp_et = pd.DataFrame()\n", - " df_rcp_etco2 = pd.DataFrame()\n", - " for i in np.arange(0, len(methods)):\n", - " input1 = input_rcp(rcp_temp.loc[year, rcp])\n", - " df_rcp_et[methods[i]] = simulate(sollutions2[i], methods[i], input1[i])\n", - " df_rcp_etco2[methods[i]] = simulate(sollutions2[i], methods[i], \n", - " input1[i]) * (1+res1.x*(rcp_co2.loc[year, rcp]-300))\n", - " dpet_rcp_et.loc[year, rcp] = df_rcp_et.resample(\"y\").mean().mean().mean()\n", - " dpet_rcp_et_5th.loc[year, rcp] = df_rcp_et.resample(\"y\").mean().mean().quantile(0.05)\n", - " dpet_rcp_et_95th.loc[year, rcp] = df_rcp_et.resample(\"y\").mean().mean().quantile(0.95)\n", - " dpet_rcp_etco2.loc[year, rcp] = df_rcp_etco2.resample(\"y\").mean().mean().mean()\n", - " dpet_rcp_etco2_5th.loc[year, rcp] = df_rcp_etco2.resample(\"y\").mean().mean().quantile(0.05)\n", - " dpet_rcp_etco2_95th.loc[year, rcp] = df_rcp_etco2.resample(\"y\").mean().mean().quantile(0.95)" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "76d45437", - "metadata": {}, - "outputs": [], - "source": [ - "dpet_rcp_et = dpet_rcp_et.apply(pd.to_numeric)\n", - "dpet_rcp_et_5th = dpet_rcp_et_5th.apply(pd.to_numeric)\n", - "dpet_rcp_et_95th = dpet_rcp_et_95th.apply(pd.to_numeric)\n", - "dpet_rcp_etco2 = dpet_rcp_etco2.apply(pd.to_numeric)\n", - "dpet_rcp_etco2_5th = dpet_rcp_etco2_5th.apply(pd.to_numeric)\n", - "dpet_rcp_etco2_95th = dpet_rcp_etco2_95th.apply(pd.to_numeric)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "8c97280e", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(2,2, figsize=(6, 5), constrained_layout=True, sharex=True)\n", - "axs = axs.flatten()\n", - "viridis = cm.get_cmap('viridis', len(rcp_temp.columns))\n", - "colors = [viridis(i) for i in range(0, len(rcp_temp.columns))]\n", - "\n", - "for col, rcp, name in zip(colors, rcp_temp.columns, [\"RCP 2.6\", \"RCP 4.5\", \"RCP 6.0\", \"RCP 8.5\"]):\n", - " axs[2].plot(dpet_rcp_et.loc[:, rcp]-dpet_rcp_et.loc[2020, rcp], c=col);\n", - " axs[2].fill_between(dpet_rcp_et.index, dpet_rcp_et_5th[rcp]-dpet_rcp_et.loc[2020, rcp], \n", - " dpet_rcp_et_95th[rcp]-dpet_rcp_et.loc[2020, rcp], color=col, alpha=0.2)\n", - " axs[3].fill_between(dpet_rcp_et.index, dpet_rcp_etco2_5th[rcp]-dpet_rcp_etco2.loc[2020, rcp], \n", - " dpet_rcp_etco2_95th[rcp]-dpet_rcp_etco2.loc[2020, rcp], color=col, alpha=0.2)\n", - " axs[3].plot(dpet_rcp_etco2.loc[:, rcp]-dpet_rcp_etco2.loc[2020, rcp], c=col);\n", - " axs[1].plot(rcp_co2[rcp], c=col)\n", - " axs[0].plot(rcp_temp[rcp], c=col, label=name)\n", - "\n", - "axs[0].set_ylabel(r\"$\\Delta$T [°C]\")\n", - "axs[0].legend()\n", - "\n", - "axs[1].set_ylabel(\"$CO_2$ [ppm]]\")\n", - "\n", - "axs[2].set_ylim(0, 0.79)\n", - "axs[2].set_ylabel(\"$\\Delta$PET [mm/day]\")\n", - "\n", - "axs[3].set_ylim(0, 0.79)\n", - "#axs[3].set_xlim(\"2020\", \"2100\")\n", - "axs[2].set_ylabel(\"$\\Delta$PET [mm/day]\")\n", - "\n", - "axs[2].text(2025, 0.7, \"T+\", fontsize=14)\n", - "axs[3].text(2025, 0.7, \"T + $CO_2$+\", fontsize=14)\n", - "\n", - "for i, letter in enumerate([\"a\", \"b\", \"c\", \"d\"]):\n", - " axs[i].text(0.85, 0.9, \"({})\".format(letter), transform=axs[i].transAxes, fontsize=12)\n", - " axs[i].tick_params(axis='both', which='major', labelsize=13)\n", - "\n", - "#fig.savefig(\"figure4.png\", dpi=600, bbox_inches=\"tight\")" - ] - }, - { - "cell_type": "markdown", - "id": "abfb2272", - "metadata": {}, - "source": [ - "# Code example in paper" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "b7d21bf4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 61, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# 1. Import needed Python packages\n", - "import numpy as np\n", - "import pandas as pd\n", - "\n", - "# 2. Reading meteorological data\n", - "meteo = pd.read_csv(\"data//example_0//0_example_meteo.csv\", index_col=0, parse_dates=True)\n", - "\n", - "# 3. Determining the necessary input data\n", - "tmean, tmax, tmin, rh, rs, wind, pet_knmi = (meteo[col] for col in meteo.columns)\n", - "lat = 0.91 # define latitude [radians]\n", - "elev = 4 # define elevation [meters above sea-level]\n", - "\n", - "# 4. Estimate PET (all methods) and save the results in a Pandas.DataFrame\n", - "pet_df = pyet.calculate_all(tmean, wind, rs, elev, lat, tmax, tmin, rh)\n", - " \n", - "# (4. Estimate potential evaporation - Example with one method)\n", - "pyet_makkink = pyet.makkink(tmean, rs, elevation=elev)\n", - "\n", - "# 5. Plot PET \n", - "pet_df.plot() # daily PET [mm/day]\n", - "pet_df.boxplot() # boxplot PET[mm/day]\n", - "pet_df.cumsum().plot() # cummulative PET [mm]\n", - "plt.scatter(pyet_makkink, pet_knmi) # plot Makkink pyet vs KNMI" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "e0c2479f", - "metadata": {}, - "outputs": [], - "source": [ - "# 2. Reading meteorological data\n", - "meteo = pd.read_csv(\"data//example_0//0_example_meteo.csv\", index_col=0, parse_dates=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "cb4b5ee1", - "metadata": {}, - "outputs": [], - "source": [ - "# 3. Determining the necessary input data\n", - "tmean, tmax, tmin, rh, rs, wind, pet_knmi = (meteo[col] for col in meteo.columns)\n", - "lat = 0.91 # define latitude [radians]\n", - "elevation = 4 # define elevation [meters above sea-level]" - ] - }, - { - "cell_type": "markdown", - "id": "13bae9c9", - "metadata": { - "tags": [] - }, - "source": [ - "Now that we have defined the input data, we can estimate potential evaporation with different estimation methods. " - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "id": "54f684ea", - "metadata": {}, - "outputs": [], - "source": [ - "# 4. Estimate potential evaporation (with all available methods) and save the results in a Pandas.DataFrame\n", - "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax, tmin, rh)" - ] - }, - { - "cell_type": "code", - "execution_count": 65, - "id": "2c8652d0", - "metadata": {}, - "outputs": [], - "source": [ - "# 4. Estimate PE and save the results in a xarray.DataArray\n", - "pe_pm_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, \n", - " lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", - "pe_makkink = pyet.makkink(tmean, rs, elevation=elevation)\n", - "pe_pt = pyet.priestley_taylor(tmean, rs=rs, elevation=elevation, \n", - " lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", - "pe_hamon = pyet.hamon(tmean, lat=lat) \n", - "pe_blaney_criddle = pyet.blaney_criddle(tmean, lat)\n", - "pe_hargreaves = pyet.hargreaves(tmean, tmax, tmin, lat=lat)" - ] - }, - { - "cell_type": "markdown", - "id": "d43d1f5e-0bbc-43f9-ac94-6f952278245e", - "metadata": {}, - "source": [ - "# Acknowledgements" - ] - }, - { - "cell_type": "markdown", - "id": "49ac81b2-c7f8-4670-b8a2-2a4f64368903", - "metadata": {}, - "source": [ - "We acknowledge the ZAMG dataset (https://data.hub.zamg.ac.at), KNMI dataset (https://www.knmi.nl/home), and the E-OBS dataset from the EU-FP6 project UERRA (http://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA&D project (https://www.ecad.eu). " - ] - }, - { - "cell_type": "markdown", - "id": "e69f71ff-fa2d-449a-9321-944acd4248b4", - "metadata": {}, - "source": [ - "# Literature\n", - "\n", - "Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome, 300(9), D05109.\n", - "\n", - "Guo, D., Westra, S., & Maier, H. R. (2016). An R package for modelling actual, potential and reference evapotranspiration. Environmental Modelling & Software, 78, 216-224.\n", - "\n", - "McMahon, T. A., Peel, M. C., Lowe, L., Srikanthan, R., & McVicar, T. R. (2013). Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences, 17(4), 1331-1363.\n", - "\n", - "Penman, H. L. (1948). Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 193(1032), 120-145.\n", - "\n", - "Schrödter, H. (1985). Hinweise Für den Einsatz Anwendungsorientierter Bestimmungsverfahren. In: Verdunstung. Hochschultext. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-70434-5_8" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/01_example_zamg.ipynb b/examples/01_example_zamg.ipynb deleted file mode 100644 index dd152b7..0000000 --- a/examples/01_example_zamg.ipynb +++ /dev/null @@ -1,402 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "999bc8b7-804c-4301-b8c7-5077a38dc06f", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "# 1. Potential Evapotranspiration from ZAMG data\n", - "*A. Kokimova, November 2021, University of Graz*\n", - "\n", - "Data source: ZAMG - https://data.hub.zamg.ac.at\n", - "\n", - "What is done:\n", - "\n", - "- load the station data from ZAMG\n", - "- estimate potential evapotranspiration\n", - "- plot and store results" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "7a2ae568-3c3b-44f5-8b82-ab5a99d35d2d", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python version: 3.9.13 (main, Oct 13 2022, 21:23:06) [MSC v.1916 64 bit (AMD64)]\n", - "Numpy version: 1.21.5\n", - "Pandas version: 1.4.4\n", - "Pyet version: 1.2.2b\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pyet\n", - "pyet.show_versions()" - ] - }, - { - "cell_type": "markdown", - "id": "da6f3e98-0073-4db9-b763-03beb2611e78", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "## Loading daily data from ZAMG (Messstationen Tagesdaten)\n", - "\n", - "station: Graz Universität 16412\n", - "\n", - "Selected variables:\n", - "- globalstrahlung (global radiation), J/cm2 needs to be in MJ/m3d, ZAMG abbreviation - strahl\n", - "- arithmetische windgeschwindigkeit (wind speed), m/s, ZAMG abbreviation - vv\n", - "- relative feuchte (relative humidity), %, ZAMG abbreviation - rel\n", - "- lufttemparatur (air temperature) in 2 m, C, ZAMG abbreviation - t\n", - "- lufttemperatur (air temperature) max in 2 m, C, ZAMG abbreviation - tmax\n", - "- lufttemperatur (air temperature) min in 2 m, C, ZAMG abbreviation - tmin\n", - "- latitute and elevation of a station" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "236434b2-3c33-4772-93ec-de0cb7317209", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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time
2000-01-0116412300.080.0-2.70.5-5.81.0
2000-01-0216412250.086.00.22.5-2.11.0
2000-01-0316412598.086.00.63.6-2.41.0
2000-01-0416412619.083.0-0.54.5-5.51.0
2000-01-0516412463.084.0-0.15.4-5.51.0
........................
2021-11-0716412852.074.08.512.24.71.6
2021-11-0816412553.078.07.510.44.51.6
2021-11-0916412902.067.07.111.72.42.7
2021-11-1016412785.079.05.310.10.42.1
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7986 rows × 7 columns

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" - ], - "text/plain": [ - " station strahl rel t tmax tmin vv\n", - "time \n", - "2000-01-01 16412 300.0 80.0 -2.7 0.5 -5.8 1.0\n", - "2000-01-02 16412 250.0 86.0 0.2 2.5 -2.1 1.0\n", - "2000-01-03 16412 598.0 86.0 0.6 3.6 -2.4 1.0\n", - "2000-01-04 16412 619.0 83.0 -0.5 4.5 -5.5 1.0\n", - "2000-01-05 16412 463.0 84.0 -0.1 5.4 -5.5 1.0\n", - "... ... ... ... ... ... ... ...\n", - "2021-11-07 16412 852.0 74.0 8.5 12.2 4.7 1.6\n", - "2021-11-08 16412 553.0 78.0 7.5 10.4 4.5 1.6\n", - "2021-11-09 16412 902.0 67.0 7.1 11.7 2.4 2.7\n", - "2021-11-10 16412 785.0 79.0 5.3 10.1 0.4 2.1\n", - "2021-11-11 16412 194.0 91.0 5.1 6.5 3.7 1.1\n", - "\n", - "[7986 rows x 7 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#read data\n", - "data_16412 = pd.read_csv('data//example_1//klima_daily.csv', index_col=1, parse_dates=True)\n", - "data_16412" - ] - }, - { - "cell_type": "markdown", - "id": "22ebf3bc-6b9a-4f81-a455-7ca1b51879dd", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "## Calculate PET for Graz Universität - 16412" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "bc5ba933-22c2-4c5b-9ca6-43a4bcdad344", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", - "\n", - "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", - " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", - "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", - "\n", - "lat = 47.077778*np.pi/180 # Latitude of the meteorological station, converting from degrees to radians\n", - "elevation = 367 # meters above sea-level\n", - "\n", - "# Estimate evapotranspiration with four different methods and create a dataframe\n", - "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax,\n", - " tmin=tmin, rh=rh)" - ] - }, - { - "cell_type": "markdown", - "id": "e6e2564c-48ed-46b7-a275-fd17db592456", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "### Plot results" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c9a4582f-219b-47f8-9ed2-dac80720cf55", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(figsize=(13,4), ncols=2)\n", - "pet_df.plot(ax=axs[0])\n", - "pet_df.cumsum().plot(ax=axs[1], legend=False)\n", - "\n", - "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=12)\n", - "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", - "axs[0].legend(ncol=6, loc=[0,1.])\n", - "for i in (0,1):\n", - " axs[i].set_xlabel(\"Date\", fontsize=12)" - ] - }, - { - "cell_type": "markdown", - "id": "1fe2a55b-838a-4e3a-a621-c5fe55db399a", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "### Store results" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "3c5e47fb-3ec7-4bc9-ad6c-be0edc67ba09", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "#plt.savefig(\"PET_methods.png\", dpi=300)\n", - "#pet_u.to_csv('../evap_16412.csv')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/02_example_zamg_netcdf.ipynb b/examples/02_example_zamg_netcdf.ipynb deleted file mode 100644 index b5e99cd..0000000 --- a/examples/02_example_zamg_netcdf.ipynb +++ /dev/null @@ -1,255 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "999bc8b7-804c-4301-b8c7-5077a38dc06f", - "metadata": {}, - "source": [ - "# 2. Potential Evapotranspiration from ZAMG INCA data (NetCDF)\n", - "*M. Vremec, October 2022, University of Graz*\n", - "\n", - "\n", - "What is done:\n", - "\n", - "- load the data from ZAMG\n", - "- estimate potential evapotranspiration\n", - "- plot and store results\n", - "\n", - "Data source: ZAMG - https://data.hub.zamg.ac.at" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "7a2ae568-3c3b-44f5-8b82-ab5a99d35d2d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python version: 3.9.13 (main, Oct 13 2022, 21:23:06) [MSC v.1916 64 bit (AMD64)]\n", - "Numpy version: 1.21.5\n", - "Pandas version: 1.4.4\n", - "Pyet version: 1.2.2b\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import xarray as xr\n", - "import pyet\n", - "pyet.show_versions()" - ] - }, - { - "cell_type": "markdown", - "id": "da6f3e98-0073-4db9-b763-03beb2611e78", - "metadata": {}, - "source": [ - "## Loading daily data from ZAMG (INCA hourly NetCDF data)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "236434b2-3c33-4772-93ec-de0cb7317209", - "metadata": {}, - "outputs": [], - "source": [ - "#read data\n", - "xr_ds = xr.open_dataset(\"data//example_2//incal_hourly_20120501T0000_20120930T2300.nc\", \n", - " engine=\"netcdf4\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "fd56788b-5aed-499b-8a6a-9c6fb68bb2f6", - "metadata": {}, - "outputs": [], - "source": [ - "# Resample and define input meteorological variables\n", - "tmean = xr_ds[\"T2M\"].resample(time=\"1D\").mean()\n", - "tmax = xr_ds[\"T2M\"].resample(time=\"1D\").max()\n", - "tmin = xr_ds[\"T2M\"].resample(time=\"1D\").min()\n", - "rh = xr_ds[\"RH2M\"].resample(time=\"1D\").mean()\n", - "rhmax = xr_ds[\"RH2M\"].resample(time=\"1D\").max()\n", - "rhmin = xr_ds[\"RH2M\"].resample(time=\"1D\").min()\n", - "wind = ((np.abs(xr_ds[\"VV\"]) + xr_ds[\"UU\"]) / 2).resample(time=\"1D\").mean()\n", - "rs = xr_ds[\"GL\"].resample(time=\"1D\").mean() * 86400 / 1000000" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "f5bb9668-075b-4a8c-99e5-64a998c9c9d5", - "metadata": {}, - "outputs": [], - "source": [ - "# Define latitude and elevation\n", - "lat = tmean.lat * np.pi / 180 \n", - "elevation = lat / lat * 350" - ] - }, - { - "cell_type": "markdown", - "id": "22ebf3bc-6b9a-4f81-a455-7ca1b51879dd", - "metadata": {}, - "source": [ - "## Calculate PET" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "2b8859a2-37e3-40db-afc1-01b449adfc35", - "metadata": {}, - "outputs": [], - "source": [ - "# Estimate evapotranspiration with nine different methods \n", - "pet_penman = pyet.penman(tmean, wind, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", - "pet_pt = pyet.priestley_taylor(tmean, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", - "pet_makkink = pyet.makkink(tmean, rs, elevation=elevation)\n", - "pet_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, lat=lat, tmax=tmax, tmin=tmin, rh=rh)\n", - "pet_hamon = pyet.hamon(tmean, lat=lat, method=1)\n", - "pet_oudin = pyet.oudin(tmean, lat=lat)\n", - "pet_haude = pyet.haude(tmax, rh)\n", - "pet_turc = pyet.turc(tmean, rs, rh)\n", - "pet_har = pyet.hargreaves(tmean, tmax, tmin, lat)" - ] - }, - { - "cell_type": "markdown", - "id": "e6e2564c-48ed-46b7-a275-fd17db592456", - "metadata": {}, - "source": [ - "### Plot results" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "3c0fad4c-4890-48b7-9183-ee861402f509", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(ncols=2, figsize=(12,3))\n", - "pet_penman[:,2,2].plot(ax=axs[0], label=\"Penman\")\n", - "pet_pt[:,2,2].plot(ax=axs[0], label=\"Priestley-Taylor\")\n", - "pet_makkink[:,2,2].plot(ax=axs[0], label=\"Makkink\")\n", - "pet_fao56[:,2,2].plot(ax=axs[0], label=\"FAO56\")\n", - "pet_hamon[:,2,2].plot(ax=axs[0], label=\"Hamon\")\n", - "pet_oudin[:,2,2].plot(ax=axs[0], label=\"Oudin\")\n", - "pet_haude[:,2,2].plot(ax=axs[0], label=\"Haude\")\n", - "pet_turc[:,2,2].plot(ax=axs[0], label=\"Turc\")\n", - "pet_har[:,2,2].plot(ax=axs[0], label=\"Hargreaves\")\n", - "axs[0].legend()\n", - "\n", - "pet_penman[:,2,2].cumsum().plot(ax=axs[1], label=\"Penman\")\n", - "pet_pt[:,2,2].cumsum().plot(ax=axs[1], label=\"Priestley-Taylor\")\n", - "pet_makkink[:,2,2].cumsum().plot(ax=axs[1], label=\"Makkink\")\n", - "pet_fao56[:,2,2].cumsum().plot(ax=axs[1], label=\"FAO56\")\n", - "pet_hamon[:,2,2].cumsum().plot(ax=axs[1], label=\"Hamon\")\n", - "pet_oudin[:,2,2].cumsum().plot(ax=axs[1], label=\"Oudin\")\n", - "pet_haude[:,2,2].cumsum().plot(ax=axs[1], label=\"Haude\")\n", - "pet_turc[:,2,2].cumsum().plot(ax=axs[1], label=\"Turc\")\n", - "pet_har[:,2,2].cumsum().plot(ax=axs[1], label=\"Hargreaves\")\n", - "axs[1].legend()" - ] - }, - { - "cell_type": "markdown", - "id": "1fe2a55b-838a-4e3a-a621-c5fe55db399a", - "metadata": {}, - "source": [ - "### Store results" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "3c5e47fb-3ec7-4bc9-ad6c-be0edc67ba09", - "metadata": {}, - "outputs": [], - "source": [ - "#pet_pt.to_netcdf('../pe_pt_INCA.csv')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/03_example_knmi.ipynb b/examples/03_example_knmi.ipynb deleted file mode 100644 index 625e301..0000000 --- a/examples/03_example_knmi.ipynb +++ /dev/null @@ -1,533 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "d0959a4c", - "metadata": {}, - "source": [ - "# 3. Potential Evapotranspiration from KNMI data\n", - "*R.A. Collenteur, University of Graz, 2021*\n", - "\n", - "Data source: KNMI - https://dataplatform.knmi.nl/\n", - "\n", - "In this notebook it is shown how to compute (potential) evapotranspiration from meteorological data using PyEt. Meteorological data is observed by the KNMI at De Bilt in the Netherlands." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "f8c6cab3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python version: 3.9.13 (main, Oct 13 2022, 21:23:06) [MSC v.1916 64 bit (AMD64)]\n", - "Numpy version: 1.21.5\n", - "Pandas version: 1.4.4\n", - "Pyet version: 1.2.1\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import pyet\n", - "pyet.show_versions()" - ] - }, - { - "cell_type": "markdown", - "id": "61cb9b9e", - "metadata": {}, - "source": [ - "## 1. Load KNMI Data\n", - "\n", - "We first load the raw meteorological data observed by the KNMI at De Bilt in the Netherlands. This datafile contains a lot of different variables, please see the end of the notebook for an explanation of all the variables. " - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "cbc6c337", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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# STNDDVECFHVECFGFHXFHXHFHNFHNHFXXFXXH...VVNHVVXVVXHNGUGUXUXHUNUNHEV24
YYYYMMDD
2018-01-0126022545509021018190.02.0...2.075.03.07.08496177313
2018-01-0226021639458024201140.024.0...19.075.08.07.0889638082
2018-01-03260257828812011704290.03.0...1.075.04.08.0739516591
2018-01-04260238515690203014180.020.0...14.080.021.08.082971467212
2018-01-0526022538406012017150.016.0...15.075.01.06.08796177132
\n", - "

5 rows × 40 columns

\n", - "
" - ], - "text/plain": [ - " # STN DDVEC FHVEC FG FHX FHXH FHN FHNH FXX FXXH ... \\\n", - "YYYYMMDD ... \n", - "2018-01-01 260 225 45 50 90 2 10 18 190.0 2.0 ... \n", - "2018-01-02 260 216 39 45 80 24 20 1 140.0 24.0 ... \n", - "2018-01-03 260 257 82 88 120 11 70 4 290.0 3.0 ... \n", - "2018-01-04 260 238 51 56 90 20 30 14 180.0 20.0 ... \n", - "2018-01-05 260 225 38 40 60 1 20 17 150.0 16.0 ... \n", - "\n", - " VVNH VVX VVXH NG UG UX UXH UN UNH EV24 \n", - "YYYYMMDD \n", - "2018-01-01 2.0 75.0 3.0 7.0 84 96 17 73 1 3 \n", - "2018-01-02 19.0 75.0 8.0 7.0 88 96 3 80 8 2 \n", - "2018-01-03 1.0 75.0 4.0 8.0 73 95 1 65 9 1 \n", - "2018-01-04 14.0 80.0 21.0 8.0 82 97 14 67 21 2 \n", - "2018-01-05 15.0 75.0 1.0 6.0 87 96 17 71 3 2 \n", - "\n", - "[5 rows x 40 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data = pd.read_csv(\"data//example_3//etmgeg_260.txt\", skiprows=46, delimiter=\",\", \n", - " skipinitialspace=True, index_col=\"YYYYMMDD\", parse_dates=True).loc[\"2018\",:]\n", - "data.head()" - ] - }, - { - "cell_type": "markdown", - "id": "be888ed3", - "metadata": {}, - "source": [ - "## 2. Estimating potential evapotranspiration\n", - "\n", - "Now that we have the input data, we can estimate potential evapotranspiration with different estimation methods. Here we choose the Penman, Priestley-Taylor, Makkink, and Oudin methods. " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "abe8a230", - "metadata": {}, - "outputs": [], - "source": [ - "# Preprocess the input data\n", - "meteo = pd.DataFrame({\"tmean\":data.TG/10, \"tmax\":data.TX/10, \"tmin\":data.TN/10, \"rh\":data.UG, \"wind\":data.FG/10, \"rs\":data.Q/100})\n", - "tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", - "pressure = data.PG / 100 # to kPa\n", - "wind = data.FG/10 # to m/s\n", - "lat = 0.91 # Latitude of the meteorological station\n", - "elevation = 4 # meters above sea-level \n", - "\n", - "# Estimate evapotranspiration with four different methods\n", - "pet_penman = pyet.penman(tmean, wind, rs=rs, elevation=4, lat=0.91, tmax=tmax, tmin=tmin, rh=rh)\n", - "pet_pt = pyet.priestley_taylor(tmean, rs=rs, elevation=4, lat=0.91, tmax=tmax, tmin=tmin, rh=rh)\n", - "pet_makkink = pyet.makkink(tmean, rs, elevation=4, pressure=pressure)\n", - "pet_oudin = pyet.oudin(tmean, lat=0.91)" - ] - }, - { - "cell_type": "markdown", - "id": "578f8ac2", - "metadata": {}, - "source": [ - "## 3. Plot the results\n", - "\n", - "We plot the cumulative sums to compare the different estimation methods." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "4c5a8008", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from matplotlib import cm\n", - "viridis = cm.get_cmap('viridis', 4)\n", - "colors = [viridis(i) for i in range(0, 4)]\n", - "\n", - "fig, axs = plt.subplots(figsize=(14,3.5), ncols=2)\n", - "axs[0].plot(pet_penman,label=\"Penman\", c=colors[0])\n", - "axs[0].plot(pet_pt, label=\"Priestley-Taylor\", c=colors[1])\n", - "axs[0].plot(pet_makkink, label=\"Makkink - PyEt\", c=colors[2])\n", - "axs[0].plot(pet_oudin, label=\"Oudin\", c=colors[3])\n", - "axs[1].plot(pet_penman.cumsum(),label=\"Penman\")\n", - "axs[1].plot(pet_pt.cumsum(), label=\"Priestley-Taylor\")\n", - "axs[1].plot(pet_makkink.cumsum(), label=\"Makkink\")\n", - "axs[1].plot(pet_oudin.cumsum(), label=\"Oudin\")\n", - "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=16)\n", - "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", - "for i in (0,1):\n", - " axs[i].set_xlabel(\"Date\", fontsize=12)\n", - " axs[i].legend(loc=2, fontsize=14)\n", - " axs[i].tick_params(\"both\", direction=\"in\", labelsize=14)\n", - "plt.tight_layout()\n", - "#plt.savefig(\"Figure1.png\", dpi=300)" - ] - }, - { - "cell_type": "markdown", - "id": "75dacdc4", - "metadata": {}, - "source": [ - "## 4. Comparison: pyet Makkink vs KNMI Makkink\n", - "\n", - "The KNMI also provides Makkink potential evapotranspiration data (column EV24). We can now compare the results from Pyet and the KNMI to confirm that these are the same." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "95c6b234", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pet_knmi = data.EV24 / 10 # Makkink potential evaporation computen by the KNMI for comparison\n", - "\n", - "# Plot the two series against each other\n", - "plt.scatter(pet_makkink, pet_knmi)\n", - "plt.plot([0,6],[0,6], color=\"red\", label=\"1:1 line\")\n", - "plt.legend()\n", - "plt.xlabel(\"pyet-Makkink [mm]\")\n", - "plt.ylabel(\"KNMI-Makkink [mm]\");" - ] - }, - { - "cell_type": "markdown", - "id": "a51c36d1", - "metadata": {}, - "source": [ - "## 5. Estimation of PET - all methods" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "2a2b17d3", - "metadata": {}, - "outputs": [], - "source": [ - "pet_df = pyet.calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax,\n", - " tmin=tmin, rh=rh)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "055e90d1", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(figsize=(13,4), ncols=2)\n", - "pet_df.plot(ax=axs[0])\n", - "pet_df.cumsum().plot(ax=axs[1], legend=False)\n", - "\n", - "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=12)\n", - "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", - "axs[0].legend(ncol=6, loc=[0,1.])\n", - "for i in (0,1):\n", - " axs[i].set_xlabel(\"Date\", fontsize=12)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "7e55de8b", - "metadata": {}, - "outputs": [], - "source": [ - "#plt.savefig(\"PET_methods.png\", dpi=300)" - ] - }, - { - "cell_type": "markdown", - "id": "815addc4", - "metadata": {}, - "source": [ - "## References\n", - "\n", - "Column description of the KNMI data\n", - "\n", - "- DDVEC = Vector mean wind direction in degrees (360=north, 90=east, 180=south, 270=west, 0=calm/variable)\n", - "- FHVEC = Vector mean windspeed (in 0.1 m/s)\n", - "- FG = Daily mean windspeed (in 0.1 m/s) \n", - "- FHX = Maximum hourly mean windspeed (in 0.1 m/s)\n", - "- FHXH = Hourly division in which FHX was measured\n", - "- FHN = Minimum hourly mean windspeed (in 0.1 m/s)\n", - "- FHNH = Hourly division in which FHN was measured\n", - "- FXX = Maximum wind gust (in 0.1 m/s)\n", - "- FXXH = Hourly division in which FXX was measured\n", - "- TG = Daily mean temperature in (0.1 degrees Celsius)\n", - "- TN = Minimum temperature (in 0.1 degrees Celsius)\n", - "- TNH = Hourly division in which TN was measured\n", - "- TX = Maximum temperature (in 0.1 degrees Celsius)\n", - "- TXH = Hourly division in which TX was measured\n", - "- T10N = Minimum temperature at 10 cm above surface (in 0.1 degrees Celsius)\n", - "- T10NH = 6-hourly division in which T10N was measured; 6=0-6 UT, 12=6-12 UT, 18=12-18 UT, 24=18-24 UT \n", - "- SQ = Sunshine duration (in 0.1 hour) calculated from global radiation (-1 for <0.05 hour)\n", - "- SP = Percentage of maximum potential sunshine duration\n", - "- Q = Global radiation (in J/cm2)\n", - "- DR = Precipitation duration (in 0.1 hour)\n", - "- RH = Daily precipitation amount (in 0.1 mm) (-1 for <0.05 mm)\n", - "- RHX = Maximum hourly precipitation amount (in 0.1 mm) (-1 for <0.05 mm)\n", - "- RHXH = Hourly division in which RHX was measured\n", - "- PG = Daily mean sea level pressure (in 0.1 hPa) calculated from 24 hourly values\n", - "- PX = Maximum hourly sea level pressure (in 0.1 hPa)\n", - "- PXH = Hourly division in which PX was measured\n", - "- PN = Minimum hourly sea level pressure (in 0.1 hPa)\n", - "- PNH = Hourly division in which PN was measured\n", - "- VVN = Minimum visibility; 0: <100 m, 1:100-200 m, 2:200-300 m,..., 49:4900-5000 m, 50:5-6 km, 56:6-7 km, 57:7-8 km,..., 79:29-30 km, 80:30-35 km, 81:35-40 km,..., 89: >70 km)\n", - "- VVNH = Hourly division in which VVN was measured\n", - "- VVX = Maximum visibility; 0: <100 m, 1:100-200 m, 2:200-300 m,..., 49:4900-5000 m, 50:5-6 km, 56:6-7 km, 57:7-8 km,..., 79:29-30 km, 80:30-35 km, 81:35-40 km,..., 89: >70 km)\n", - "- VVXH = Hourly division in which VVX was measured\n", - "- NG = Mean daily cloud cover (in octants, 9=sky invisible)\n", - "- UG = Daily mean relative atmospheric humidity (in percents)\n", - "- UX = Maximum relative atmospheric humidity (in percents)\n", - "- UXH = Hourly division in which UX was measured\n", - "- UN = Minimum relative atmospheric humidity (in percents)\n", - "- UNH = Hourly division in which UN was measured\n", - "- EV24 = Potential evapotranspiration (Makkink) (in 0.1 mm)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/04_example_coagmet.ipynb b/examples/04_example_coagmet.ipynb deleted file mode 100644 index 675659a..0000000 --- a/examples/04_example_coagmet.ipynb +++ /dev/null @@ -1,408 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# 4. Potential Evapotranspiration from CoAgMET data\n", - "*M. Vremec, University of Graz, 2021*\n", - "\n", - "In this notebook it is shown how to compute (reference) evapotranspiration ($ET_0$) from meteorological data observed by the Colorado State University (CoAgMET) at Holyoke in Colorado, USA. The notebook also includes a comparison between $ET_0$ estimated using *pyet* (FAO56) and $ET_0$ available from CoAgMET. According to CoAgMET documentation, the provided reference evapotranspiration is estimated using ASCE reference evapotranspiration for short reference grass (Wright, 2000), which corresponds to the FAO-56 method used with *pyet*.\n", - "\n", - "Source: https://coagmet.colostate.edu/station/selector" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python version: 3.9.13 (main, Oct 13 2022, 21:23:06) [MSC v.1916 64 bit (AMD64)]\n", - "Numpy version: 1.21.5\n", - "Pandas version: 1.4.4\n", - "Pyet version: 1.2.1\n" - ] - } - ], - "source": [ - "import numpy as np\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import pyet as pyet\n", - "pyet.show_versions()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Load CoAgMET Data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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nametavgtmaxtminrhmaxrhminsolarwindrunet_asceet_pket_asce0
date
2020-01-01hyk02-0.89.4-8.90.9290.47063.1203.11.91.91.2
2020-01-02hyk020.87.2-4.20.9020.568107.4314.71.71.71.1
2020-01-03hyk02-0.45.0-4.70.8550.44876.2239.61.71.31.1
2020-01-04hyk024.116.1-4.80.8930.22497.6253.74.01.72.4
2020-01-05hyk020.58.2-6.90.8200.232102.3312.23.11.91.9
....................................
2020-12-27hyk022.28.9-6.20.9670.31898.6324.52.81.61.7
2020-12-28hyk02-4.00.0-10.10.9940.87826.2248.30.40.60.3
2020-12-29hyk02-4.7-1.1-10.80.9830.73755.6441.70.80.60.5
2020-12-30hyk02-8.42.2-14.60.9390.489111.5197.91.21.00.8
2020-12-31hyk02-6.33.4-15.30.9290.459109.099.90.90.60.6
\n", - "

366 rows × 11 columns

\n", - "
" - ], - "text/plain": [ - " name tavg tmax tmin rhmax rhmin solar windrun et_asce \\\n", - "date \n", - "2020-01-01 hyk02 -0.8 9.4 -8.9 0.929 0.470 63.1 203.1 1.9 \n", - "2020-01-02 hyk02 0.8 7.2 -4.2 0.902 0.568 107.4 314.7 1.7 \n", - "2020-01-03 hyk02 -0.4 5.0 -4.7 0.855 0.448 76.2 239.6 1.7 \n", - "2020-01-04 hyk02 4.1 16.1 -4.8 0.893 0.224 97.6 253.7 4.0 \n", - "2020-01-05 hyk02 0.5 8.2 -6.9 0.820 0.232 102.3 312.2 3.1 \n", - "... ... ... ... ... ... ... ... ... ... \n", - "2020-12-27 hyk02 2.2 8.9 -6.2 0.967 0.318 98.6 324.5 2.8 \n", - "2020-12-28 hyk02 -4.0 0.0 -10.1 0.994 0.878 26.2 248.3 0.4 \n", - "2020-12-29 hyk02 -4.7 -1.1 -10.8 0.983 0.737 55.6 441.7 0.8 \n", - "2020-12-30 hyk02 -8.4 2.2 -14.6 0.939 0.489 111.5 197.9 1.2 \n", - "2020-12-31 hyk02 -6.3 3.4 -15.3 0.929 0.459 109.0 99.9 0.9 \n", - "\n", - " et_pk et_asce0 \n", - "date \n", - "2020-01-01 1.9 1.2 \n", - "2020-01-02 1.7 1.1 \n", - "2020-01-03 1.3 1.1 \n", - "2020-01-04 1.7 2.4 \n", - "2020-01-05 1.9 1.9 \n", - "... ... ... \n", - "2020-12-27 1.6 1.7 \n", - "2020-12-28 0.6 0.3 \n", - "2020-12-29 0.6 0.5 \n", - "2020-12-30 1.0 0.8 \n", - "2020-12-31 0.6 0.6 \n", - "\n", - "[366 rows x 11 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data = pd.read_csv(\"data//example_4//et_coagmet.txt\", parse_dates=True, index_col=\"date\")\n", - "data" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "et0_coagmet = data[\"et_asce0\"]\n", - "\n", - "meteo = pd.DataFrame({\"tmean\":data[\"tavg\"], \n", - " \"tmax\":data[\"tmax\"],\n", - " \"tmin\":data[\"tmin\"], \n", - " \"rhmax\":data[\"rhmax\"]*100,\n", - " \"rhmin\":data[\"rhmin\"]*100, \n", - " \"u2\":data[\"windrun\"]*1000/86400,\n", - " \"rs\":data[\"solar\"]*86400/1000000})\n", - "\n", - "tmean, tmax, tmin, rhmax, rhmin, wind, rs = [meteo[col] for col in meteo.columns]\n", - "lat = 40.49 * np.pi / 180" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Comparison: pyet FAO56 vs CoAgMET ASCE " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "et0_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=1138, lat=lat, \n", - " tmax=tmax, tmin=tmin, rhmax=rhmax, rhmin=rhmin)\n", - "\n", - "et0_fao56.plot()\n", - "et0_coagmet.plot();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Plot the results\n", - "\n", - "We now plot the evaporation time series against each other to see how these compare. " - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.scatter(et0_fao56, et0_coagmet)\n", - "plt.plot([0,15],[0,15], color=\"red\", label=\"1:1 line\")\n", - "plt.legend()\n", - "plt.xlabel(\"ET0 pyet-FAO56 [mm]\")\n", - "plt.ylabel(\"ET0 CoAgMET-ASCE [mm]\");" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/05_example_calibration.ipynb b/examples/05_example_calibration.ipynb deleted file mode 100644 index 77129b7..0000000 --- a/examples/05_example_calibration.ipynb +++ /dev/null @@ -1,518 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# 5. Calibration of potential evapotranspiration methods\n", - "*M. Vremec, R.A. Collenteur University of Graz, 2021*\n", - "\n", - "In this notebook it is shown how to calibrate various (potential) evapotranspiration (PET) equations, using a linear regression relationship between daily potential evapotranspiration obtained with the FAO-56 equation and daily PET estimates obtained with the alternative methods. This notebook requires Scipy and SkLearn python packages to run." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "from scipy.optimize import least_squares\n", - "from sklearn.metrics import mean_squared_error\n", - "\n", - "import pyet as pyet" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Load KNMI Data" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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# STNDDVECFHVECFGFHXFHXHFHNFHNHFXXFXXH...VVNHVVXVVXHNGUGUXUXHUNUNHEV24
YYYYMMDD
2018-01-0126022545509021018190.02.0...2.075.03.07.08496177313
2018-01-0226021639458024201140.024.0...19.075.08.07.0889638082
2018-01-03260257828812011704290.03.0...1.075.04.08.0739516591
2018-01-04260238515690203014180.020.0...14.080.021.08.082971467212
2018-01-0526022538406012017150.016.0...15.075.01.06.08796177132
\n", - "

5 rows × 40 columns

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" - ], - "text/plain": [ - " # STN DDVEC FHVEC FG FHX FHXH FHN FHNH FXX FXXH ... \\\n", - "YYYYMMDD ... \n", - "2018-01-01 260 225 45 50 90 2 10 18 190.0 2.0 ... \n", - "2018-01-02 260 216 39 45 80 24 20 1 140.0 24.0 ... \n", - "2018-01-03 260 257 82 88 120 11 70 4 290.0 3.0 ... \n", - "2018-01-04 260 238 51 56 90 20 30 14 180.0 20.0 ... \n", - "2018-01-05 260 225 38 40 60 1 20 17 150.0 16.0 ... \n", - "\n", - " VVNH VVX VVXH NG UG UX UXH UN UNH EV24 \n", - "YYYYMMDD \n", - "2018-01-01 2.0 75.0 3.0 7.0 84 96 17 73 1 3 \n", - "2018-01-02 19.0 75.0 8.0 7.0 88 96 3 80 8 2 \n", - "2018-01-03 1.0 75.0 4.0 8.0 73 95 1 65 9 1 \n", - "2018-01-04 14.0 80.0 21.0 8.0 82 97 14 67 21 2 \n", - "2018-01-05 15.0 75.0 1.0 6.0 87 96 17 71 3 2 \n", - "\n", - "[5 rows x 40 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data = pd.read_csv(\"data//example_3//etmgeg_260.txt\", skiprows=46, delimiter=\",\", \n", - " skipinitialspace=True, index_col=\"YYYYMMDD\", parse_dates=True).loc[\"2018\",:]\n", - "data.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.Estimation of potential evapotranspiration" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# define meteorological variables needed for PE estimation\n", - "meteo = pd.DataFrame({\"tmean\":data.TG/10, \"tmax\":data.TX/10, \"tmin\":data.TN/10, \"rh\":data.UG, \"wind\":data.FG/10, \"rs\":data.Q/100})\n", - "tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", - "pressure = data.PG / 100 # to kPa\n", - "wind = data.FG/10 # to m/s\n", - "lat = 0.91 # [rad]\n", - "elevation = 4 \n", - "\n", - "pet_fao56 = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, lat=lat, \n", - " tmax=tmax, tmin=tmin, rh=rh) # FAO-56 method\n", - "pet_romanenko = pyet.romanenko(tmean, rh) # Romanenko method\n", - "pet_abtew = pyet.abtew(tmean, rs) # Abtew method" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The model performance of the Abtew and Romanenko method will be evaluated using the root mean square error (RMSE), as implemented in SkLearn’s mean_squared_error method." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RMSE(Romanenko) = 0.6919512654413198 mm/d\n", - "RMSE(Abtew) = 0.7387078735036146 mm/d\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pet_fao56.plot()\n", - "pet_romanenko.plot()\n", - "pet_abtew.plot()\n", - "plt.ylabel(\"PE [mm/day]\")\n", - "print(\"RMSE(Romanenko) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_romanenko, squared=False)))\n", - "print(\"RMSE(Abtew) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_abtew, squared=False)))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Calibration of different PE equations\n", - "\n", - "The least squares approach is applied to estimate the parameters in the PE equations, by minimizing the sum of the residuals between the simulated (Abtew and Romanenko) and observed (FAO-56) data. The minimization of the objective function is done using the Trust Region Reflective algorithm, as implemented in Scipy’s least squares method." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 3.1 Romanenko method" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# Define function for computing residuals\n", - "def cal_romanenko(k, obs):\n", - " return pyet.romanenko(tmean, rh, k)-obs" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([3.87304623])" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# estimate k in the Romanenko method\n", - "x0 = 4.5 # initial estimate of parameter\n", - "res_1 = least_squares(cal_romanenko, x0, args=[pet_fao56])\n", - "res_1.x" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RMSE(Romanenko) = 0.5470690023375226 mm/d\n" - ] - } - ], - "source": [ - "# Compute RMSE using the calibrated value of k\n", - "pet_romanenko_cal = pyet.romanenko(tmean, rh, k=res_1.x)\n", - "print(\"RMSE(Romanenko) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_romanenko_cal, squared=False)))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "RMSE (calibrated) = 0.546 < RMSE (uncalibrated) = 0.694" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 3.2 Abtew method" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# Define function for computing residuals and initial estimate of parameters\n", - "def cal_abtew(k,obs):\n", - " return pyet.abtew(tmean, rs, k)-obs\n", - "x0 = 0.53" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0.45748986])" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# estimate k in the Romanenko method\n", - "res_2 = least_squares(cal_abtew, x0, args=[pet_fao56])\n", - "res_2.x" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "RMSE(Abtew) = 0.6127899429733885 mm/d\n" - ] - } - ], - "source": [ - "pet_abtew_cali = pyet.abtew(tmean, rs, res_2.x)\n", - "print(\"RMSE(Abtew) = {} mm/d\".format(mean_squared_error(pet_fao56, pet_abtew_cali, squared=False)))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "RMSE (calibrated) = 0.613 < RMSE (uncalibrated) = 0.741" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pet_fao56.plot()\n", - "pet_romanenko_cal.plot()\n", - "pet_abtew_cali.plot()\n", - "plt.ylabel(\"PET [mm/d]\");" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/07_example_climate_change.ipynb b/examples/07_example_climate_change.ipynb deleted file mode 100644 index 1b060e9..0000000 --- a/examples/07_example_climate_change.ipynb +++ /dev/null @@ -1,334 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# 7. Potential evapotranspiration under warming and elevated $CO_2$ concentration\n", - "*M. Vremec, R.A. Collenteur University of Graz, 2021*\n", - "\n", - "In this notebook it is shown how to estimate Potential Evapotranspiration under elevated $CO_2$ conditions and an increase in temperature.\n", - "The work follows the suggestions made by Yang et al. (2019) to include the sensitivity of stomatal resistance to $CO_2$ in the Penman-Monteith equation.\n", - "\n", - "Yang, Y., Roderick, M.L., Zhang, S. et al. Hydrologic implications of vegetation response to elevated CO2 in climate projections. Nature Clim Change 9, 44–48 (2019). https://doi.org/10.1038/s41558-018-0361-0" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import pyet as pyet" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Load daily data from ZAMG (Messstationen Tagesdaten)\n", - "\n", - "station: Graz Universität 16412\n", - "\n", - "Selected variables:\n", - "- globalstrahlung (global radiation), J/cm2 needs to be in MJ/m3d, ZAMG abbreviation - strahl\n", - "- arithmetische windgeschwindigkeit (wind speed), m/s, ZAMG abbreviation - vv\n", - "- relative feuchte (relative humidity), %, ZAMG abbreviation - rel\n", - "- lufttemparatur (air temperature) in 2 m, C, ZAMG abbreviation - t\n", - "- lufttemperatur (air temperature) max in 2 m, C, ZAMG abbreviation - tmax\n", - "- lufttemperatur (air temperature) min in 2 m, C, ZAMG abbreviation - tmin\n", - "- latitute and elevation of a station" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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2000-01-0116412300.080.0-2.70.5-5.81.0
2000-01-0216412250.086.00.22.5-2.11.0
2000-01-0316412598.086.00.63.6-2.41.0
2000-01-0416412619.083.0-0.54.5-5.51.0
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........................
2021-11-0716412852.074.08.512.24.71.6
2021-11-0816412553.078.07.510.44.51.6
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" - ], - "text/plain": [ - " station strahl rel t tmax tmin vv\n", - "time \n", - "2000-01-01 16412 300.0 80.0 -2.7 0.5 -5.8 1.0\n", - "2000-01-02 16412 250.0 86.0 0.2 2.5 -2.1 1.0\n", - "2000-01-03 16412 598.0 86.0 0.6 3.6 -2.4 1.0\n", - "2000-01-04 16412 619.0 83.0 -0.5 4.5 -5.5 1.0\n", - "2000-01-05 16412 463.0 84.0 -0.1 5.4 -5.5 1.0\n", - "... ... ... ... ... ... ... ...\n", - "2021-11-07 16412 852.0 74.0 8.5 12.2 4.7 1.6\n", - "2021-11-08 16412 553.0 78.0 7.5 10.4 4.5 1.6\n", - "2021-11-09 16412 902.0 67.0 7.1 11.7 2.4 2.7\n", - "2021-11-10 16412 785.0 79.0 5.3 10.1 0.4 2.1\n", - "2021-11-11 16412 194.0 91.0 5.1 6.5 3.7 1.1\n", - "\n", - "[7986 rows x 7 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#read data\n", - "data_16412 = pd.read_csv('data//example_1//klima_daily.csv', index_col=1, parse_dates=True)\n", - "data_16412" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", - "\n", - "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", - " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", - "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", - "\n", - "lat = 47.077778 * np.pi / 180 # Latitude of the meteorological station, converting from degrees to radians\n", - "elevation = 367 # meters above sea-level" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.Estimate potential evapotranspiration under RCP scenarios" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# the first element in the list includes the rise in temperature, and the CO2 concentration\n", - "rcp_26 = [1.3, 450]\n", - "rcp_45 = [2, 650]\n", - "rcp_85 = [4.5, 850]\n", - "\n", - "def pe_cc(tincrease, co2):\n", - " pe = pyet.pm(tmean+tincrease, wind, rs=rs, elevation=elevation, lat=lat, \n", - " tmax=tmax+tincrease, tmin=tmin+tincrease, rh=rh, co2=co2)\n", - " return pe\n", - "\n", - "# Estimate evapotranspiration with four different methods and create a dataframe\n", - "pet_df = pd.DataFrame()\n", - "pet_df[\"amb.\"] = pe_cc(0, 420)\n", - "pet_df[\"RCP 2.6\"] = pe_cc(rcp_26[0], rcp_26[1])\n", - "pet_df[\"RCP 4.5\"] = pe_cc(rcp_45[0], rcp_45[1])\n", - "pet_df[\"RCP 8.5\"] = pe_cc(rcp_85[0], rcp_85[1])" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axs = plt.subplots(figsize=(13,4), ncols=2)\n", - "pet_df.plot(ax=axs[0])\n", - "pet_df.cumsum().plot(ax=axs[1], legend=False)\n", - "\n", - "axs[0].set_ylabel(\"PET [mm/day]\", fontsize=12)\n", - "axs[1].set_ylabel(\"Cumulative PET [mm]\", fontsize=12)\n", - "axs[0].legend(ncol=6, loc=[0,1.])\n", - "for i in (0,1):\n", - " axs[i].set_xlabel(\"Date\", fontsize=12)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/08_crop_coefficient.ipynb b/examples/08_crop_coefficient.ipynb deleted file mode 100644 index 9309aa8..0000000 --- a/examples/08_crop_coefficient.ipynb +++ /dev/null @@ -1,455 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "999bc8b7-804c-4301-b8c7-5077a38dc06f", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "# 8. Determining the crop coefficient function with Python\n", - "*M. Vremec, October 2022, University of Graz*\n", - "\n", - "Data source: ZAMG - https://data.hub.zamg.ac.at\n", - "\n", - "What is done:\n", - "\n", - "- load the station data from ZAMG\n", - "- estimate potential evapotranspiration\n", - "- determine the crop coefficient function based on equation 65 in Allen et al. 1998\n", - "- plot and store result" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "7a2ae568-3c3b-44f5-8b82-ab5a99d35d2d", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Python version: 3.9.13 (main, Oct 13 2022, 21:23:06) [MSC v.1916 64 bit (AMD64)]\n", - "Numpy version: 1.21.5\n", - "Pandas version: 1.4.4\n", - "Pyet version: 1.2.0b\n" - ] - } - ], - "source": [ - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import pyet\n", - "pyet.show_versions()" - ] - }, - { - "cell_type": "markdown", - "id": "da6f3e98-0073-4db9-b763-03beb2611e78", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "## Loading daily data from ZAMG (Messstationen Tagesdaten)\n", - "\n", - "station: Graz Universität 16412\n", - "\n", - "Selected variables:\n", - "- globalstrahlung (global radiation), J/cm2 needs to be in MJ/m3d, ZAMG abbreviation - strahl\n", - "- arithmetische windgeschwindigkeit (wind speed), m/s, ZAMG abbreviation - vv\n", - "- relative feuchte (relative humidity), %, ZAMG abbreviation - rel\n", - "- lufttemparatur (air temperature) in 2 m, C, ZAMG abbreviation - t\n", - "- lufttemperatur (air temperature) max in 2 m, C, ZAMG abbreviation - tmax\n", - "- lufttemperatur (air temperature) min in 2 m, C, ZAMG abbreviation - tmin\n", - "- latitute and elevation of a station" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "236434b2-3c33-4772-93ec-de0cb7317209", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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stationstrahlrelttmaxtminvv
time
2000-01-0116412300.080.0-2.70.5-5.81.0
2000-01-0216412250.086.00.22.5-2.11.0
2000-01-0316412598.086.00.63.6-2.41.0
2000-01-0416412619.083.0-0.54.5-5.51.0
2000-01-0516412463.084.0-0.15.4-5.51.0
........................
2021-11-0716412852.074.08.512.24.71.6
2021-11-0816412553.078.07.510.44.51.6
2021-11-0916412902.067.07.111.72.42.7
2021-11-1016412785.079.05.310.10.42.1
2021-11-1116412194.091.05.16.53.71.1
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7986 rows × 7 columns

\n", - "
" - ], - "text/plain": [ - " station strahl rel t tmax tmin vv\n", - "time \n", - "2000-01-01 16412 300.0 80.0 -2.7 0.5 -5.8 1.0\n", - "2000-01-02 16412 250.0 86.0 0.2 2.5 -2.1 1.0\n", - "2000-01-03 16412 598.0 86.0 0.6 3.6 -2.4 1.0\n", - "2000-01-04 16412 619.0 83.0 -0.5 4.5 -5.5 1.0\n", - "2000-01-05 16412 463.0 84.0 -0.1 5.4 -5.5 1.0\n", - "... ... ... ... ... ... ... ...\n", - "2021-11-07 16412 852.0 74.0 8.5 12.2 4.7 1.6\n", - "2021-11-08 16412 553.0 78.0 7.5 10.4 4.5 1.6\n", - "2021-11-09 16412 902.0 67.0 7.1 11.7 2.4 2.7\n", - "2021-11-10 16412 785.0 79.0 5.3 10.1 0.4 2.1\n", - "2021-11-11 16412 194.0 91.0 5.1 6.5 3.7 1.1\n", - "\n", - "[7986 rows x 7 columns]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#read data\n", - "data_16412 = pd.read_csv('data//example_1//klima_daily.csv', index_col=1, parse_dates=True)\n", - "data_16412" - ] - }, - { - "cell_type": "markdown", - "id": "22ebf3bc-6b9a-4f81-a455-7ca1b51879dd", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "## Calculate PET for Graz Universität - 16412" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "bc5ba933-22c2-4c5b-9ca6-43a4bcdad344", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [], - "source": [ - "# Convert Glabalstrahlung J/cm2 to MJ/m2 by dividing to 100\n", - "\n", - "meteo = pd.DataFrame({\"time\":data_16412.index, \"tmean\":data_16412.t, \"tmax\":data_16412.tmax, \"tmin\":data_16412.tmin, \"rh\":data_16412.rel, \n", - " \"wind\":data_16412.vv, \"rs\":data_16412.strahl/100})\n", - "time, tmean, tmax, tmin, rh, wind, rs = [meteo[col] for col in meteo.columns]\n", - "\n", - "lat = 47.077778*np.pi/180 # Latitude of the meteorological station, converting from degrees to radians\n", - "elevation = 367 # meters above sea-level\n", - "\n", - "# Estimate potential ET with Penman-Monteith FAO-56\n", - "pet_pm = pyet.pm_fao56(tmean, wind, rs=rs, elevation=elevation, \n", - " lat=lat, tmax=tmax, tmin=tmin, rh=rh)" - ] - }, - { - "cell_type": "markdown", - "id": "696cb6aa-773d-4e1b-8a11-64ee5a5242e9", - "metadata": {}, - "source": [ - "## Determine the crop coefficient function\n", - "\n", - "Based on: https://www.fao.org/3/x0490e/x0490e0b.htm\n", - "figure 34.\n", - "\n", - "\n", - "![Figure 34](https://www.fao.org/3/x0490e/x0490e6k.gif)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "f92b3767-7233-461c-a924-cafc6f5c9882", - "metadata": {}, - "outputs": [], - "source": [ - "Kcini = 0.3 \n", - "Kcmid = 1.1\n", - "Kcend = 0.65\n", - "\n", - "crop_ini = pd.Timestamp(\"2020-04-01\")\n", - "crop_dev = pd.Timestamp(\"2020-05-01\")\n", - "mid_season = pd.Timestamp(\"2020-06-01\")\n", - "late_s_start = pd.Timestamp(\"2020-07-01\")\n", - "late_s_end = pd.Timestamp(\"2020-08-01\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "86d39fcb-0dea-42ca-9b7a-afa5327ad990", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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Yu2EyLuxGgAG8jO9W8h9CDBBmnLth+LJHwDf4biX/IMQAYYZuGMD3uFvJPwgxQJihGwbwjzNL8E7WnQ70kkIOIQYII87dMLek83UegK85l+A9/fe9gV5OyCHEAGHEuRvm8v7nB3o5QMhjrORbhBggjNANA/gfYyXfIcQAYeJQ1UkVflUpSbppaJ8ArwYIL/PHpai3/W6ljYyVvIUQA4QJ526YhK50wwD+FBvdQblOY6WP91UGeEWhgRADhAG6YYDA+9HF3XX75Y0X1P+/dTsZK3kBIQYIA3TDAMFh/ljGSt5EiAHCAN0wQHDozFjJqwgxQIijGwYILoyVvIcQA4Q4umGA4MNYyTsIMUCIoxsGCD6MlbyDEAOEMOdumJvT6IYBgonzWOnBtYyVPEGIAULYeqdumL7n0w0DBBv7WKn0GGMlTxBigBBls9m0jm4YIKgxVjo3hBggRG0/QDcMYASMlTxHiAFC1NriMkl0wwBGwFjJM4QYIASdrDutt3bSDQMYBWMlzxBigBC08bNy1dTV0w0DGAgleO4jxAAhiG4YwJgowXMPIQYIMYeqTuqjfXTDAEbEWMk9hBggxLxBNwxgaIyV2o4QA4QQm82mtXTDAIbHWKltCDFACCk6SDcMEAoYK7UNIQYIIWuLGs/C0A0DGB9jpbMjxAAh4mTdab21q7EbZmIaoyQgFDBWah0hBggRf/+8XCdqT6tf1466IqlroJcDwAsYK7WOEAOECLphgNDEdyu1zKMQs3TpUiUlJSk6Olrp6enavHlzq/uvXr1agwcPVseOHdWrVy/dddddqqwkTQLecqjqpAq/ohsGCFUP8d1KzXI7xKxZs0Zz587V/PnztWPHDo0aNUpZWVkqLS1tdv8tW7Zo6tSpmj59uj7//HO9/vrr2r59u2bMmHHOiwfQaD3dMEBIi2Ws1Cy3Q8yiRYs0ffp0zZgxQykpKVq8eLESEhK0bNmyZvffunWr+vfvrzlz5igpKUlXXXWV7rnnHhUVFZ3z4gF83w1TTDcMEOoYKzXlVoipq6tTcXGxMjMzXbZnZmaqsLCw2WMyMjJ06NAh5efny2az6euvv9batWs1duzYFl+ntrZWVqvV5QGgedsPVKn0GN0wQDiYz1jJhVshpqKiQvX19YqPj3fZHh8fr/Ly8maPycjI0OrVqzVp0iRFRkaqZ8+e6tKli/7whz+0+Dq5ubkym82OR0JCgjvLBMLK2uIySXTDAOGgc3QHPeE0Vtoa5mMljy7sPfPOB5vN1uLdELt379acOXP08MMPq7i4WBs3btT+/fs1c+bMFp8/JydH1dXVjkdZWZknywRC3sm603prZ2M3zC3phH0gHFztXIIX5mMlt/7aFhcXp4iIiCZnXY4ePdrk7Ixdbm6uRo4cqQcffFCSdNlll6lTp04aNWqUHnvsMfXq1avJMVFRUYqKinJnaUBY2vhZuWrq6pXYraMu739+oJcDwE/mj03RB1984xgrPfqTSwO9pIBw60xMZGSk0tPTVVBQ4LK9oKBAGRkZzR5z8uRJtWvn+jIRERGSGs/gAPCc44LeNLphgHDCWKmR2+Ok7OxsLV++XHl5edqzZ4/uv/9+lZaWOsZDOTk5mjp1qmP/8ePHa/369Vq2bJn27dunDz/8UHPmzNEVV1yh3r17e++dAGHG3g1jMkk30Q0DhJ2rL+6uO64I77GS21cBTpo0SZWVlVq4cKEsFotSU1OVn5+vxMRESZLFYnHpjJk2bZqOHz+uJUuW6Je//KW6dOmia665Rk8++aT33gUQhtZ/clgS3TBAOHtoTIre3xu+YyWTzQAzHavVKrPZrOrqasXGxgZ6OUDA2Ww2/ejpTSo9dlK/nzRYNw2lHwYIVx988Y2m5m2TJL328yt15QXdAryiH/j69zffnQQYkL0b5ryo9rrhUrphgHAWzmMlQgxgQI5umEF0wwBoHCv16RITdiV4hBjAYFy6YYYxRgJgv1tpkKTwuluJEAMYjHM3zLBEumEANBo1IPzGSoQYwGDohgHQknAbKxFiAANx7oa5mW+sBnCGcBsrEWIAA3HuhunTJSbAqwEQjMJprESIAQzCZrNp3Sffj5I4CwOgFeEyViLEAAax/UCVDlaeVKfICLphALQqXMZKhBjAIOzdMOMu6003DICzCoexEiEGMAC6YQB4ItTHSoQYwADohgHgiVAfKxFiAAOgGwaAp0J5rESIAYJc2TG6YQCcm1AdKxFigCBHNwyAcxWqYyVCDBDEGhpsWvtJ411JdMMAOBeNY6V+kkJnrESIAYLY9gPHVHbsO50X1Z5uGADn7KExl4TUWIkQAwQx+wW9Ywb1pBsGwDkLtbESIQYIUifrTit/1/fdMOkJAV4NgFARSmMlQgwQpN7e1dgN069rR13en24YAN7jPFZ68u1/Bno5HiPEAEHK0Q2TTjcMAO9yHiv96aODhh0rEWKAIFR27KQ+2vd9N0xan0AvB0AICoWxEiEGCELO3TB9z+8Y4NUACFVGHysRYoAgQzcMAH85c6z00VfGGisRYoAgQzcMAH9yGSut+9RQYyVCDBBk7Bf0jh3Ui24YAH5hHyuVHfvOUGMlQgwQRGpqT+stezfMMEZJAPyjc3QHPTnxMknGGisRYoAgsvGzcp2sq1dit44alkg3DAD/uWpAnMtYqaY2+MdKhBggiDi6YdLohgHgf85jpac2Bv9YiRADBAmXbhjuSgIQAEYbKxFigCBh74YZcUE39ekSE+DVAAhXRhoreRRili5dqqSkJEVHRys9PV2bN29ucd9p06bJZDI1eVx66aUeLxoINc7dMLdyQS+AAHO5WymIx0puh5g1a9Zo7ty5mj9/vnbs2KFRo0YpKytLpaWlze7/7LPPymKxOB5lZWXq2rWrbr311nNePBAq6IYBEEycx0ovBfFYye0Qs2jRIk2fPl0zZsxQSkqKFi9erISEBC1btqzZ/c1ms3r27Ol4FBUVqaqqSnfdddc5Lx4IFXTDAAg2Vw2I0+ThwT1WcivE1NXVqbi4WJmZmS7bMzMzVVhY2KbnWLFiha677jolJia2uE9tba2sVqvLAwhVdMMACFY5WcF9t5JbIaaiokL19fWKj4932R4fH6/y8vKzHm+xWPT2229rxowZre6Xm5srs9nseCQkJLizTMBQ6IYBEKyC/W4ljy7sPbO/wmaztanTYtWqVerSpYsmTJjQ6n45OTmqrq52PMrKyjxZJmAIdMMACGbBPFZyK8TExcUpIiKiyVmXo0ePNjk7cyabzaa8vDxNmTJFkZGRre4bFRWl2NhYlwcQiuiGAWAEzmOlYLpbya0QExkZqfT0dBUUFLhsLygoUEZGRqvHvv/++/rXv/6l6dOnu79KIETZu2EyLqQbBkDwCta7ldweJ2VnZ2v58uXKy8vTnj17dP/996u0tFQzZ86U1DgKmjp1apPjVqxYoeHDhys1NfXcVw2EAOdumFs4CwMgyAVjCZ7b93JOmjRJlZWVWrhwoSwWi1JTU5Wfn++428hisTTpjKmurta6dev07LPPemfVQAigGwaA0Tw05hJ98MU3jruVFvw0sCcmTDabzRbQFbSB1WqV2WxWdXU118cgZDz4+qd6vfiQJg1L0JO3XBbo5QBAm2z5skJ3rvhYkvTqf16pERd2a3FfX//+5ruTgABw7obhawYAGEkwjZUIMUAA2Lth+nfrqHS6YQAYTLB8txIhBggARzdMOt0wAIync3QHPTFxkKTA3q1EiAH8zLkb5qY0RkkAjGnUgO4BHysRYgA/s3fDjLwwjm4YAIYW6LESIQbwI7phAISSM0vwCr+q8OvrE2IAP6IbBkCocblbae1Ov46VCDGAH9kv6B13WS/FREYEeDUA4B32sdKhqu/0xNv+GysRYgA/ce6GYZQEIJQ4j5X+vNV/YyVCDOAndMMACGVXDYjT5OH+HSsRYgA/oRsGQKh7aEyKX8dKhBjAD+iGARAOzotq7zJW+nifb0vwCDGAH9ANAyBcOI+VfvOXz3z6WoQYwMfohgEQbuxjpSPf/tunr0OIAXyMbhgA4cZ5rORLhBjAx+iGARCOrhoQp3lZyT59DUIM4EN0wwAIZ3de2d+nz0+IAXzobbphAMBnCDGAD60t/uGCXrphAMC7CDGAj5QdO6mt+47RDQMAPkKIAXxk3SeNF/RmXNiNbhgA8AFCDOADDQ02R4i5NT0hwKsBgNBEiAF8YBvdMADgc4QYwAfohgEA3yPEAF5WU3ta+XTDAIDPEWIAL6MbBgD8gxADeBndMADgH4QYwIvohgEA/yHEAF5kv6165IVxdMMAgI8RYgAvce6G4YJeAPA9QgzgJXTDAIB/eRRili5dqqSkJEVHRys9PV2bN29udf/a2lrNnz9fiYmJioqK0oUXXqi8vDyPFgwEK3s3zNhBdMMAgD+0d/eANWvWaO7cuVq6dKlGjhypF154QVlZWdq9e7f69evX7DG33Xabvv76a61YsUIXXXSRjh49qtOnT5/z4oFg4dwNc+swRkkA4A8mm81mc+eA4cOHKy0tTcuWLXNsS0lJ0YQJE5Sbm9tk/40bN+r222/Xvn371LVrV48WabVaZTabVV1drdjYWI+eA/CltcWH9MDrn6p/t45674Efc2s1AMj3v7/dGifV1dWpuLhYmZmZLtszMzNVWFjY7DEbNmzQsGHD9NRTT6lPnz66+OKL9cADD+i7775r8XVqa2tltVpdHkAwoxsGAPzPrXFSRUWF6uvrFR8f77I9Pj5e5eXlzR6zb98+bdmyRdHR0XrjjTdUUVGhe++9V8eOHWvxupjc3FwtWLDAnaUBAUM3DAAEhkcX9p75N02bzdbi3z4bGhpkMpm0evVqXXHFFRozZowWLVqkVatWtXg2JicnR9XV1Y5HWVmZJ8sE/IJuGAAIDLfOxMTFxSkiIqLJWZejR482OTtj16tXL/Xp00dms9mxLSUlRTabTYcOHdKAAQOaHBMVFaWoqCh3lgYEBN0wABA4bp2JiYyMVHp6ugoKCly2FxQUKCMjo9ljRo4cqSNHjujEiROObV988YXatWunvn35P30YG90wABA4bo+TsrOztXz5cuXl5WnPnj26//77VVpaqpkzZ0pqHAVNnTrVsf/kyZPVrVs33XXXXdq9e7c++OADPfjgg7r77rsVE8OpdxibvRtm3GV0wwCAv7ndEzNp0iRVVlZq4cKFslgsSk1NVX5+vhITEyVJFotFpaWljv3PO+88FRQUaPbs2Ro2bJi6deum2267TY899pj33gUQAM7dMIySAMD/3O6JCQR6YhCM6IYBgNYFVU8MgB/Yu2EmptENAwCBQIgBPODcDXMzoyQACAhCDOABumEAIPAIMYCb6IYBgOBAiAHcZO+G6Uw3DAAEFCEGcJOjG2Yw3TAAEEiEGMANdMMAQPAgxABuePuzcp2sq1dSXCel9Ts/0MsBgLBGiAHcYO+GuSWdbhgACDRCDNBGzt0wNw3tE+jlAEDYI8QAbWS/rfqqi+LUm24YAAg4QgzQBs7dMBPTuKAXAIIBIQZoA7phACD4EGKANqAbBgCCDyEGOAu6YQAgOBFigLOgGwYAghMhBjgLumEAIDgRYoBWlFbSDQMAwYoQA7SCbhgACF6EGKAFzt0wXNALAMGHEAO04OP9x3SoqrEbJnMg3TAAEGwIMUAL6IYBgOBGiAGaUVN7Wm9/RjcMAAQzQgzQjPxdFrphACDIEWKAZthHSXTDAEDwIsQAZyitPKmP99MNAwDBjhADnIFuGAAwBkIM4IRuGAAwDkIM4IRuGAAwDkIM4IRuGAAwDkIM8D26YQDAWDwKMUuXLlVSUpKio6OVnp6uzZs3t7jvpk2bZDKZmjz++c9/erxowBfohgEAY3E7xKxZs0Zz587V/PnztWPHDo0aNUpZWVkqLS1t9bi9e/fKYrE4HgMGDPB40YAv0A0DAMbidohZtGiRpk+frhkzZiglJUWLFy9WQkKCli1b1upxPXr0UM+ePR2PiAiuN0DwoBsGAIzHrRBTV1en4uJiZWZmumzPzMxUYWFhq8cOHTpUvXr10rXXXqv33nuv1X1ra2tltVpdHoAvraUbBgAMx60QU1FRofr6esXHx7tsj4+PV3l5ebPH9OrVSy+++KLWrVun9evXKzk5Wddee60++OCDFl8nNzdXZrPZ8UhISHBnmYBbGhpsWldMNwwAGE17Tw4683oBm83W4jUEycnJSk5Odvx5xIgRKisr0zPPPKOrr7662WNycnKUnZ3t+LPVaiXIwGe27q/U4W/phgEAo3HrTExcXJwiIiKanHU5evRok7Mzrbnyyiv15ZdftvjzqKgoxcbGujwAX6EbBgCMya0QExkZqfT0dBUUFLhsLygoUEZGRpufZ8eOHerVq5c7Lw34xIna03p7V2MoZ5QEAMbi9jgpOztbU6ZM0bBhwzRixAi9+OKLKi0t1cyZMyU1joIOHz6sl156SZK0ePFi9e/fX5deeqnq6ur08ssva926dVq3bp133wnggfxdFn13im4YADAit0PMpEmTVFlZqYULF8pisSg1NVX5+flKTEyUJFksFpfOmLq6Oj3wwAM6fPiwYmJidOmll+qtt97SmDFjvPcuAA/RDQMAxmWy2Wy2QC/ibKxWq8xms6qrq7k+Bl5zsLJGP3p6k0wm6cNfXcOt1QDgZb7+/c13JyFsrfvksCS6YQDAqAgxCEvO3TAT07igFwCMiBCDsOTcDXPDpXTDAIAREWIQluiGAQDjI8Qg7NANAwChgRCDsGPvhrmAbhgAMDRCDMKOfZQ0kW4YADA0QgzCysHKGm3bf0wmk3RzWp9ALwcAcA4IMQgrzt0wvcx0wwCAkRFiEDacu2G4oBcAjI8Qg7BBNwwAhBZCDMLGD90wvRXdgW4YADA6QgzCgms3DBf0AkAoIMQgLNANAwChhxCDsEA3DACEHkIMQh7dMAAQmggxCHl0wwBAaCLEIKTRDQMAoYsQg5BGNwwAhC5CDEIa3TAAELoIMQhZrt0wjJIAINQQYhCyXLthugR6OQAALyPEIGTRDQMAoY0Qg5BENwwAhD5CDEIS3TAAEPoIMQg5dMMAQHggxCDk0A0DAOGBEIOQQzcMAIQHQgxCCt0wABA+CDEIKXTDAED4IMQgpNANAwDhw6MQs3TpUiUlJSk6Olrp6enavHlzm4778MMP1b59ew0ZMsSTlwVaRTcMAIQXt0PMmjVrNHfuXM2fP187duzQqFGjlJWVpdLS0laPq66u1tSpU3Xttdd6vFigNXTDAEB4cTvELFq0SNOnT9eMGTOUkpKixYsXKyEhQcuWLWv1uHvuuUeTJ0/WiBEjPF4s0BK6YQAg/LgVYurq6lRcXKzMzEyX7ZmZmSosLGzxuJUrV+qrr77SI4880qbXqa2tldVqdXkAraEbBgDCj1shpqKiQvX19YqPj3fZHh8fr/Ly8maP+fLLLzVv3jytXr1a7du3b9Pr5Obmymw2Ox4JCQnuLBNhiG4YAAg/Hl3Ye+ZdHzabrdk7Qerr6zV58mQtWLBAF198cZufPycnR9XV1Y5HWVmZJ8tEmKAbBgDCU9tOjXwvLi5OERERTc66HD16tMnZGUk6fvy4ioqKtGPHDs2aNUuS1NDQIJvNpvbt2+udd97RNddc0+S4qKgoRUVFubM0hDG6YQAgPLl1JiYyMlLp6ekqKChw2V5QUKCMjIwm+8fGxmrXrl0qKSlxPGbOnKnk5GSVlJRo+PDh57Z6QHTDAEC4cutMjCRlZ2drypQpGjZsmEaMGKEXX3xRpaWlmjlzpqTGUdDhw4f10ksvqV27dkpNTXU5vkePHoqOjm6yHfAE3TAAEL7cDjGTJk1SZWWlFi5cKIvFotTUVOXn5ysxMVGSZLFYztoZA3iL/bZqumEAIPyYbDabLdCLOBur1Sqz2azq6mrFxsYGejkIEg0NNo166j0d/vY7PXv7EP10CGdiACCY+Pr3N9+dBMPauu/7bphoumEAIBwRYmBY9gt6x9MNAwBhiRADQzpRe1pvf9Z4q//ENLphACAcEWJgSPk76YYBgHBHiIEh0Q0DACDEwHAOVNRo2wG6YQAg3BFiYDjrP6EbBgBAiIHBNDTYtO6Tw5KkW4fx7eYAEM4IMTAU526YzIFNv3QUABA+CDEwFLphAAB2hBgYxvF/n1L+ZxZJ0i3pdMMAQLgjxMAw3t5Vrn+fatAF3TtpaEKXQC8HABBghBgYhn2UdAvdMAAAEWJgEAcrnbphhjJKAgAQYmAQ9tuqRw3orp7m6ACvBgAQDAgxCHoNDTatcxolAQAgEWJgAFv30w0DAGiKEIOgRzcMAKA5hBgEtRO1p/X2rnJJjJIAAK4IMQhq+bss+u5UPd0wAIAmCDEIanTDAABaQohB0DpYWaNt+4+pHd0wAIBmEGIQtOzdMFfRDQMAaAYhBkGJbhgAwNkQYhCU6IYBAJwNIQZBiW4YAMDZEGIQdOiGAQC0BSEGQSd/J90wAICzI8Qg6NANAwBoC0IMgsqBihptO0A3DADg7AgxCCrrP2k8C0M3DADgbDwKMUuXLlVSUpKio6OVnp6uzZs3t7jvli1bNHLkSHXr1k0xMTG65JJL9Pvf/97jBSN0NTTYHAV3XNALADib9u4esGbNGs2dO1dLly7VyJEj9cILLygrK0u7d+9Wv379muzfqVMnzZo1S5dddpk6deqkLVu26J577lGnTp3085//3CtvAqFh6z66YQAAbWey2Ww2dw4YPny40tLStGzZMse2lJQUTZgwQbm5uW16jptvvlmdOnXSn//85zbtb7VaZTabVV1drdjYWHeWCwPJXlOi9TsO62fD++m/bxoU6OUAAM6Rr39/u3Umpq6uTsXFxZo3b57L9szMTBUWFrbpOXbs2KHCwkI99thjLe5TW1ur2tpax5+tVqskacryj9UhppM7S4aB7DxcLYlREgCgbdwKMRUVFaqvr1d8vOup/vj4eJWXl7d6bN++ffXNN9/o9OnTevTRRzVjxowW983NzdWCBQuabN9R9q3aRdW5s2QYzCU9O2sI3TAAgDZw+5oYSU26O2w221n7PDZv3qwTJ05o69atmjdvni666CLdcccdze6bk5Oj7Oxsx5+tVqsSEhL0+0mD1em8zp4sGYZgUnri+XTDAADaxK0QExcXp4iIiCZnXY4ePdrk7MyZkpKSJEmDBg3S119/rUcffbTFEBMVFaWoqKgm268f2JNrYgAAgCQ3b7GOjIxUenq6CgoKXLYXFBQoIyOjzc9js9lcrnkBAABwl9vjpOzsbE2ZMkXDhg3TiBEj9OKLL6q0tFQzZ86U1DgKOnz4sF566SVJ0nPPPad+/frpkksukdTYG/PMM89o9uzZXnwbAAAg3LgdYiZNmqTKykotXLhQFotFqampys/PV2JioiTJYrGotLTUsX9DQ4NycnK0f/9+tW/fXhdeeKGeeOIJ3XPPPd57FwAAIOy43RMTCPTEAABgPL7+/c13JwEAAEMixAAAAEMixAAAAEMixAAAAEMixAAAAEMixAAAAEMixAAAAEMixAAAAEMixAAAAENy+2sHAsFeKmy1WgO8EgAA0Fb239u++nIAQ4SYyspKSVJCQkKAVwIAANxVWVkps9ns9ec1RIjp2rWrJKm0tNRr/xIuv/xybd++3SvPFayvabT3aLValZCQoLKysjZ/xwb/To3/ep587ueKz9H/r+mLzznY3mMovJ63X7O6ulr9+vVz/B73NkOEmHbtGi/dMZvNXvuPPyIiwu9fJunv1zTqe4yNjW3zc/Dv1PivZ+fO536u+BwD95re/JyD9T0a+fV89Zr23+PeFrYX9t53330h/5q8R+O/XiBeMxDv0d/4HEPjNXmPofOanjLZfHW1jRf5+qu8ERz4nMMTn3t44HMOT77+3A1xJiYqKkqPPPKIoqKiAr0U+BCfc3jicw8PfM7hydefuyHOxAAAAJzJEGdiAAAAzkSIAQAAhkSIAQAAhkSIAQAEjMlk0ptvvhnoZcCggiLEFBYWKiIiQjfeeGOglwIvmjZtmkwmk2bOnNnkZ/fee69MJpOmTZvm/4XBb6ZNm6YJEyYEehnwIz7z8BAsv7eDIsTk5eVp9uzZ2rJli0pLS8/puerr69XQ0OClleFcJSQk6LXXXtN3333n2Pbvf/9br776qvr16xfAlQEAPOXN39vnIuAhpqamRv/7v/+r//qv/9K4ceO0atUqx882bdokk8mkt956S4MHD1Z0dLSGDx+uXbt2OfZZtWqVunTpor/97W8aOHCgoqKidPDgwQC8EzQnLS1N/fr10/r16x3b1q9fr4SEBA0dOtSxbePGjbrqqqvUpUsXdevWTePGjdNXX33l+Pk111yjWbNmuTx3ZWWloqKi9I9//MP3bwTnrH///lq8eLHLtiFDhujRRx91/NlkMmn58uW66aab1LFjRw0YMEAbNmzw70LhNW35zGE8rf3etv9Odvbmm2/KZDK5bHvsscfUo0cPde7cWTNmzNC8efM0ZMgQt9cS8BCzZs0aJScnKzk5WXfeeadWrlzZ5Cu7H3zwQT3zzDPavn27evTooZ/85Cc6deqU4+cnT55Ubm6uli9frs8//1w9evTw99tAK+666y6tXLnS8ee8vDzdfffdLvvU1NQoOztb27dv17vvvqt27drppptucpxVmzFjhl555RXV1tY6jlm9erV69+6t0aNH++eNwC8WLFig2267TTt37tSYMWP0s5/9TMeOHQv0sgB8ry2/t1uzevVq/fd//7eefPJJFRcXq1+/flq2bJlHawl4iFmxYoXuvPNOSdKNN96oEydO6N1333XZ55FHHtH111+vQYMG6U9/+pO+/vprvfHGG46fnzp1SkuXLlVGRoaSk5PVqVMnv74HtG7KlCnasmWLDhw4oIMHD+rDDz90fOZ2EydO1M0336wBAwZoyJAhWrFihXbt2qXdu3c7fm4ymfSXv/zFcczKlSsd190gdEybNk133HGHLrroIj3++OOqqanRtm3bAr0sAN9ry+/t1vzhD3/Q9OnTddddd+niiy/Www8/rEGDBnm0loCGmL1792rbtm26/fbbJUnt27fXpEmTlJeX57LfiBEjHP/ctWtXJScna8+ePY5tkZGRuuyyy/yzaLgtLi5OY8eO1Z/+9CetXLlSY8eOVVxcnMs+X331lSZPnqwLLrhAsbGxSkpKkiTHrDUqKkp33nmn47+NkpISffrpp1wYHIKc/7fcqVMnde7cWUePHg3gigDYtfX39tme44orrnDZduaf26q9R0d5yYoVK3T69Gn16dPHsc1ms6lDhw6qqqpq9Vjnv33HxMTwt/Egd/fddzuuaXnuueea/Hz8+PFKSEjQH//4R/Xu3VsNDQ1KTU1VXV2dY58ZM2ZoyJAhOnTokPLy8nTttdcqMTHRb+8B56Zdu3ZNTjk7j4XtOnTo4PJnk8nExfoG1dbPHMZxtt/bbf3Mz/yd7ek3IAXsTMzp06f10ksv6Xe/+51KSkocj08//VSJiYlavXq1Y9+tW7c6/rmqqkpffPGFLrnkkkAsGx668cYbVVdXp7q6Ot1www0uP6usrNSePXv061//Wtdee61SUlKaDbGDBg3SsGHD9Mc//lGvvPJKk+tqENy6d+8ui8Xi+LPVatX+/fsDuCL4Gp95aGnL7+3u3bvr+PHjqqmpcRxXUlLi8jzJyclNRsRFRUUerSlgZ2L+9re/qaqqStOnT5fZbHb52S233KIVK1bo97//vSRp4cKF6tatm+Lj4zV//nzFxcXRQ2AwERERjhFgRESEy8/OP/98devWTS+++KJ69eql0tJSzZs3r9nnmTFjhmbNmqWOHTvqpptu8vm64T3XXHONVq1apfHjx+v888/Xb37zmyb/LSC08JmHlrb83n733XfVsWNHPfTQQ5o9e7a2bdvmcveSJM2ePVv/+Z//qWHDhikjI0Nr1qzRzp07dcEFF7i9poCdiVmxYoWuu+66Jv8ipMaLOEtKSvTJJ59Ikp544gn94he/UHp6uiwWizZs2KDIyEh/LxnnKDY2VrGxsU22t2vXTq+99pqKi4uVmpqq+++/X08//XSzz3HHHXeoffv2mjx5sqKjo329ZJyjhoYGtW/f+HelnJwcXX311Ro3bpzGjBmjCRMm6MILLwzwCuFtfOahqy2/tw8cOKCXX35Z+fn5GjRokF599dUmt9T/7Gc/U05Ojh544AGlpaVp//79mjZtmkf/n26yeTqI8oNNmzZp9OjRqqqqanLfOcJTWVmZ+vfvr+3btystLS3Qy8FZ3Hjjjbrooou0ZMmSQC8FfsJnDk9cf/316tmzp/785z+7dVxAL+wF2urUqVOyWCyaN2+errzySgJMkKuqqlJhYaE2bdrU7NdOIPTwmaOtTp48qeeff1433HCDIiIi9Oqrr+r//u//VFBQ4PZzEWJgCB9++KFGjx6tiy++WGvXrg30cnAWd999t7Zv365f/vKX+ulPfxro5cAP+MzRViaTSfn5+XrsscdUW1ur5ORkrVu3Ttddd537zxXM4yQAAICWBLyxFwAAwBOEGAAAYEiEGAAAYEh+CTG5ubm6/PLL1blzZ/Xo0UMTJkzQ3r17Xfax2Wx69NFH1bt3b8XExOjHP/6xPv/8c8fPjx07ptmzZys5OVkdO3ZUv379NGfOHFVXV7s8T1VVlaZMmSKz2Syz2awpU6bo22+/9cfbBAAAfuSXEPP+++/rvvvu09atW1VQUKDTp08rMzPTpZb4qaee0qJFi7RkyRJt375dPXv21PXXX6/jx49Lko4cOaIjR47omWee0a5du7Rq1Spt3LhR06dPd3mtyZMnq6SkRBs3btTGjRtVUlKiKVOm+ONtAgAAPwrI3UnffPONevTooffff19XX321bDabevfurblz5+pXv/qVJKm2tlbx8fF68skndc899zT7PK+//rruvPNO1dTUqH379tqzZ48GDhyorVu3avjw4ZIav3dpxIgR+uc//6nk5GS/vUcAAOBbAbkmxj4C6tq1qyRp//79Ki8vV2ZmpmOfqKgo/ehHP1JhYWGrzxMbG+uouP7oo49kNpsdAUaSrrzySpnN5lafBwAAGI/fQ4zNZlN2drauuuoqpaamSpLKy8slSfHx8S77xsfHO352psrKSv32t791OUtTXl6uHj16NNm3R48eLT4PAAAwJr839s6aNUs7d+7Uli1bmvzMZDK5/NlmszXZJjV+nfvYsWM1cOBAPfLII60+R2vPAwAAjMuvZ2Jmz56tDRs26L333lPfvn0d23v27ClJTc6WHD16tMnZmePHj+vGG2/UeeedpzfeeEMdOnRweZ6vv/66yet+8803TZ4HAAAYm19CjM1m06xZs7R+/Xr94x//UFJSksvPk5KS1LNnT5cvf6qrq9P777+vjIwMxzar1arMzExFRkZqw4YNTb62e8SIEaqurta2bdsc2z7++GNVV1e7PA8AADA+v9yddO+99+qVV17RX/7yF5c7hMxms2JiYiRJTz75pHJzc7Vy5UoNGDBAjz/+uDZt2qS9e/eqc+fOOn78uK6//nqdPHlSb7zxhjp16uR4nu7duysiIkKSlJWVpSNHjuiFF16QJP385z9XYmKi/vrXv/r6bQIAAD/yS4hp6XqUlStXatq0aZIaz9YsWLBAL7zwgqqqqjR8+HA999xzjot/N23apNGjRzf7PPv371f//v0lNZbizZkzRxs2bJAk/eQnP9GSJUvUpUsXr74nAAAQWHyLNQAAMCS+OwkAABgSIQYAABgSIQYAABgSIQYAABgSIQYAABgSIQYAABgSIQYAABgSIQYAABgSIQYAABgSIQYAABgSIQYAABjS/wd0oUKUGegNIQAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "kc = pd.Series(index=[crop_ini, crop_dev, mid_season, late_s_start, late_s_end],\n", - " data=[Kcini, Kcini, Kcmid, Kcmid, Kcend])\n", - "kc = kc.resample(\"d\").mean().interpolate()\n", - "kc.plot()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "c73067c3-2d7e-4bb4-8cff-91f707f7c34b", - "metadata": {}, - "outputs": [], - "source": [ - "petc = pet_pm.loc[crop_dev:late_s_end] * kc" - ] - }, - { - "cell_type": "markdown", - "id": "e6e2564c-48ed-46b7-a275-fd17db592456", - "metadata": { - "pycharm": { - "name": "#%% md\n" - } - }, - "source": [ - "### Plot results" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "c9a4582f-219b-47f8-9ed2-dac80720cf55", - "metadata": { - "pycharm": { - "name": "#%%\n" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pet_pm.loc[crop_dev:late_s_end].plot(label=\"Potential evapotranspiration\")\n", - "petc.loc[crop_dev:late_s_end].plot(label=\"Potential crop evapotranspiration\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/data/example_0/df_Guo_2016.xlsx b/examples/data/example_0/df_Guo_2016.xlsx deleted file mode 100644 index 039db23..0000000 Binary files a/examples/data/example_0/df_Guo_2016.xlsx and /dev/null differ diff --git a/examples/data/example_0/fg_ens_mean_0.25deg_reg_2018_v25.0e.nc 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b/examples/figure2.png deleted file mode 100644 index 426d87a..0000000 Binary files a/examples/figure2.png and /dev/null differ diff --git a/pyet/__init__.py b/pyet/__init__.py index 1014bb2..23324b8 100644 --- a/pyet/__init__.py +++ b/pyet/__init__.py @@ -1,7 +1,51 @@ -from .combination import * -from .temperature import * -from .radiation import * -from .meteo_utils import * -from .rad_utils import * +from .combination import ( + penman, + pm_asce, + pm, + pm_fao56, + priestley_taylor, + kimberly_penman, + thom_oliver, + calculate_all, +) +from .temperature import blaney_criddle, haude, hamon, romanenko, linacre +from .radiation import ( + turc, + jensen_haise, + mcguinness_bordne, + hargreaves, + fao_24, + abtew, + makkink, + makkink_knmi, + oudin, +) +from .meteo_utils import ( + calc_psy, + calc_vpc, + calc_lambda, + calc_press, + calc_rho, + calc_e0, + calc_es, + calc_ea, + extraterrestrial_r, + calc_res_surf, + calc_laieff, + calc_res_aero, + relative_distance, + solar_declination, + sunset_angle, + day_of_year, + daylight_hours, +) + +from .rad_utils import ( + calc_rad_net, + calc_rad_long, + calc_rad_short, + calc_rad_sol_in, + calc_rso, +) from .version import __version__ from .utils import show_versions diff --git a/pyet/combination.py b/pyet/combination.py index 5340771..57ec524 100644 --- a/pyet/combination.py +++ b/pyet/combination.py @@ -1,93 +1,136 @@ """The combination module contains functions of combination PE methods """ + import pandas -from .meteo_utils import * -from .rad_utils import * -from .temperature import * -from .radiation import * -from .utils import * +from numpy import exp, newaxis + +from .meteo_utils import ( + calc_lambda, + calc_press, + calc_psy, + calc_vpc, + calc_ea, + calc_es, + calc_rho, + calc_res_surf, + calc_res_aero, + day_of_year, +) +from .radiation import ( + jensen_haise, + turc, + mcguinness_bordne, + hargreaves, + fao_24, + abtew, + makkink, + oudin, +) +from .temperature import blaney_criddle, romanenko, linacre, haude, hamon +from .rad_utils import calc_rad_net +from .utils import clip_zeros, get_index, check_rh, pet_out # Specific heat of air [MJ kg-1 °C-1] -CP = 1.013 * 10 ** -3 +CP = 1.013 * 10**-3 # Stefan Boltzmann constant - hourly [MJm-2K-4h-1] -STEFAN_BOLTZMANN_HOUR = 2.042 * 10 ** -10 +STEFAN_BOLTZMANN_HOUR = 2.042 * 10**-10 # Stefan Boltzmann constant - daily [MJm-2K-4d-1] -STEFAN_BOLTZMANN_DAY = 4.903 * 10 ** -9 - - -def penman(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, - rhmax=None, rhmin=None, rh=None, pressure=None, elevation=None, - lat=None, n=None, nn=None, rso=None, aw=1, bw=0.537, a=1.35, - b=-0.35, ea=None, albedo=0.23, kab=None, as1=0.25, bs1=0.5, - ku=6.43, clip_zero=True): +STEFAN_BOLTZMANN_DAY = 4.903 * 10**-9 + + +def penman( + tmean, + wind, + rs=None, + rn=None, + g=0, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + pressure=None, + elevation=None, + lat=None, + n=None, + nn=None, + rso=None, + aw=1, + bw=0.537, + a=1.35, + b=-0.35, + ea=None, + albedo=0.23, + kab=None, + as1=0.25, + bs1=0.5, + clip_zero=True, +): """Potential evapotranspiration calculated according to :cite:t:`penman_natural_1948`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - wind: float/pandas.Series/xarray.DataArray - mean day wind speed [m/s] - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] - rn: float/pandas.Series/xarray.DataArray, optional - net radiation [MJ m-2 d-1] - g: float/pandas.Series/xarray.DataArray, optional - soil heat flux [MJ m-2 d-1] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] - pressure: float/pandas.Series/xarray.DataArray, optional - atmospheric pressure [kPa] - elevation: float/xarray.DataArray, optional - the site elevation [m] - lat: float/xarray.DataArray, optional - the site latitude [rad] - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] - rso: float/pandas.Series/xarray.DataArray, optional - clear-sky solar radiation [MJ m-2 day-1] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + wind: float or pandas.Series or xarray.DataArray + mean day wind speed [m/s]. + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. + rn: float or pandas.Series or xarray.DataArray, optional + net radiation [MJ m-2 d-1]. + g: float or pandas.Series or xarray.DataArray, optional + soil heat flux [MJ m-2 d-1]. + tmax: float or pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: float or pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: float or pandas.Series or xarray.DataArray, optional + mean daily relative humidity [%]. + pressure: float or pandas.Series or xarray.DataArray, optional + atmospheric pressure [kPa]. + elevation: float or xarray.DataArray, optional + the site elevation [m]. + lat: float or xarray.DataArray, optional + the site latitude [rad]. + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. + rso: float or pandas.Series or xarray.DataArray, optional + clear-sky solar radiation [MJ m-2 day-1]. aw: float, optional - wind coefficient [-] + wind coefficient [-]. bw: float, optional - wind coefficient [-] + wind coefficient [-]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] - ea: float/pandas.Series/xarray.DataArray, optional - actual vapor pressure [kPa] + empirical coefficient for Net Long-Wave radiation [-]. + ea: float or pandas.Series or xarray.DataArray, optional + actual vapor pressure [kPa]. albedo: float, optional - surface albedo [-] + surface albedo [-]. kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] - ku: float, optional - unit conversion factor [MJm−2 t−1 kPa−1] + empirical coefficient for extraterrestrial radiation [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -95,110 +138,143 @@ def penman(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, Notes ----- - Following :cite:t:`penman_natural_1948` and - :cite:t:`valiantzas_simplified_2006`. + Following :cite:t:`penman_natural_1948` and :cite:t:`valiantzas_simplified_2006`. - .. math:: PET = \\frac{\\Delta (R_n-G) + \\gamma 2.6 (1 + 0.536 u_2) - (e_s-e_a)}{\\lambda (\\Delta +\\gamma)} + .. math:: PET = \\frac{\\frac{\\Delta (R_n-G)}{\\lambda} + + \\gamma (a_w + b_w u_2) (e_s-e_a)}{(\\Delta +\\gamma)} """ - pressure = calc_press(elevation, pressure) - gamma = calc_psy(pressure) - dlt = calc_vpc(tmean) - lambd = calc_lambda(tmean) - - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=check_rh(rhmax), - rhmin=check_rh(rhmin), rh=check_rh(rh), ea=ea) - es = calc_es(tmean=tmean, tmax=tmax, tmin=tmin) - - rn = calc_rad_net(tmean, rn, rs, check_lat(lat), n, nn, tmax, tmin, rhmax, - rhmin, rh, elevation, rso, a, b, ea, albedo, as1, bs1, - kab) - - fu = ku * (aw + bw * wind) - - den = lambd * (dlt + gamma) - num1 = dlt * (rn - g) / den + pressure, gamma, dlt, lambd, ea, es = _lambda_gamma_dlt_ea_es( + elevation, pressure, tmean, tmax, tmin, rhmax, rhmin, rh, ea + ) + rn = calc_rad_net( + tmean, + rn, + rs, + lat, + n, + nn, + tmax, + tmin, + rhmax, + rhmin, + rh, + elevation, + rso, + a, + b, + ea, + albedo, + as1, + bs1, + kab, + ) + fu = aw + bw * wind + + den = dlt + gamma + num1 = dlt * (rn - g) / den / lambd num2 = gamma * (es - ea) * fu / den pet = num1 + num2 pet = clip_zeros(pet, clip_zero) - return pet.rename("Penman") - - -def pm_asce(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, - rhmax=None, rhmin=None, rh=None, pressure=None, elevation=None, - lat=None, n=None, nn=None, rso=None, a=1.35, b=-0.35, cn=900, - cd=0.34, ea=None, albedo=0.23, kab=None, as1=0.25, bs1=0.5, - clip_zero=True, etype="os"): + return pet_out(tmean, pet, "Penman") + + +def pm_asce( + tmean, + wind, + rs=None, + rn=None, + g=0, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + pressure=None, + elevation=None, + lat=None, + n=None, + nn=None, + rso=None, + a=1.35, + b=-0.35, + cn=900, + cd=0.34, + ea=None, + albedo=0.23, + kab=None, + as1=0.25, + bs1=0.5, + clip_zero=True, + etype="os", +): """Potential evapotranspiration calculated according to :cite:t:`monteith_evaporation_1965`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - wind: float/pandas.Series/xarray.DataArray - mean day wind speed [m/s] - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] - rn: float/pandas.Series/xarray.DataArray, optional - net radiation [MJ m-2 d-1] - g: float/pandas.Series/xarray.DataArray, optional - soil heat flux [MJ m-2 d-1] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] - pressure: float/xarray.DataArray, optional - atmospheric pressure [kPa] - elevation: float/xarray.DataArray, optional - the site elevation [m] - lat: float/xarray.DataArray, optional - the site latitude [rad] - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] - rso: float/pandas.Series/xarray.DataArray, optional - clear-sky solar radiation [MJ m-2 day-1] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + wind: float or pandas.Series or xarray.DataArray + mean day wind speed [m/s]. + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. + rn: float or pandas.Series or xarray.DataArray, optional + net radiation [MJ m-2 d-1]. + g: float or pandas.Series or xarray.DataArray, optional + soil heat flux [MJ m-2 d-1]. + tmax: float or pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: float or pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: float or pandas.Series or xarray.DataArray, optional + mean daily relative humidity [%]. + pressure: float or xarray.DataArray, optional + atmospheric pressure [kPa]. + elevation: float or xarray.DataArray, optional + the site elevation [m]. + lat: float or xarray.DataArray, optional + the site latitude [rad]. + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. + rso: float or pandas.Series or xarray.DataArray, optional + clear-sky solar radiation [MJ m-2 day-1]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. cn: float, optional - numerator constant [K mm s3 Mg-1 d-1] + numerator constant [K mm s3 Mg-1 d-1]. cd: float, optional - denominator constant [s m-1] - ea: pandas.Series/float, optional - actual vapor pressure [kPa] + denominator constant [s m-1]. + ea: pandas.Series or float, optional + actual vapor pressure [kPa]. albedo: float, optional - surface albedo [-] + surface albedo [-]. kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] + empirical coefficient for extraterrestrial radiation [-]. clip_zero: bool, optional if True, replace all negative values with 0. etype: str, optional - "os" => ASCE-PM method is applied for a reference surfaces - representing clipped grass (a short, smooth crop) - "rs" => ASCE-PM method is applied for a reference surfaces - representing alfalfa (a taller, rougher agricultural crop),) + "os" => ASCE-PM method is applied for a reference surfaces representing + clipped grass (a short, smooth crop). "rs" => ASCE-PM method is applied for a + reference surfaces representing alfalfa (a taller, rougher agricultural crop),). Returns ------- - pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -206,23 +282,37 @@ def pm_asce(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, Notes ----- - Following :cite:t:`monteith_evaporation_1965` and - :cite:t:`walter_asces_2000` + Following :cite:t:`monteith_evaporation_1965` and :cite:t:`walter_asces_2000` .. math:: PET = \\frac{\\Delta (R_{n}-G)+ \\rho_a c_p K_{min} \\frac{e_s-e_a}{r_a}}{\\lambda(\\Delta +\\gamma(1+\\frac{r_s}{r_a}))} """ - pressure = calc_press(elevation, pressure) - gamma = calc_psy(pressure) - dlt = calc_vpc(tmean) - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=check_rh(rhmax), - rhmin=check_rh(rhmin), rh=check_rh(rh), ea=ea) - es = calc_es(tmean=tmean, tmax=tmax, tmin=tmin) - rn = calc_rad_net(tmean, rn, rs, check_lat(lat), n, nn, tmax, tmin, rhmax, - rhmin, rh, elevation, rso, a, b, ea, albedo, as1, bs1, - kab) - + pressure, gamma, dlt, lambd, ea, es = _lambda_gamma_dlt_ea_es( + elevation, pressure, tmean, tmax, tmin, rhmax, rhmin, rh, ea + ) + rn = calc_rad_net( + tmean, + rn, + rs, + lat, + n, + nn, + tmax, + tmin, + rhmax, + rhmin, + rh, + elevation, + rso, + a, + b, + ea, + albedo, + as1, + bs1, + kab, + ) if etype == "rs": cn = 1600 cd = 0.38 @@ -232,99 +322,129 @@ def pm_asce(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, num2 = gamma * cn / (tmean + 273) * wind * (es - ea) / den pet = num1 + num2 pet = clip_zeros(pet, clip_zero) - return pet.rename("PM_ASCE") - - -def pm(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, rhmax=None, - rhmin=None, rh=None, pressure=None, elevation=None, lat=None, n=None, - nn=None, rso=None, ea=None, a=1.35, b=-0.35, lai=None, croph=0.12, - r_l=100, r_s=None, ra_method=0, a_sh=1, a_s=1, lai_eff=0, srs=0.0009, - co2=300, albedo=0.23, kab=None, as1=0.25, bs1=0.5, clip_zero=True): + return pet_out(tmean, pet, "PM_ASCE") + + +def pm( + tmean, + wind, + rs=None, + rn=None, + g=0, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + pressure=None, + elevation=None, + lat=None, + n=None, + nn=None, + rso=None, + ea=None, + a=1.35, + b=-0.35, + lai=None, + croph=0.12, + r_l=100, + r_s=None, + ra_method=0, + a_sh=1, + a_s=1, + lai_eff=0, + srs=0.0009, + co2=300, + albedo=0.23, + kab=None, + as1=0.25, + bs1=0.5, + clip_zero=True, +): """Potential evapotranspiration calculated according to :cite:t:`monteith_evaporation_1965`. Parameters ---------- - tmean: float/xarray.DataArray - average day temperature [°C] - wind: float/pandas.Series/xarray.DataArray - mean day wind speed [m/s] - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] - rn: float/pandas.Series/xarray.DataArray, optional - net radiation [MJ m-2 d-1] - g: float/pandas.Series/xarray.DataArray, optional - soil heat flux [MJ m-2 d-1] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] - pressure: float/xarray.DataArray, optional - atmospheric pressure [kPa] - elevation: float/xarray.DataArray, optional - the site elevation [m] - lat: float/xarray.DataArray, optional - the site latitude [rad] - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] - rso: float/pandas.Series/xarray.DataArray, optional - clear-sky solar radiation [MJ m-2 day-1] - ea: float/pandas.Series/xarray.DataArray, optional - actual vapor pressure [kPa] + tmean: float or xarray.DataArray + average day temperature [°C]. + wind: float or pandas.Series or xarray.DataArray + mean day wind speed [m/s]. + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. + rn: float or pandas.Series or xarray.DataArray, optional + net radiation [MJ m-2 d-1]. + g: float or pandas.Series or xarray.DataArray, optional + soil heat flux [MJ m-2 d-1]. + tmax: float or pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: float or pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: float or pandas.Series or xarray.DataArray, optional + mean daily relative humidity [%]. + pressure: float or xarray.DataArray, optional + atmospheric pressure [kPa]. + elevation: float or xarray.DataArray, optional + the site elevation [m]. + lat: float or xarray.DataArray, optional + the site latitude [rad]. + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. + rso: float or pandas.Series or xarray.DataArray, optional + clear-sky solar radiation [MJ m-2 day-1]. + ea: float or pandas.Series or xarray.DataArray, optional + actual vapor pressure [kPa]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] - lai: float/pandas.Series/xarray.DataArray, optional - leaf area index [-] - croph: float/pandas.Series/xarray.DataArray, optional - crop height [m] - r_l: pandas.series/float, optional - bulk stomatal resistance [s m-1] - r_s: pandas.series/float, optional - bulk surface resistance [s m-1] + empirical coefficient for Net Long-Wave radiation [-]. + lai: float or pandas.Series or xarray.DataArray, optional + leaf area index [-]. + croph: float or pandas.Series or xarray.DataArray, optional + crop height [m]. + r_l: pandas.Series or float, optional + bulk stomatal resistance [s m-1]. + r_s: pandas.Series or float, optional + bulk surface resistance [s m-1]. ra_method: float, optional 0 => ra = 208/wind 1 => ra is calculated based on equation 36 in FAO (1990), ANNEX V. a_s: float, optional Fraction of one-sided leaf area covered by stomata (1 if stomata are 1 - on one side only, 2 if they are on both sides) + on one side only, 2 if they are on both sides). a_sh: float, optional - Fraction of projected area exchanging sensible heat with the air (2) + Fraction of projected area exchanging sensible heat with the air (2). lai_eff: float, optional 0 => LAI_eff = 0.5 * LAI 1 => LAI_eff = lai / (0.3 * lai + 1.2) 2 => LAI_eff = 0.5 * LAI; (LAI>4=4) 3 => see :cite:t:`zhang_comparison_2008`. - srs: float/pandas.Series/xarray.DataArray, optional - Relative sensitivity of rl to Δ[CO2] - co2: float/pandas.Series/xarray.DataArray, optional - CO2 concentration [ppm] + srs: float or pandas.Series or xarray.DataArray, optional + Relative sensitivity of rl to Δ[CO2]. + co2: float or pandas.Series or xarray.DataArray, optional + CO2 concentration [ppm]. albedo: float, optional - surface albedo [-] + surface albedo [-]. kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] + empirical coefficient for extraterrestrial radiation [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -356,23 +476,38 @@ def pm(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, rhmax=None, \\frac{log(\\frac{(zh - d)}{zoh})}{(0.41^2)u_2} """ - pressure = calc_press(elevation, pressure) - gamma = calc_psy(pressure) - dlt = calc_vpc(tmean) - lambd = calc_lambda(tmean) - - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=check_rh(rhmax), - rhmin=check_rh(rhmin), rh=check_rh(rh), ea=ea) - es = calc_es(tmean=tmean, tmax=tmax, tmin=tmin) + pressure, gamma, dlt, lambd, ea, es = _lambda_gamma_dlt_ea_es( + elevation, pressure, tmean, tmax, tmin, rhmax, rhmin, rh, ea + ) res_a = calc_res_aero(wind, ra_method=ra_method, croph=croph) - res_s = calc_res_surf(lai=lai, r_s=r_s, r_l=r_l, lai_eff=lai_eff, srs=srs, - co2=co2, croph=croph) + res_s = calc_res_surf( + lai=lai, r_s=r_s, r_l=r_l, lai_eff=lai_eff, srs=srs, co2=co2, croph=croph + ) gamma1 = gamma * a_sh / a_s * (1 + res_s / res_a) - rn = calc_rad_net(tmean, rn, rs, check_lat(lat), n, nn, tmax, tmin, rhmax, - rhmin, rh, elevation, rso, a, b, ea, albedo, as1, bs1, - kab) + rn = calc_rad_net( + tmean, + rn, + rs, + lat, + n, + nn, + tmax, + tmin, + rhmax, + rhmin, + rh, + elevation, + rso, + a, + b, + ea, + albedo, + as1, + bs1, + kab, + ) kmin = 86400 # unit conversion s d-1 rho_a = calc_rho(pressure, tmean, ea) @@ -382,73 +517,94 @@ def pm(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, rhmax=None, num2 = rho_a * CP * kmin * (es - ea) * a_sh / res_a / den pet = num1 + num2 pet = clip_zeros(pet, clip_zero) - return pet.rename("Penman_Monteith") - - -def pm_fao56(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, - rhmax=None, rhmin=None, rh=None, pressure=None, elevation=None, - lat=None, n=None, nn=None, rso=None, a=1.35, b=-0.35, ea=None, - albedo=0.23, kab=None, as1=0.25, bs1=0.5, clip_zero=True): + return pet_out(tmean, pet, "Penman_Monteith") + + +def pm_fao56( + tmean, + wind, + rs=None, + rn=None, + g=0, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + pressure=None, + elevation=None, + lat=None, + n=None, + nn=None, + rso=None, + a=1.35, + b=-0.35, + ea=None, + albedo=0.23, + kab=None, + as1=0.25, + bs1=0.5, + clip_zero=True, +): """Potential evapotranspiration calculated according to :cite:t:`allen_crop_1998`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - wind: float/pandas.Series/xarray.DataArray - mean day wind speed [m/s] - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] - rn: float/pandas.Series/xarray.DataArray, optional - net radiation [MJ m-2 d-1] - g: float/pandas.Series/xarray.DataArray, optional - soil heat flux [MJ m-2 d-1] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray optional - mean daily relative humidity [%] - pressure: float/pandas.Series/xarray.DataArray, optional - atmospheric pressure [kPa] - elevation: float/xarray.DataArray, optional - the site elevation [m] - lat: float/xarray.DataArray, optional - the site latitude [rad] - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] - rso: float/pandas.Series/xarray.DataArray, optional - clear-sky solar radiation [MJ m-2 day-1] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + wind: float or pandas.Series or xarray.DataArray + mean day wind speed [m/s]. + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. + rn: float or pandas.Series or xarray.DataArray, optional + net radiation [MJ m-2 d-1]. + g: float or pandas.Series or xarray.DataArray, optional + soil heat flux [MJ m-2 d-1]. + tmax: float or pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: float or pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: float or pandas.Series or xarray.DataArray optional + mean daily relative humidity [%]. + pressure: float or pandas.Series or xarray.DataArray, optional + atmospheric pressure [kPa]. + elevation: float or xarray.DataArray, optional + the site elevation [m]. + lat: float or xarray.DataArray, optional + the site latitude [rad]. + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. + rso: float or pandas.Series or xarray.DataArray, optional + clear-sky solar radiation [MJ m-2 day-1]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] - ea: float/pandas.Series/xarray.DataArray, optional - actual vapor pressure [kPa] + empirical coefficient for Net Long-Wave radiation [-]. + ea: float or pandas.Series or xarray.DataArray, optional + actual vapor pressure [kPa]. albedo: float, optional - surface albedo [-] + surface albedo [-]. kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] + empirical coefficient for extraterrestrial radiation [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -462,91 +618,124 @@ def pm_fao56(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, """ if tmean is None: tmean = (tmax + tmin) / 2 - pressure = calc_press(elevation, pressure) - gamma = calc_psy(pressure) - dlt = calc_vpc(tmean) - - gamma1 = (gamma * (1 + 0.34 * wind)) - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=check_rh(rhmax), - rhmin=check_rh(rhmin), rh=check_rh(rh), ea=ea) - es = calc_es(tmean=tmean, tmax=tmax, tmin=tmin) - - rn = calc_rad_net(tmean, rn, rs, check_lat(lat), n, nn, tmax, tmin, rhmax, - rhmin, rh, elevation, rso, a, b, ea, albedo, as1, bs1, - kab) + pressure, gamma, dlt, lambd, ea, es = _lambda_gamma_dlt_ea_es( + elevation, pressure, tmean, tmax, tmin, rhmax, rhmin, rh, ea + ) + gamma1 = gamma * (1 + 0.34 * wind) + rn = calc_rad_net( + tmean, + rn, + rs, + lat, + n, + nn, + tmax, + tmin, + rhmax, + rhmin, + rh, + elevation, + rso, + a, + b, + ea, + albedo, + as1, + bs1, + kab, + ) den = dlt + gamma1 num1 = (0.408 * dlt * (rn - g)) / den num2 = (gamma * (es - ea) * 900 * wind / (tmean + 273)) / den pet = num1 + num2 pet = clip_zeros(pet, clip_zero) - return pet.rename("PM_FAO_56") - - -def priestley_taylor(tmean, rs=None, rn=None, g=0, tmax=None, tmin=None, - rhmax=None, rhmin=None, rh=None, pressure=None, - elevation=None, lat=None, n=None, nn=None, rso=None, - a=1.35, b=-0.35, alpha=1.26, albedo=0.23, kab=None, - as1=0.25, bs1=0.5, clip_zero=True): + return pet # pet_out(tmean, pet, "PM_FAO_56") + + +def priestley_taylor( + tmean, + rs=None, + rn=None, + g=0, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + pressure=None, + elevation=None, + lat=None, + n=None, + nn=None, + rso=None, + a=1.35, + b=-0.35, + alpha=1.26, + albedo=0.23, + kab=None, + as1=0.25, + bs1=0.5, + clip_zero=True, +): """Potential evapotranspiration calculated according to :cite:t:`priestley_assessment_1972`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] - rn: float/pandas.Series/xarray.DataArray, optional - net radiation [MJ m-2 d-1] - g: float/pandas.Series/xarray.DataArray, optional - soil heat flux [MJ m-2 d-1] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] - pressure: float/pandas.Series/xarray.DataArray, optional - atmospheric pressure [kPa] - elevation: float/xarray.DataArray, optional - the site elevation [m] - lat: float/xarray.DataArray, optional - the site latitude [rad] - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] - rso: float/pandas.Series/xarray.DataArray, optional - clear-sky solar radiation [MJ m-2 day-1] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. + rn: float or pandas.Series or xarray.DataArray, optional + net radiation [MJ m-2 d-1]. + g: float or pandas.Series or xarray.DataArray, optional + soil heat flux [MJ m-2 d-1]. + tmax: float or pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: float or pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: float or pandas.Series or xarray.DataArray, optional + mean daily relative humidity [%]. + pressure: float or pandas.Series or xarray.DataArray, optional + atmospheric pressure [kPa]. + elevation: float or xarray.DataArray, optional + the site elevation [m]. + lat: float or xarray.DataArray, optional + the site latitude [rad]. + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. + rso: float or pandas.Series or xarray.DataArray, optional + clear-sky solar radiation [MJ m-2 day-1]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. alpha: float, optional - calibration coeffiecient [-] + calibration coefficient [-]. albedo: float, optional - surface albedo [-] + surface albedo [-]. kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] + empirical coefficient for extraterrestrial radiation [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated pootential + evapotranspiration [mm d-1]. Examples -------- >>> pt = priestley_taylor(tmean, rn=rn, rh=rh) @@ -563,80 +752,118 @@ def priestley_taylor(tmean, rs=None, rn=None, g=0, tmax=None, tmin=None, dlt = calc_vpc(tmean) lambd = calc_lambda(tmean) - rn = calc_rad_net(tmean, rn, rs, check_lat(lat), n, nn, tmax, tmin, - check_rh(rhmax), check_rh(rhmin), check_rh(rh), - elevation, rso, a, b, None, albedo, as1, bs1, kab) + rn = calc_rad_net( + tmean, + rn, + rs, + lat, + n, + nn, + tmax, + tmin, + rhmax, + rhmin, + rh, + elevation, + rso, + a, + b, + None, + albedo, + as1, + bs1, + kab, + ) pet = (alpha * dlt * (rn - g)) / (lambd * (dlt + gamma)) pet = clip_zeros(pet, clip_zero) - return pet.rename("Priestley_Taylor") - - -def kimberly_penman(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, - rhmax=None, rhmin=None, rh=None, pressure=None, - elevation=None, lat=None, n=None, nn=None, rso=None, - a=1.35, b=-0.35, ea=None, albedo=0.23, kab=None, as1=0.25, - bs1=0.5, clip_zero=True): - """Potential evapotranspiration calculated according to - :cite:t:`wright_new_1982`. + return pet_out(tmean, pet, "Priestley_Taylor") + + +def kimberly_penman( + tmean, + wind, + rs=None, + rn=None, + g=0, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + pressure=None, + elevation=None, + lat=None, + n=None, + nn=None, + rso=None, + a=1.35, + b=-0.35, + ea=None, + albedo=0.23, + kab=None, + as1=0.25, + bs1=0.5, + clip_zero=True, +): + """Potential evapotranspiration calculated according to :cite:t:`wright_new_1982`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - wind: pandas.Series/xarray.DataArray - mean day wind speed [m/s] - rs: pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] - rn: pandas.Series/xarray.DataArray, optional - net radiation [MJ m-2 d-1] - g: pandas.Series/int/xarray.DataArray, optional - soil heat flux [MJ m-2 d-1] - tmax: pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] - pressure: float/xarray.DataArray, optional - atmospheric pressure [kPa] - elevation: float/xarray.DataArray, optional - the site elevation [m] - lat: float/xarray.DataArray, optional - the site latitude [rad] - n: pandas.Series/float, optional - actual duration of sunshine [hour] - nn: pandas.Series/float, optional - maximum possible duration of sunshine or daylight hours [hour] - rso: pandas.Series/float, optional - clear-sky solar radiation [MJ m-2 day-1] - a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + wind: pandas.Series or xarray.DataArray + mean day wind speed [m/s]. + rs: pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. + rn: pandas.Series or xarray.DataArray, optional + net radiation [MJ m-2 d-1]. + g: pandas.Series or int/xarray.DataArray, optional + soil heat flux [MJ m-2 d-1]. + tmax: pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: pandas.Series or xarray.DataArray, optional + mean daily relative humidity [%]. + pressure: float or xarray.DataArray, optional + atmospheric pressure [kPa]. + elevation: float or xarray.DataArray, optional + the site elevation [m]. + lat: float or xarray.DataArray, optional + the site latitude [rad]. + n: pandas.Series or float, optional + actual duration of sunshine [hour]. + nn: pandas.Series or float, optional + maximum possible duration of sunshine or daylight hours [hour]. + rso: pandas.Series or float, optional + clear-sky solar radiation [MJ m-2 day-1]. + a: float, optional.= + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] - ea: float/pandas.Series/xarray.DataArray, optional - actual vapor pressure [kPa] + empirical coefficient for Net Long-Wave radiation [-]. + ea: float or pandas.Series or xarray.DataArray, optional + actual vapor pressure [kPa]. albedo: float, optional - surface albedo [-] + surface albedo [-]. kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] + empirical coefficient for extraterrestrial radiation [-]. clip_zero: bool, optional - if True, replace all negative values with 0. + if True, replace all negative values with 0.. Returns ------- - pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Notes ----- @@ -648,90 +875,139 @@ def kimberly_penman(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, (0.605 + 0.345 * exp(-(\\frac{J_D-243}{80})^2)) """ - pressure = calc_press(elevation, pressure) - gamma = calc_psy(pressure) - dlt = calc_vpc(tmean) - lambd = calc_lambda(tmean) - - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=check_rh(rhmax), - rhmin=check_rh(rhmin), rh=check_rh(rh), ea=ea) - es = calc_es(tmean=tmean, tmax=tmax, tmin=tmin) - - rn = calc_rad_net(tmean, rn, rs, check_lat(lat), n, nn, tmax, tmin, rhmax, - rhmin, rh, elevation, rso, a, b, ea, albedo, as1, bs1, - kab) - - j = day_of_year(tmean.index) - w = wind * (0.4 + 0.14 * exp(-((j - 173) / 58) ** 2) + ( - 0.605 + 0.345 * exp((j - 243) / 80) ** 2)) + pressure, gamma, dlt, lambd, ea, es = _lambda_gamma_dlt_ea_es( + elevation, pressure, tmean, tmax, tmin, rhmax, rhmin, rh, ea + ) + + rn = calc_rad_net( + tmean, + rn, + rs, + lat, + n, + nn, + tmax, + tmin, + rhmax, + rhmin, + rh, + elevation, + rso, + a, + b, + ea, + albedo, + as1, + bs1, + kab, + ) + + tindex = get_index(tmean) + j = day_of_year(tindex) + if len(wind.shape) == 3: + j = j[:, newaxis, newaxis] + w = wind * ( + 0.4 + + 0.14 * exp(-(((j - 173) / 58) ** 2)) + + (0.605 + 0.345 * exp((j - 243) / 80) ** 2) + ) den = lambd * (dlt + gamma) num1 = dlt * (rn - g) / den num2 = gamma * (es - ea) * w / den pet = num1 + num2 pet = clip_zeros(pet, clip_zero) - return pet.rename("Kimberly_Penman") - - -def thom_oliver(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, - rhmax=None, rhmin=None, rh=None, pressure=None, elevation=None, - lat=None, n=None, nn=None, rso=None, aw=2.6, bw=0.536, a=1.35, - b=-0.35, lai=None, croph=0.12, r_l=100, r_s=None, ra_method=0, - lai_eff=0, srs=0.0009, co2=300, ea=None, albedo=0.23, kab=None, - as1=0.25, bs1=0.5, clip_zero=True): - """Potential evapotranspiration calculated according to - :cite:t:`thom_penmans_1977`. + return pet_out(tmean, pet, "Kimberly_Penman") + + +def thom_oliver( + tmean, + wind, + rs=None, + rn=None, + g=0, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + pressure=None, + elevation=None, + lat=None, + n=None, + nn=None, + rso=None, + aw=2.6, + bw=0.536, + a=1.35, + b=-0.35, + lai=None, + croph=0.12, + r_l=100, + r_s=None, + ra_method=0, + lai_eff=0, + srs=0.0009, + co2=300, + ea=None, + albedo=0.23, + kab=None, + as1=0.25, + bs1=0.5, + clip_zero=True, +): + """Potential evapotranspiration calculated according to :cite:t:`thom_penmans_1977`. Parameters ---------- tmean: pandas.Series - average day temperature [°C] + average day temperature [°C]. wind: pandas.Series - mean day wind speed [m/s] + mean day wind speed [m/s]. rs: pandas.Series, optional - incoming solar radiation [MJ m-2 d-1] + incoming solar radiation [MJ m-2 d-1]. rn: pandas.Series, optional - net radiation [MJ m-2 d-1] - g: pandas.Series/int, optional - soil heat flux [MJ m-2 d-1] + net radiation [MJ m-2 d-1]. + g: pandas.Series or int, optional + soil heat flux [MJ m-2 d-1]. tmax: pandas.Series, optional - maximum day temperature [°C] + maximum day temperature [°C]. tmin: pandas.Series, optional - minimum day temperature [°C] + minimum day temperature [°C]. rhmax: pandas.Series, optional - maximum daily relative humidity [%] + maximum daily relative humidity [%]. rhmin: pandas.Series, optional - mainimum daily relative humidity [%] + mainimum daily relative humidity [%]. rh: pandas.Series, optional - mean daily relative humidity [%] + mean daily relative humidity [%]. pressure: float, optional - atmospheric pressure [kPa] + atmospheric pressure [kPa]. elevation: float, optional - the site elevation [m] + the site elevation [m]. lat: float, optional - the site latitude [rad] - n: pandas.Series/float, optional - actual duration of sunshine [hour] - nn: pandas.Series/float, optional - maximum possible duration of sunshine or daylight hours [hour] - rso: pandas.Series/float, optional - clear-sky solar radiation [MJ m-2 day-1] + the site latitude [rad]. + n: pandas.Series or float, optional + actual duration of sunshine [hour]. + nn: pandas.Series or float, optional + maximum possible duration of sunshine or daylight hours [hour]. + rso: pandas.Series or float, optional + clear-sky solar radiation [MJ m-2 day-1]. aw: float, optional - wind coefficient [-] + wind coefficient [-]. bw: float, optional - wind coefficient [-] + wind coefficient [-]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] - lai: pandas.Series/float, optional - leaf area index [-] - croph: pandas.series/float, optional - crop height [m] - r_l: pandas.series/float, optional - bulk stomatal resistance [s m-1] - r_s: pandas.series/float, optional - bulk surface resistance [s m-1] + empirical coefficient for Net Long-Wave radiation [-]. + lai: pandas.Series or float, optional + leaf area index [-]. + croph: pandas.Series or float, optional + crop height [m]. + r_l: pandas.Series or float, optional + bulk stomatal resistance [s m-1]. + r_s: pandas.Series or float, optional + bulk surface resistance [s m-1]. ra_method: float, optional 1 => ra = 208/wind 2 => ra is calculated based on equation 36 in FAO (1990), ANNEX V. @@ -741,28 +1017,27 @@ def thom_oliver(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, 2 => LAI_eff = 0.5 * LAI; (LAI>4=4) 3 => see :cite:t:`zhang_comparison_2008`. srs: float, optional - Relative sensitivity of rl to Δ[CO2] + Relative sensitivity of rl to Δ[CO2]. co2: float - CO2 concentration [ppm] - ea: float/pandas.Series/xarray.DataArray, optional - actual vapor pressure [kPa] + CO2 concentration [ppm]. + ea: float or pandas.Series or xarray.DataArray, optional + actual vapor pressure [kPa]. albedo: float, optional - surface albedo [-] + surface albedo [-]. kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] + empirical coefficient for extraterrestrial radiation [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Notes ----- @@ -774,23 +1049,37 @@ def thom_oliver(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, .. math:: w=2.6(1+0.53u_2) """ - pressure = calc_press(elevation, pressure) - gamma = calc_psy(pressure) - dlt = calc_vpc(tmean) - lambd = calc_lambda(tmean) - - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=check_rh(rhmax), - rhmin=check_rh(rhmin), rh=check_rh(rh), ea=ea) - es = calc_es(tmean=tmean, tmax=tmax, tmin=tmin) - + pressure, gamma, dlt, lambd, ea, es = _lambda_gamma_dlt_ea_es( + elevation, pressure, tmean, tmax, tmin, rhmax, rhmin, rh, ea + ) res_a = calc_res_aero(wind, ra_method=ra_method, croph=croph) - res_s = calc_res_surf(lai=lai, r_s=r_s, r_l=r_l, lai_eff=lai_eff, srs=srs, - co2=co2, croph=croph) + res_s = calc_res_surf( + lai=lai, r_s=r_s, r_l=r_l, lai_eff=lai_eff, srs=srs, co2=co2, croph=croph + ) gamma1 = gamma * (1 + res_s / res_a) - rn = calc_rad_net(tmean, rn, rs, check_lat(lat), n, nn, tmax, tmin, rhmax, - rhmin, rh, elevation, rso, a, b, ea, albedo, as1, bs1, - kab) + rn = calc_rad_net( + tmean, + rn, + rs, + lat, + n, + nn, + tmax, + tmin, + rhmax, + rhmin, + rh, + elevation, + rso, + a, + b, + ea, + albedo, + as1, + bs1, + kab, + ) w = aw * (1 + bw * wind) @@ -799,70 +1088,112 @@ def thom_oliver(tmean, wind, rs=None, rn=None, g=0, tmax=None, tmin=None, num2 = 2.5 * gamma * (es - ea) * w / den pet = num1 + num2 pet = clip_zeros(pet, clip_zero) - return pet.rename("Thom_Oliver") - - -def calculate_all(tmean, wind, rs, elevation, lat, tmax, tmin, rh=None, - rhmax=None, rhmin=None): - """Potential evapotranspiration estimated based on all available methods - in pyet with time series data. - - Parameters - ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - wind: float/pandas.Series/xarray.DataArray - mean day wind speed [m/s] - rs: float/pandas.Series/xarray.DataArray - incoming solar radiation [MJ m-2 d-1] - elevation: float/xarray.DataArray - the site elevation [m] - lat: float/xarray.DataArray - the site latitude [rad] - tmax: float/pandas.Series/xarray.DataArray - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray - minimum day temperature [°C] - rh: float/pandas.Series/xarray.DataArray - mean daily relative humidity [%] + return pet_out(tmean, pet, "Thom_Oliver") + + +def calculate_all( + tmean, wind, rs, elevation, lat, tmax, tmin, rh=None, rhmax=None, rhmin=None +): + """Potential evapotranspiration estimated based on all available methods. + + Parameters + ---------- + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + wind: float or pandas.Series or xarray.DataArray + mean day wind speed [m/s]. + rs: float or pandas.Series or xarray.DataArray + incoming solar radiation [MJ m-2 d-1]. + elevation: float or xarray.DataArray + the site elevation [m]. + lat: float or xarray.DataArray + the site latitude [rad]. + tmax: float or pandas.Series or xarray.DataArray + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray + minimum day temperature [°C]. + rh: float or pandas.Series or xarray.DataArray + mean daily relative humidity [%]. rhmax: pandas.Series, optional - maximum daily relative humidity [%] + maximum daily relative humidity [%]. rhmin: pandas.Series, optional - mainimum daily relative humidity [%] + minimum daily relative humidity [%]. - Returns - ------- - pandas.DataFrame containing the calculated Potential evapotranspiration + Returns + ------- + pandas.DataFrame containing the calculated Potential evapotranspiration - Examples - -------- - >>> pe_all = calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax, - tmin=tmin, rh=rh) - """ + Examples + -------- + >>> pe_all = calculate_all(tmean, wind, rs, elevation, lat, tmax=tmax, + tmin=tmin, rh=rh) + """ pe_df = pandas.DataFrame() - pe_df["Penman"] = penman(tmean, wind, rs=rs, elevation=elevation, - lat=lat, tmax=tmax, tmin=tmin, rh=rh, rhmax=rhmax, - rhmin=rhmin) - pe_df["FAO-56"] = pm_fao56(tmean, wind, rs=rs, elevation=elevation, - lat=lat, tmax=tmax, tmin=tmin, rh=rh, - rhmax=rhmax, rhmin=rhmin) - pe_df["Priestley-Taylor"] = priestley_taylor(tmean, rs=rs, - elevation=elevation, lat=lat, - tmax=tmax, tmin=tmin, rh=rh, - rhmax=rhmax, rhmin=rhmin) - pe_df["Kimberly-Penman"] = kimberly_penman(tmean, wind, rs=rs, - elevation=elevation, - lat=lat, tmax=tmax, tmin=tmin, - rh=rh, rhmax=rhmax, rhmin=rhmin) - pe_df["Thom-Oliver"] = thom_oliver(tmean, wind, rs=rs, - elevation=elevation, lat=lat, tmax=tmax, - tmin=tmin, rh=rh, rhmax=rhmax, - rhmin=rhmin) + pe_df["Penman"] = penman( + tmean, + wind, + rs=rs, + elevation=elevation, + lat=lat, + tmax=tmax, + tmin=tmin, + rh=rh, + rhmax=rhmax, + rhmin=rhmin, + ) + pe_df["FAO-56"] = pm_fao56( + tmean, + wind, + rs=rs, + elevation=elevation, + lat=lat, + tmax=tmax, + tmin=tmin, + rh=rh, + rhmax=rhmax, + rhmin=rhmin, + ) + pe_df["Priestley-Taylor"] = priestley_taylor( + tmean, + rs=rs, + elevation=elevation, + lat=lat, + tmax=tmax, + tmin=tmin, + rh=rh, + rhmax=rhmax, + rhmin=rhmin, + ) + pe_df["Kimberly-Penman"] = kimberly_penman( + tmean, + wind, + rs=rs, + elevation=elevation, + lat=lat, + tmax=tmax, + tmin=tmin, + rh=rh, + rhmax=rhmax, + rhmin=rhmin, + ) + pe_df["Thom-Oliver"] = thom_oliver( + tmean, + wind, + rs=rs, + elevation=elevation, + lat=lat, + tmax=tmax, + tmin=tmin, + rh=rh, + rhmax=rhmax, + rhmin=rhmin, + ) pe_df["Blaney-Criddle"] = blaney_criddle(tmean, lat) pe_df["Hamon"] = hamon(tmean, lat=lat, method=1) - pe_df["Romanenko"] = romanenko(tmean, rh=rh, tmax=tmax, tmin=tmin, - rhmax=rhmax, rhmin=rhmin) + pe_df["Romanenko"] = romanenko( + tmean, rh=rh, tmax=tmax, tmin=tmin, rhmax=rhmax, rhmin=rhmin + ) pe_df["Linacre"] = linacre(tmean, elevation, lat, tmax=tmax, tmin=tmin) pe_df["Haude"] = haude(tmax, rh) @@ -875,3 +1206,25 @@ def calculate_all(tmean, wind, rs, elevation, lat, tmax, tmin, rh=None, pe_df["Makkink"] = makkink(tmean, rs, elevation=elevation) pe_df["Oudin"] = oudin(tmean, lat=lat) return pe_df + + +def _lambda_gamma_dlt_ea_es( + velevation, vpressure, vtmean, vtmax, vtmin, vrhmax, vrhmin, vrh, vea +): + """Just ot avoid duplicated rows.""" + vpressure = calc_press(velevation, vpressure) + gamma = calc_psy(vpressure) + dlt = calc_vpc(vtmean) + lambd = calc_lambda(vtmean) + + ea = calc_ea( + tmean=vtmean, + tmax=vtmax, + tmin=vtmin, + rhmax=check_rh(vrhmax), + rhmin=check_rh(vrhmin), + rh=check_rh(vrh), + ea=vea, + ) + es = calc_es(tmean=vtmean, tmax=vtmax, tmin=vtmin) + return vpressure, gamma, dlt, lambd, ea, es diff --git a/pyet/meteo_utils.py b/pyet/meteo_utils.py index fabf549..0e35c58 100644 --- a/pyet/meteo_utils.py +++ b/pyet/meteo_utils.py @@ -1,16 +1,14 @@ -"""The meteo_utils module contains utility functions for meteorological data +"""The meteo_utils module contains utility functions for meteorological data. """ -from numpy import tan, cos, pi, sin, arccos, mod, exp, log, nanmax, isnan, \ - where - -from pandas import to_numeric, Series - +from numpy import cos, exp, isnan, log, pi, sin, tan +from pandas import Series, to_numeric from xarray import DataArray +from numpy import arccos, clip, nanmax, where # Specific heat of air [MJ kg-1 °C-1] -CP = 1.013 * 10 ** -3 +CP = 1.013 * 10**-3 def calc_psy(pressure, tmean=None): @@ -18,14 +16,14 @@ def calc_psy(pressure, tmean=None): Parameters ---------- - pressure: float/pandas.Series/xarray.DataArray + pressure: array_like atmospheric pressure [kPa]. - tmean: float/pandas.Series/xarray.DataArray + tmean: array_like average day temperature [°C]. Returns ------- - float/pandas.Series/xarray.DataArray containing the Psychrometric + array_like containing the Psychrometric constant [kPa °C-1]. Examples @@ -52,12 +50,12 @@ def calc_vpc(tmean): Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] + tmean: array_like + average day temperature [°C]. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated + array_like containing the calculated Saturation vapour pressure [kPa °C-1]. Examples @@ -78,12 +76,12 @@ def calc_lambda(tmean): Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] + tmean: array_like + average day temperature [°C]. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated Latent Heat + array_like containing the calculated Latent Heat of Vaporization [MJ kg-1]. Examples @@ -103,14 +101,14 @@ def calc_press(elevation, pressure=None): Parameters ---------- - elevation: float/xarray.DataArray - the site elevation [m] - pressure: float/xarray.DataArray, optional + elevation: array_like + the site elevation [m]. + pressure: array_like, optional atmospheric pressure [kPa]. + Returns ------- - float/xarray.DataArray containing the calculated atmospheric - pressure [kPa]. + array_like containing the calculated atmospheric pressure [kPa]. Examples -------- @@ -121,6 +119,8 @@ def calc_press(elevation, pressure=None): Based on equation 7 in :cite:t:`allen_crop_1998`. """ + if pressure is None and elevation is None: + raise Exception("Please provide either pressure or the elevation!") if pressure is None: return 101.3 * ((293 - 0.0065 * elevation) / 293) ** 5.26 else: @@ -128,22 +128,21 @@ def calc_press(elevation, pressure=None): def calc_rho(pressure, tmean, ea): - """Atmospheric air density calculated according to - :cite:t:`allen_crop_1998`. + """Atmospheric air density calculated according to :cite:t:`allen_crop_1998`. Parameters ---------- - pressure: float/pandas.Series/xarray.DataArray - atmospheric pressure [kPa] - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] - ea: float/pandas.Series/xarray.DataArray - actual vapour pressure [kPa] + pressure: array_like + atmospheric pressure [kPa]. + tmean: array_like + average day temperature [°C]. + ea: array_like + actual vapour pressure [kPa]. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated mean - air density [kg/m3] + float or pandas.Series or xarray.DataArray containing the calculated mean air + density [kg/m3] Examples -------- @@ -166,13 +165,13 @@ def calc_e0(tmean): Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] + tmean: array_like + average day temperature [°C]. Returns ------- - pandas.Series containing the calculated saturation vapor pressure at the - air temperature tmean [kPa]. + array_like containing the calculated saturation vapor pressure at the air + temperature tmean [kPa]. Examples -------- @@ -191,17 +190,17 @@ def calc_es(tmean=None, tmax=None, tmin=None): Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray, optional - average day temperature [°C] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] + tmean: array_like, optional + average day temperature [°C]. + tmax: array_like, optional + maximum day temperature [°C]. + tmin: array_like, optional + minimum day temperature [°C]. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - saturation vapor pressure [kPa]. + float or pandas.Series or xarray.DataArray containing the calculated saturation + vapor pressure [kPa]. Examples -------- @@ -220,31 +219,30 @@ def calc_es(tmean=None, tmax=None, tmin=None): return calc_e0(tmean) -def calc_ea(tmean=None, tmax=None, tmin=None, rhmax=None, rhmin=None, rh=None, - ea=None): +def calc_ea(tmean=None, tmax=None, tmin=None, rhmax=None, rhmin=None, rh=None, ea=None): """Actual vapor pressure [kPa]. Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray, optional - average day temperature [°C] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] - ea: pandas.Series/float, optional - actual vapor pressure [kPa] + tmean: array_like, optional + average day temperature [°C]. + tmax: array_like, optional + maximum day temperature [°C]. + tmin: array_like, optional + minimum day temperature [°C]. + rhmax: array_like, optional + maximum daily relative humidity [%]. + rhmin: array_like, optional + mainimum daily relative humidity [%]. + rh: array_like, optional + mean daily relative humidity [%]. + ea: array_like, optional + actual vapor pressure [kPa]. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated actual - vapor pressure [kPa]. + float or pandas.Series or xarray.DataArray containing the calculated actual vapor + pressure [kPa]. Examples -------- @@ -270,7 +268,7 @@ def calc_ea(tmean=None, tmax=None, tmin=None, rhmax=None, rhmin=None, rh=None, def day_of_year(tindex): - """Day of the year (1-365) based on pandas.Index + """Day of the year (1-365) based on pandas.Index. Parameters ---------- @@ -278,41 +276,30 @@ def day_of_year(tindex): Returns ------- - pandas.Series with ints specifying day of year. + array_like with ints specifying day of year. """ - return Series(to_numeric(tindex.strftime('%j')), tindex, dtype=int) + return Series(to_numeric(tindex.strftime("%j")), tindex, dtype=int) -def daylight_hours(tindex, lat): - """Daylight hours [hour]. +def solar_declination(j): + """Solar declination from day of year [rad]. Parameters ---------- - tindex: pandas.DatetimeIndex - lat: float/xarray.DataArray - the site latitude [rad] + j: array_like + day of the year (1-365). Returns ------- - pandas.Series or xarray.DataArray containing the calculated - daylight hours [hour] + array_like of solar declination [rad]. Notes - ----- - Based on equation 34 in :cite:t:`allen_crop_1998`. + ------- + Based on equations 24 in :cite:t:`allen_crop_1998`. """ - j = day_of_year(tindex) - sol_dec = solar_declination(j) - sangle = sunset_angle(sol_dec, lat) - # Account for subpolar belt which returns NaN values - dl = 24 / pi * sangle - if isinstance(lat, DataArray): - sol_dec = ((dl / dl).T * sol_dec.values).T - dl = where((sol_dec > 0) & (isnan(dl)), nanmax(dl), dl) - dl = where((sol_dec < 0) & (isnan(dl)), 0, dl) - return dl + return 0.409 * sin(2.0 * pi / 365.0 * j - 1.39) def sunset_angle(sol_dec, lat): @@ -320,15 +307,14 @@ def sunset_angle(sol_dec, lat): Parameters ---------- - sol_dec: float/pandas.Series/xarray.DataArray - solar declination [rad] - lat: float/xarray.DataArray - the site latitude [rad] + sol_dec: array_like + solar declination [rad]. + lat: array_like + the site latitude [rad]. Returns ------- - pandas.Series/xarray.DataArray containing the calculated sunset hour - angle - daily [rad] + array_like containing the calculated sunset hour angle - daily [rad]. Notes ----- @@ -337,48 +323,39 @@ def sunset_angle(sol_dec, lat): """ if isinstance(lat, DataArray): lat = lat.expand_dims(dim={"time": sol_dec.index}, axis=0) - return arccos(-tan(sol_dec.values) * tan(lat).T).T + return arccos(clip(-tan(sol_dec.values) * tan(lat).T, -1, 1)).T else: - return arccos(-tan(sol_dec) * tan(lat)) + return arccos(clip(-tan(sol_dec) * tan(lat), -1, 1)) -def _wrap(x, x_min, x_max): - """Wrap floating point values into range - github.com/WSWUP/RefET. +def daylight_hours(tindex, lat): + """Daylight hours [hour]. Parameters ---------- - x : ndarray - Values to wrap. - x_min : float - Minimum value in output range. - x_max : float - Maximum value in output range. - - Returns - ------- - ndarray - - """ - return mod((x - x_min), (x_max - x_min)) + x_min - - -def solar_declination(j): - """Solar declination from day of year [rad]. + tindex: pandas.DatetimeIndex + lat: array_like + the site latitude [rad]. - Parameters - ---------- - j: pandas.Series - day of the year (1-365) Returns ------- - pandas.Series of solar declination [rad]. + pandas.Series or xarray.DataArray containing the calculated daylight hours [hour]. Notes - ------- - Based on equations 24 in :cite:t:`allen_crop_1998`. + ----- + Based on equation 34 in :cite:t:`allen_crop_1998`. """ - return 0.409 * sin(2. * pi / 365. * j - 1.39) + j = day_of_year(tindex) + sol_dec = solar_declination(j) + sangle = sunset_angle(sol_dec, lat) + # Account for subpolar belt which returns NaN values + dl = 24 / pi * sangle + if isinstance(lat, DataArray): + sol_dec = ((dl / dl).T * sol_dec.values).T + dl = where((sol_dec > 0) & (isnan(dl)), nanmax(dl), dl) + dl = where((sol_dec < 0) & (isnan(dl)), 0, dl) + return dl def relative_distance(j): @@ -386,8 +363,8 @@ def relative_distance(j): Parameters ---------- - j: pandas.Series - day of the year (1-365) + j: array_like + day of the year (1-365). Returns ------- @@ -398,22 +375,22 @@ def relative_distance(j): Based on equations 23 in :cite:t:`allen_crop_1998`. """ - return 1 + 0.033 * cos(2. * pi / 365. * j) + return 1 + 0.033 * cos(2.0 * pi / 365.0 * j) def extraterrestrial_r(tindex, lat): - """Extraterrestrial daily radiation [MJ m-2 d-1]. + """ + Extraterrestrial daily radiation [MJ m-2 d-1]. Parameters ---------- tindex: pandas.DatetimeIndex - lat: float/xarray.DataArray - the site latitude [rad] + lat: array_like + the site latitude [rad]. Returns ------- - pandas.Series/xarray.DataArray containing the calculated extraterrestrial - radiation [MJ m-2 d-1] + array_like containing the calculated extraterrestrial radiation [MJ m-2 d-1] Notes ----- @@ -424,53 +401,52 @@ def extraterrestrial_r(tindex, lat): dr = relative_distance(j) sol_dec = solar_declination(j) - omega = sunset_angle(sol_dec, lat).values + omega = sunset_angle(sol_dec, lat) if isinstance(lat, DataArray): lat = lat.expand_dims(dim={"time": sol_dec.index}, axis=0) - xx = (sin(sol_dec.values) * sin(lat.T)) - yy = (cos(sol_dec.values) * cos(lat.T)) - return (118.08 / 3.141592654 * dr.values * ( - omega.T * xx + yy * sin(omega.T))).T + xx = sin(sol_dec.values) * sin(lat.T) + yy = cos(sol_dec.values) * cos(lat.T) + return (118.08 / 3.141592654 * dr.values * (omega.T * xx + yy * sin(omega.T))).T else: xx = sin(sol_dec) * sin(lat) yy = cos(sol_dec) * cos(lat) return 118.08 / 3.141592654 * dr * (omega * xx + yy * sin(omega)) -def calc_res_surf(lai=None, r_s=None, srs=0.002, co2=300, r_l=100, lai_eff=0, - croph=0.12): +def calc_res_surf( + lai=None, r_s=None, srs=0.002, co2=300, r_l=100, lai_eff=0, croph=0.12 +): """Surface resistance [s m-1]. Parameters ---------- - lai: float/pandas.Series/xarray.DataArray, optional - leaf area index [-] - r_s: float/pandas.Series/xarray.DataArray, optional - surface resistance [s m-1] - r_l: float/pandas.Series/xarray.DataArray, optional - bulk stomatal resistance [s m-1] + lai: float or pandas.Series or xarray.DataArray, optional + leaf area index [-]. + r_s: float or pandas.Series or xarray.DataArray, optional + surface resistance [s m-1]. + r_l: float or pandas.Series or xarray.DataArray, optional + bulk stomatal resistance [s m-1]. lai_eff: float, optional 1 => LAI_eff = 0.5 * LAI 2 => LAI_eff = lai / (0.3 * lai + 1.2) 3 => LAI_eff = 0.5 * LAI; (LAI>4=4) 4 => see :cite:t:`zhang_comparison_2008`. - srs: float/pandas.Series/xarray.DataArray, optional - Relative sensitivity of rl to Δ[CO2] :cite:t:`yang_hydrologic_2019` - co2: float/pandas.Series/xarray.DataArray - CO2 concentration [ppm] - croph: float/pandas.Series/xarray.DataArray, optional - crop height [m] + srs: float or pandas.Series or xarray.DataArray, optional + Relative sensitivity of rl to Δ[CO2] :cite:t:`yang_hydrologic_2019`. + co2: float or pandas.Series or xarray.DataArray + CO2 concentration [ppm]. + croph: float or pandas.Series or xarray.DataArray, optional crop height [m]. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated surface - resistance [s / m] + float or pandas.Series or xarray.DataArray containing the calculated surface + resistance [s / m] """ if r_s: return r_s else: - fco2 = (1 + srs * (co2 - 300)) + fco2 = 1 + srs * (co2 - 300) if lai is None: return fco2 * r_l / (0.5 * croph * 24) # after FAO-56 else: @@ -483,7 +459,7 @@ def calc_laieff(lai=None, lai_eff=0): Parameters ---------- lai: pandas.Series/float, optional - leaf area index [-] + leaf area index [-]. lai_eff: float, optional 0 => LAI_eff = 0.5 * LAI 1 => LAI_eff = lai / (0.3 * lai + 1.2) @@ -492,7 +468,7 @@ def calc_laieff(lai=None, lai_eff=0): Returns ------- - pandas.Series containing the calculated effective leaf area index + pandas.Series containing the calculated effective leaf area index. """ if lai_eff == 0: @@ -515,28 +491,28 @@ def calc_res_aero(wind, croph=0.12, zw=2, zh=2, ra_method=0): Parameters ---------- - wind: float/pandas.Series/xarray.DataArray - mean day wind speed [m/s] - croph: float/pandas.Series/xarray.DataArray, optional - crop height [m] + wind: float or pandas.Series or xarray.DataArray + mean day wind speed [m/s]. + croph: float or pandas.Series or xarray.DataArray, optional + crop height [m]. zw: float, optional - height of wind measurement [m] + height of wind measurement [m]. zh: float, optional - height of humidity and or air temperature measurement [m] + height of humidity and or air temperature measurement [m]. ra_method: float, optional 0 => ra = 208/wind 1 => ra is calculated based on equation 36 in FAO (1990), ANNEX V. Returns ------- - pandas.Series containing the calculated aerodynamic resistance + pandas.Series containing the calculated aerodynamic resistance. """ if ra_method == 0: + wind = wind.where(wind != 0, 0.0001) return 208 / wind else: d = 0.667 * croph zom = 0.123 * croph zoh = 0.0123 * croph - return (log((zw - d) / zom)) * (log((zh - d) / zoh) / - (0.41 ** 2) / wind) + return (log((zw - d) / zom)) * (log((zh - d) / zoh) / (0.41**2) / wind) diff --git a/pyet/rad_utils.py b/pyet/rad_utils.py index 584a639..b10272f 100644 --- a/pyet/rad_utils.py +++ b/pyet/rad_utils.py @@ -1,78 +1,95 @@ -"""The rad_utils module contains utility functions for radiation data +"""The rad_utils module contains utility functions for radiation data. """ -from numpy import sqrt, clip +from numpy import sqrt, clip, newaxis -from pandas import DatetimeIndex +from pandas import Series from xarray import DataArray from .meteo_utils import calc_ea, extraterrestrial_r, daylight_hours -from .utils import get_index, check_rad +from .utils import get_index, check_rad, vectorize # Stefan Boltzmann constant - hourly [MJm-2K-4h-1] -STEFAN_BOLTZMANN_HOUR = 2.042 * 10 ** -10 +STEFAN_BOLTZMANN_HOUR = 2.042 * 10**-10 # Stefan Boltzmann constant - daily [MJm-2K-4d-1] -STEFAN_BOLTZMANN_DAY = 4.903 * 10 ** -9 - - -def calc_rad_net(tmean, rn=None, rs=None, lat=None, n=None, nn=None, tmax=None, - tmin=None, rhmax=None, rhmin=None, rh=None, elevation=None, - rso=None, a=1.35, b=-0.35, ea=None, albedo=0.23, as1=0.25, - bs1=0.5, kab=None): +STEFAN_BOLTZMANN_DAY = 4.903 * 10**-9 + + +def calc_rad_net( + tmean, + rn=None, + rs=None, + lat=None, + n=None, + nn=None, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + elevation=None, + rso=None, + a=1.35, + b=-0.35, + ea=None, + albedo=0.23, + as1=0.25, + bs1=0.5, + kab=None, +): """Net radiation [MJ m-2 d-1]. Parameters ---------- tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - rn: float/pandas.Series/xarray.DataArray, optional - net radiation [MJ m-2 d-1] - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] + average day temperature [°C]. + rn: float or pandas.Series or xarray.DataArray, optional + net radiation [MJ m-2 d-1]. + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. lat: float/xarray.DataArray, optional - the site latitude [rad] - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] + the site latitude [rad]. + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. + tmax: float or pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: float or pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: float or pandas.Series or xarray.DataArray, optional + mean daily relative humidity [%]. elevation: float/xarray.DataArray, optional - the site elevation [m] - rso: float/pandas.Series/xarray.DataArray, optional - clear-sky solar radiation [MJ m-2 day-1] + the site elevation [m]. + rso: float or pandas.Series or xarray.DataArray, optional + clear-sky solar radiation [MJ m-2 day-1]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] - ea: float/pandas.Series/xarray.DataArray, optional - actual vapor pressure [kPa] + empirical coefficient for Net Long-Wave radiation [-]. + ea: float or pandas.Series or xarray.DataArray, optional + actual vapor pressure [kPa]. albedo: float, optional surface albedo [-] as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-] bs1: float, optional empirical coefficient for extraterrestrial radiation [-] kab: float, optional - coefficient derived from as1, bs1 for estimating clear-sky radiation - [degrees]. + coefficient derived from as1, bs1 for estimating clear-sky radiation [degrees]. Returns ------- - float/pandas.Series/xarray.DataArray, optional containing the calculated - net shortwave radiation + float or pandas.Series or xarray.DataArray, optional containing the calculated net + shortwave radiation. Notes ----- @@ -85,60 +102,86 @@ def calc_rad_net(tmean, rn=None, rs=None, lat=None, n=None, nn=None, tmax=None, else: if rs is None: rs = calc_rad_sol_in(n, lat, as1=as1, bs1=bs1, nn=nn) - rns = calc_rad_short(rs=rs, lat=lat, n=n, nn=nn, albedo=albedo, - as1=as1, bs1=bs1) # [MJ/m2/d] - rnl = calc_rad_long(rs=rs, tmean=tmean, tmax=tmax, tmin=tmin, - rhmax=rhmax, rhmin=rhmin, rh=rh, - elevation=elevation, lat=lat, rso=rso, a=a, b=b, - ea=ea, kab=kab) # [MJ/m2/d] + rns = calc_rad_short( + rs=rs, lat=lat, n=n, nn=nn, albedo=albedo, as1=as1, bs1=bs1 + ) # [MJ/m2/d] + rnl = calc_rad_long( + rs=rs, + tmean=tmean, + tmax=tmax, + tmin=tmin, + rhmax=rhmax, + rhmin=rhmin, + rh=rh, + elevation=elevation, + lat=lat, + rso=rso, + a=a, + b=b, + ea=ea, + kab=kab, + ) # [MJ/m2/d] rn = rns - rnl rn = check_rad(rn) return rn -def calc_rad_long(rs, tmean=None, tmax=None, tmin=None, rhmax=None, rhmin=None, - rh=None, elevation=None, lat=None, rso=None, a=1.35, b=-0.35, - ea=None, kab=None): +def calc_rad_long( + rs, + tmean=None, + tmax=None, + tmin=None, + rhmax=None, + rhmin=None, + rh=None, + elevation=None, + lat=None, + rso=None, + a=1.35, + b=-0.35, + ea=None, + kab=None, +): """Net longwave radiation [MJ m-2 d-1]. Parameters ---------- - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] - tmean: float/pandas.Series/xarray.DataArray, optional - average day temperature [°C] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] - rhmax: float/pandas.Series/xarray.DataArray, optional - maximum daily relative humidity [%] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - rh: float/pandas.Series/xarray.DataArray, optional - mean daily relative humidity [%] + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. + tmean: float or pandas.Series or xarray.DataArray, optional + average day temperature [°C]. + tmax: float or pandas.Series or xarray.DataArray, optional + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray, optional + minimum day temperature [°C]. + rhmax: float or pandas.Series or xarray.DataArray, optional + maximum daily relative humidity [%]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + rh: float or pandas.Series or xarray.DataArray, optional + mean daily relative humidity [%]. elevation: float/xarray.DataArray, optional - the site elevation [m] + the site elevation [m]. lat: float/xarray.DataArray, optional - the site latitude [rad] - rso: float/pandas.Series/xarray.DataArray, optional - clear-sky solar radiation [MJ m-2 day-1] + the site latitude [rad]. + rso: float or pandas.Series or xarray.DataArray, optional + clear-sky solar radiation [MJ m-2 day-1]. a: float, optional - empirical coefficient for Net Long-Wave radiation [-] + empirical coefficient for Net Long-Wave radiation [-]. b: float, optional - empirical coefficient for Net Long-Wave radiation [-] - ea: float/pandas.Series/xarray.DataArray, optional - actual vapor pressure [kPa] + empirical coefficient for Net Long-Wave radiation [-]. + ea: float or pandas.Series or xarray.DataArray, optional + actual vapor pressure [kPa]. kab: float, optional coefficient that can be derived from the as and bs coefficients of the Angstrom formula, where Kab = as + bs, and where Kab represents the fraction of extraterrestrial radiation reaching the earth on clear-sky - days [-] + days [-]. Returns ------- - float/pandas.Series/xarray.DataArray, optional containing the calculated - net longwave radiation + float or pandas.Series or xarray.DataArray, optional containing the calculated net + longwave radiation. Notes ----- @@ -146,60 +189,62 @@ def calc_rad_long(rs, tmean=None, tmax=None, tmin=None, rhmax=None, rhmin=None, """ if ea is None: - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=rhmax, - rhmin=rhmin, rh=rh) + ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=rhmax, rhmin=rhmin, rh=rh) if rso is None: tindex = get_index(rs) ra = extraterrestrial_r(tindex, lat) rso = calc_rso(ra=ra, elevation=elevation, kab=kab) + # Add a small constant to rso where it is zero to avoid division with zero + rso = rso.where(rso != 0, 0.001) + if len(rs.shape) == 3 and len(rso.shape) == 1: + rso = rso.values[:, newaxis, newaxis] solar_rat = clip(rs / rso, 0.3, 1) if tmax is not None: - tmp1 = STEFAN_BOLTZMANN_DAY * ((tmax + 273.16) ** 4 + - (tmin + 273.16) ** 4) / 2 + tmp1 = STEFAN_BOLTZMANN_DAY * ((tmax + 273.16) ** 4 + (tmin + 273.16) ** 4) / 2 else: tmp1 = STEFAN_BOLTZMANN_DAY * (tmean + 273.16) ** 4 - tmp2 = 0.34 - 0.14 * sqrt(ea) # OK tmp3 = a * solar_rat + b # OK tmp3 = clip(tmp3, 0.05, 1) - return tmp1 * tmp2 * tmp3 + rnl = tmp1 * tmp2 * tmp3 + return rnl -def calc_rad_short(rs=None, lat=None, albedo=0.23, n=None, nn=None, as1=0.25, - bs1=0.5): +def calc_rad_short(rs=None, lat=None, albedo=0.23, n=None, nn=None, as1=0.25, bs1=0.5): """Net shortwave radiation [MJ m-2 d-1]. Parameters ---------- - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] + rs: float or pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. lat: float, optional - the site latitude [rad] - albedo: float/pandas.Series/xarray.DataArray, optional - surface albedo [-] + the site latitude [rad]. + albedo: float or pandas.Series or xarray.DataArray, optional + surface albedo [-]. n: pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] + actual duration of sunshine [hour]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] + empirical coefficient for extraterrestrial radiation [-]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. Returns ------- - float/pandas.Series/xarray.DataArray, optional containing the calculated - net shortwave radiation + float or pandas.Series or xarray.DataArray, optional containing the calculated + net shortwave radiation. Notes ----- Based on equation 38 in :cite:t:`allen_crop_1998`. """ - if rs is not None: - return (1 - albedo) * rs + (vrs,) = vectorize(rs) + if vrs is not None: + return (1 - albedo) * vrs else: return (1 - albedo) * calc_rad_sol_in(n, lat, as1=as1, bs1=bs1, nn=nn) @@ -209,21 +254,21 @@ def calc_rad_sol_in(n, lat, as1=0.25, bs1=0.5, nn=None): Parameters ---------- - n: pandas.Series/xarray.DataArray - actual duration of sunshine [hour] + n: pandas.Series or xarray.DataArray + actual duration of sunshine [hour]. lat: float, optional - the site latitude [rad] + the site latitude [rad]. as1: float, optional - regression constant, expressing the fraction of extraterrestrial - reaching the earth on overcast days (n = 0) [-] + regression constant, expressing the fraction of extraterrestrial reaching the + earth on overcast days (n = 0) [-]. bs1: float, optional - empirical coefficient for extraterrestrial radiation [-] + empirical coefficient for extraterrestrial radiation [-]. nn: pandas.Series/float, optional - maximum possible duration of sunshine or daylight hours [hour] + maximum possible duration of sunshine or daylight hours [hour]. Returns ------- - pandas.Series containing the calculated net shortwave radiation + pandas.Series containing the calculated net shortwave radiation. Notes ----- @@ -243,19 +288,19 @@ def calc_rso(ra, elevation, kab=None): Parameters ---------- ra: pandas.Series/xarray.DataArray, optional - Extraterrestrial daily radiation [MJ m-2 d-1] + Extraterrestrial daily radiation [MJ m-2 d-1]. elevation: float/xarray.DataArray, optional - the site elevation [m] + the site elevation [m]. kab: float, optional coefficient that can be derived from the as and bs coefficients of the Angstrom formula, where Kab = as + bs, and where Kab represents the fraction of extraterrestrial radiation reaching the earth on clear-sky - days [-] + days [-]. Returns ------- - pandas.Series/xarray.DataArray, optional containing the calculated - Clear-sky solar radiation + pandas.Series/xarray.DataArray, optional containing the calculated Clear-sky solar + radiation. Notes ----- @@ -263,9 +308,11 @@ def calc_rso(ra, elevation, kab=None): """ if isinstance(elevation, DataArray): - elevation = elevation.expand_dims(dim={"time": DatetimeIndex(ra.time)}, - axis=0) + tindex = get_index(ra) + elevation = elevation.expand_dims(dim={"time": tindex}, axis=0) + if isinstance(ra, Series): + ra = ra.values[:, newaxis, newaxis] if kab is None: - return (0.75 + (2 * 10 ** -5) * elevation) * ra + return (0.75 + (2 * 10**-5) * elevation) * ra else: return kab * ra diff --git a/pyet/radiation.py b/pyet/radiation.py index e3b9ae1..54cfde5 100644 --- a/pyet/radiation.py +++ b/pyet/radiation.py @@ -2,86 +2,83 @@ """ -from numpy import sqrt +from numpy import sqrt, log +from xarray import DataArray +from pandas import Series +from .meteo_utils import extraterrestrial_r, calc_press, calc_psy, calc_vpc, calc_lambda +from .utils import get_index, check_rad, clip_zeros, pet_out, check_rh -from .combination import calc_lambda -from .meteo_utils import extraterrestrial_r, calc_press, calc_psy, calc_vpc - -from pyet.utils import * - - -def turc(tmean, rs, rh, k=0.31, clip_zero=True): +def turc(tmean, rs, rh, k=0.013, clip_zero=True): """Potential evapotranspiration calculated according to :cite:t:`turc_estimation_1961`. Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] - rs: float/pandas.Series/xarray.DataArray - incoming solar radiation [MJ m-2 d-1] - rh: float/pandas.Series/xarray.DataArray - mean daily relative humidity [%] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + rs: pandas.Series or xarray.DataArray + incoming solar radiation [MJ m-2 d-1]. + rh: pandas.Series or xarray.DataArray + mean daily relative humidity [%]. k: float, optional - calibration coefficient [-] + calibration coefficient [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated + pandas.Series or xarray.DataArray containing the calculated Potential evapotranspiration [mm d-1]. Examples -------- - >>> iet_turc = turc(tmean, rs, rh) + >>> pet_turc = turc(tmean, rs, rh) Notes ----- - Based on equation 2 and 3 in :cite:t:`xu_evaluation_2000`. + Based on equation S9.10 and S9.11 in :cite:t:`mcmahon_estimating_2013`. - .. math:: PET=k(\\frac{T_{mean}}{T_{mean}+15})(\\frac{R_s}{4.184}+50)4.184; + .. math:: PET=k(\\frac{T_{mean}}{T_{mean}+15})(23.88R_s+50)0.013; for RH>50 .. math:: PET=k(1+\\frac{50-RH}{70})(\\frac{T_{mean}}{T_{mean}+15}) - (\\frac{R_s}{4.184}+50)4.184; for RH<50 + (23.88R_s+50)0.013; for RH<50 """ c = tmean / tmean - c.where(check_rh(rh) > 50, 1 + (50 - rh) / 70) - pet = k * c * tmean / (tmean + 15) * (check_rad(rs) + 2.094) + c = c.where(check_rh(rh) >= 50, 1 + (50 - rh) / 70) + pet = k * c * tmean / (tmean + 15) * (check_rad(rs) * 23.88 + 50) pet = clip_zeros(pet, clip_zero) - return pet.rename("Turc") + return pet_out(tmean, pet, "Turc") -def jensen_haise(tmean, rs=None, cr=0.025, tx=-3, lat=None, method=0, - clip_zero=True): +def jensen_haise(tmean, rs=None, cr=0.025, tx=-3, lat=None, method=0, clip_zero=True): """Potential evapotranspiration calculated accordinf to :cite:t:`jensen_estimating_1963`. Parameters ---------- - tmean: andas.Series/xarray.DataArray - average day temperature [°C] - rs: float/pandas.Series/xarray.DataArray, optional - incoming solar radiation [MJ m-2 d-1] + tmean: pandas.Series orxarray.DataArray + average day temperature [°C]. + rs: pandas.Series or xarray.DataArray, optional + incoming solar radiation [MJ m-2 d-1]. cr: float, optional - temperature coefficient [-] + temperature coefficient [-]. tx: float, optional - intercept of the temperature axis [°C] + intercept of the temperature axis [°C]. lat: float/xarray.DataArray - the site latitude [rad] + the site latitude [rad]. method: float, optional 0 => after :cite:t:`jensen_evaporation_2016` - 1 => after :cite:t:`oudin_which_2005` + 1 => after :cite:t:`oudin_which_2005`. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -100,15 +97,19 @@ def jensen_haise(tmean, rs=None, cr=0.025, tx=-3, lat=None, method=0, """ lambd = calc_lambda(tmean) if method == 0: + if rs is None: + raise Exception("If you choose method == 0, provide rs!") pet = check_rad(rs) / lambd * cr * (tmean - tx) elif method == 1: + if lat is None: + raise Exception("If you choose method == 1, provide lat!") index = get_index(tmean) - ra = extraterrestrial_r(index, check_lat(lat)) + ra = extraterrestrial_r(index, lat, tmean) pet = ra * (tmean + 5) / 68 / lambd else: - raise Exception("method can be either 0 or 1.") + raise Exception("Method can be either 0 or 1.") pet = clip_zeros(pet, clip_zero) - return pet.rename("Jensen_Haise") + return pet_out(tmean, pet, "Jensen_Haise") def mcguinness_bordne(tmean, lat, k=0.0147, clip_zero=True): @@ -117,19 +118,19 @@ def mcguinness_bordne(tmean, lat, k=0.0147, clip_zero=True): Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. lat: float/xarray.DataArray, optional - the site latitude [rad] + the site latitude [rad]. k: float, optional - calibration coefficient [-] + calibration coefficient [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -144,10 +145,12 @@ def mcguinness_bordne(tmean, lat, k=0.0147, clip_zero=True): """ lambd = calc_lambda(tmean) index = get_index(tmean) - ra = extraterrestrial_r(index, check_lat(lat)) + ra = extraterrestrial_r(index, lat) + if isinstance(tmean, DataArray) and isinstance(ra, Series): + ra = ra.values[:, None, None] pet = k * ra * (tmean + 5) / lambd pet = clip_zeros(pet, clip_zero) - return pet.rename("Mcguinness_Bordne") + return pet_out(tmean, pet, "Mcguinness_Bordne") def hargreaves(tmean, tmax, tmin, lat, k=0.0135, method=0, clip_zero=True): @@ -156,26 +159,26 @@ def hargreaves(tmean, tmax, tmin, lat, k=0.0135, method=0, clip_zero=True): Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - tmax: float/pandas.Series/xarray.DataArray - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray - minimum day temperature [°C] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + tmax: pandas.Series or xarray.DataArray + maximum day temperature [°C]. + tmin: pandas.Series or xarray.DataArray + minimum day temperature [°C]. lat: float/xarray.DataArray - the site latitude [rad] + the site latitude [rad]. k: float, optional - calirbation coefficient [-] + calirbation coefficient [-]. method: float, optional 0 => after :cite:t:`jensen_evaporation_2016` - 1 => after :cite:t:`mcmahon_estimating_2013` + 1 => after :cite:t:`mcmahon_estimating_2013`. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -200,48 +203,51 @@ def hargreaves(tmean, tmax, tmin, lat, k=0.0135, method=0, clip_zero=True): """ lambd = calc_lambda(tmean) index = get_index(tmean) - - ra = extraterrestrial_r(index, check_lat(lat)) + ra = extraterrestrial_r(index, lat) + if isinstance(tmean, DataArray) and isinstance(ra, Series): + ra = ra.values[:, None, None] + else: + ra = ra.values chs = 0.00185 * (tmax - tmin) ** 2 - 0.0433 * (tmax - tmin) + 0.4023 if method == 0: - pet = k / 0.0135 * 0.0023 * (tmean + 17.8) * sqrt( - tmax - tmin) * ra / lambd + pet = k / 0.0135 * 0.0023 * (tmean + 17.8) * sqrt(tmax - tmin) * ra / lambd elif method == 1: pet = k * chs * sqrt(tmax - tmin) * ra / lambd * (tmean + 17.8) else: - raise Exception("method can be either 0 or 1.") + raise Exception("Method can be either 0 or 1.") pet = clip_zeros(pet, clip_zero) - return pet.rename("Hargreaves") + return pet_out(tmean, pet, "Hargreaves") -def fao_24(tmean, wind, rs, rh, pressure=None, elevation=None, albedo=0.23, - clip_zero=True): +def fao_24( + tmean, wind, rs, rh, pressure=None, elevation=None, albedo=0.23, clip_zero=True +): """Potential evapotranspiration calculated according to :cite:t:`jensen_evapotranspiration_1990`. Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] - wind: float/pandas.Series/xarray.DataArray - mean day wind speed [m/s] - rs: float/pandas.Series/xarray.DataArray - incoming solar radiation [MJ m-2 d-1] - rh: float/pandas.Series/xarray.DataArray - mean daily relative humidity [%] - pressure: float/pandas.Series/xarray.DataArray, optional - atmospheric pressure [kPa] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + wind: pandas.Series xarray.DataArray + mean day wind speed [m/s]. + rs: pandas.Series xarray.DataArray + incoming solar radiation [MJ m-2 d-1]. + rh: pandas.Series or xarray.DataArray + mean daily relative humidity [%]. + pressure: pandas.Series or xarray.DataArray, optional + atmospheric pressure [kPa]. elevation: float/xarray.DataArray, optional - the site elevation [m] + the site elevation [m]. albedo: float/xarray.DataArray, optional - surface albedo [-] + surface albedo [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -258,12 +264,17 @@ def fao_24(tmean, wind, rs, rh, pressure=None, elevation=None, albedo=0.23, dlt = calc_vpc(tmean) lambd = calc_lambda(tmean) - w = 1.066 - 0.13 * check_rh( - rh) / 100 + 0.045 * wind - 0.02 * rh / 100 * wind - \ - 0.315 * (rh / 100) ** 2 - 0.0011 * wind - pe = -0.3 + dlt / (dlt + gamma) * check_rad(rs) * (1 - albedo) * w / lambd - pe = clip_zeros(pe, clip_zero) - return pe.rename("FAO_24") + w = ( + 1.066 + - 0.13 * check_rh(rh) / 100 + + 0.045 * wind + - 0.02 * rh / 100 * wind + - 0.315 * (rh / 100) ** 2 + - 0.0011 * wind + ) + pet = -0.3 + dlt / (dlt + gamma) * check_rad(rs) * (1 - albedo) * w / lambd + pet = clip_zeros(pet, clip_zero) + return pet_out(tmean, pet, "FAO_24") def abtew(tmean, rs, k=0.53, clip_zero=True): @@ -272,19 +283,19 @@ def abtew(tmean, rs, k=0.53, clip_zero=True): Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] - rs: float/pandas.Series/xarray.DataArray - incoming solar radiation [MJ m-2 d-1] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + rs: pandas.Series or xarray.DataArray + incoming solar radiation [MJ m-2 d-1]. k: float, optional - calibration coefficient [-] + calibration coefficient [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -298,9 +309,9 @@ def abtew(tmean, rs, k=0.53, clip_zero=True): """ lambd = calc_lambda(tmean) - pe = k * check_rad(rs) / lambd - pe = clip_zeros(pe, clip_zero) - return pe.rename("Abtew") + pet = k * check_rad(rs) / lambd + pet = clip_zeros(pet, clip_zero) + return pet_out(tmean, pet, "Abtew") def makkink(tmean, rs, pressure=None, elevation=None, k=0.65, clip_zero=True): @@ -309,23 +320,23 @@ def makkink(tmean, rs, pressure=None, elevation=None, k=0.65, clip_zero=True): Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] - rs: float/pandas.Series/xarray.DataArray - incoming solar radiation [MJ m-2 d-1] - pressure: float/pandas.Series/xarray.DataArray, optional - atmospheric pressure [kPa] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + rs: pandas.Series or xarray.DataArray + incoming solar radiation [MJ m-2 d-1]. + pressure: pandas.Series or xarray.DataArray, optional + atmospheric pressure [kPa]. elevation: float/xarray.DataArray, optional - the site elevation [m] + the site elevation [m]. k: float, optional - calirbation coefficient [-] + calirbation coefficient [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -343,30 +354,80 @@ def makkink(tmean, rs, pressure=None, elevation=None, k=0.65, clip_zero=True): lambd = calc_lambda(tmean) pet = k * dlt / (dlt + gamma) * check_rad(rs) / lambd pet = clip_zeros(pet, clip_zero) - return pet.rename("Makkink") + return pet_out(tmean, pet, "Makkink") + + +def makkink_knmi(tmean, rs, clip_zero=True): + """Potential evapotranspiration calculated according to The Royal Netherlands + Meteorological Institute (KNMI) + + Parameters + ---------- + tmean : pandas.Series or xarray.DataArray + average day temperature [°C]. + rs : pandas.Series or xarray.DataArray + incoming solar radiation [MJ m-2 d-1]. + clip_zero: bool, optional + if True, replace all negative values with 0. + + Returns + ------- + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. + + Examples + -------- + >>> pet_mak = makkink_knmi(tmean, rs) + + Notes + ---- + This method is only applicable to the Netherlands (~sea level) due to some + emperical values. Calculating the Makkink evaporation with the original + formula is more suitable for general purposes. To obtain the same value as + EV24 round the value up to one decimal. + """ + pet = ( + 650 + * ( + 1 + - (0.646 + 0.0006 * tmean) + / ( + 7.5 + * log(10) + * 6.107 + * 10 ** (7.5 * (1 - 1 / (1 + tmean / 237.3))) + / (237.3 * (1 + tmean / 237.3) * (1 + tmean / 237.3)) + + 0.646 + + 0.0006 * tmean + ) + ) + / (2501 - 2.38 * tmean) + * rs + ) + pet = clip_zeros(pet, clip_zero) + return pet_out(tmean, pet, "Makkink_KNMI") def oudin(tmean, lat, k1=100, k2=5, clip_zero=True): - """Potential evapotranspiration calculated according to - :cite:t:`oudin_which_2005`. + """Potential evapotranspiration calculated according to :cite:t:`oudin_which_2005`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - lat: float/xarray.DataArray - the site latitude [rad] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + lat: float or xarray.DataArray + the site latitude [rad]. k1: float, optional - calibration coefficient [-] + calibration coefficient [-]. k2: float, optional - calibration coefficient [-] + calibration coefficient [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. clip_zero: bool, optional if True, replace all negative values with 0. @@ -384,8 +445,8 @@ def oudin(tmean, lat, k1=100, k2=5, clip_zero=True): """ lambd = calc_lambda(tmean) index = get_index(tmean) - ra = extraterrestrial_r(index, check_lat(lat)) + ra = extraterrestrial_r(index, lat) pet = ra * (tmean + k2) / lambd / k1 - pet = pet.where(((tmean + k2) > 0) | (pet.isnull()), 0) + pet = pet.where((tmean + k2) >= 0, 0) pet = clip_zeros(pet, clip_zero) - return pet.rename("Oudin") + return pet_out(tmean, pet, "Oudin") diff --git a/pyet/temperature.py b/pyet/temperature.py index db41fe6..f47ea74 100644 --- a/pyet/temperature.py +++ b/pyet/temperature.py @@ -1,53 +1,65 @@ -"""The temperature module contains functions of temperature PET methods +"""The temperature module contains functions of temperature PET methods. """ -from numpy import exp, sum, pi +from numpy import exp, pi, asarray, newaxis from pandas import date_range +from xarray import DataArray from .meteo_utils import daylight_hours, calc_ea, calc_es, calc_e0 - -from pyet.utils import get_index, check_lat, clip_zeros, check_rh - - -def blaney_criddle(tmean, lat, a=-1.55, b=0.96, k=0.65, wind=None, rhmin=None, - n=None, nn=None, py=None, method=0, clip_zero=True): +from .utils import get_index, check_lat, clip_zeros, check_rh, pet_out + + +def blaney_criddle( + tmean, + lat, + a=-1.55, + b=0.96, + k=0.65, + wind=None, + rhmin=None, + n=None, + nn=None, + py=None, + method=0, + clip_zero=True, +): """Potential evapotranspiration calculated according to :cite:t:`blaney_determining_1952`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - lat: float/xarray.DataArray, optional - the site latitude [rad] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + lat: float or xarray.DataArray, optional + the site latitude [rad]. a: float, optional - calibration coefficient for method 0 [-] + calibration coefficient for method 0 [-]. b: float, optional - calibration coefficient for method 0 [-] + calibration coefficient for method 0 [-]. k: float, optional - calibration coefficient for method 1 [-] - wind: float/pandas.Series/xarray.DataArray, optional - mean day wind speed [m/s] - rhmin: float/pandas.Series/xarray.DataArray, optional - mainimum daily relative humidity [%] - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - nn: float/pandas.Series/xarray.DataArray, optional - maximum possible duration of sunshine or daylight hours [hour] - py: float/pandas.Series/xarray.DataArray, optional + calibration coefficient for method 1 [-]. + wind: float or pandas.Series or xarray.DataArray, optional + mean day wind speed [m/s]. + rhmin: float or pandas.Series or xarray.DataArray, optional + mainimum daily relative humidity [%]. + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + nn: float or pandas.Series or xarray.DataArray, optional + maximum possible duration of sunshine or daylight hours [hour]. + py: float or pandas.Series or xarray.DataArray, optional percentage of actual day-light hours for the day compared to the - number of day-light hour during the entire year [-] + number of day-light hour during the entire year [-]. method: float, optional 0 => Blaney Criddle after :cite:t:`schrodter_hinweise_1985` 1 => Blaney Criddle after :cite:t:`xu_evaluation_2001` - 2 => FAO-24 Blaney Criddle after :cite:t:`mcmahon_estimating_2013` + 2 => FAO-24 Blaney Criddle after :cite:t:`mcmahon_estimating_2013`. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated + float or pandas.Series or xarray.DataArray containing the calculated Potential evapotranspiration [mm d-1]. Examples @@ -81,10 +93,12 @@ def blaney_criddle(tmean, lat, a=-1.55, b=0.96, k=0.65, wind=None, rhmin=None, """ index = get_index(tmean) if nn is None: - nn = daylight_hours(index, check_lat(lat)) + nn = daylight_hours(index, lat) if py is None: nn_sum = sum(daylight_hours(date_range("2000-1-1", "2000-12-31"), lat)) py = nn / nn_sum * 100 + if isinstance(tmean, DataArray) and len(py.shape) == 1: + py = py[:, None, None] if method == 0: pet = a + b * (py * (0.457 * tmean + 8.128)) elif method == 1: @@ -92,16 +106,30 @@ def blaney_criddle(tmean, lat, a=-1.55, b=0.96, k=0.65, wind=None, rhmin=None, elif method == 2: nn_sum = sum(daylight_hours(date_range("2000-1-1", "2000-12-31"), lat)) py = n / nn_sum * 100 - k1 = (0.0043 * rhmin - n / nn - 1.41) - e0, e1, e2, e3, e4, e5 = (0.81917, -0.0040922, 1.0705, 0.065649, - -0.0059684, -0.0005967) - bvar = e0 + e1 * rhmin + e2 * n / nn + e3 * wind + e4 * rhmin * n / \ - nn + e5 * rhmin * wind + if isinstance(rhmin, DataArray) and len(nn.shape) == 1: + nn = nn[:, None, None] + k1 = 0.0043 * rhmin - n / nn - 1.41 + e0, e1, e2, e3, e4, e5 = ( + 0.81917, + -0.0040922, + 1.0705, + 0.065649, + -0.0059684, + -0.0005967, + ) + bvar = ( + e0 + + e1 * rhmin + + e2 * n / nn + + e3 * wind + + e4 * rhmin * n / nn + + e5 * rhmin * wind + ) pet = k1 + bvar * py * (0.46 * tmean + 8.13) else: - raise Exception("method can be either 0, 1 or 2.") + raise Exception("Method can be either 0, 1 or 2.") pet = clip_zeros(pet, clip_zero) - return pet.rename("Blaney_Criddle") + return pet_out(tmean, pet, "Blaney_Criddle") def haude(tmean, rh, k=1, clip_zero=True): @@ -110,19 +138,19 @@ def haude(tmean, rh, k=1, clip_zero=True): Parameters ---------- - tmean: pandas.Series/xarray.DataArray - temperature at 2pm or maximum dailty temperature [°C] - rh: float/pandas.Series/xarray.DataArray - average relative humidity at 2pm [%] + tmean: pandas.Series or xarray.DataArray + temperature at 2pm or maximum dailty temperature [°C]. + rh: float or pandas.Series or xarray.DataArray + average relative humidity at 2pm [%]. k: float, optional - calibration coefficient [-] + calibration coefficient [-]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + float or pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -130,8 +158,7 @@ def haude(tmean, rh, k=1, clip_zero=True): Notes ----- - Following :cite:t:`haude_determination_1955` and - :cite:t:`schiff_berechnung_1975`. + Following :cite:t:`haude_determination_1955` and :cite:t:`schiff_berechnung_1975`. .. math:: PET = k * f * (e_s-e_a) @@ -139,38 +166,51 @@ def haude(tmean, rh, k=1, clip_zero=True): e0 = calc_e0(tmean) ea = check_rh(rh) * e0 / 100 # Haude coefficients from :cite:t:`schiff_berechnung_1975` - fk = [0.27, 0.27, 0.28, 0.39, 0.39, 0.37, 0.35, 0.33, 0.31, 0.29, 0.27, - 0.27] + fk = [0.27, 0.27, 0.28, 0.39, 0.39, 0.37, 0.35, 0.33, 0.31, 0.29, 0.27, 0.27] index = get_index(tmean) - f = ([fk[x - 1] for x in index.month] * (tmean / tmean).T).T + fk1 = asarray([fk[x - 1] for x in index.month]) + if len(tmean.shape) > 1: + f = fk1[:, newaxis, newaxis] * (tmean / tmean) + else: + f = fk1 pet = k * f * (e0 - ea) * 10 # kPa to hPa pet = clip_zeros(pet, clip_zero) - return pet.rename("Haude") - - -def hamon(tmean, lat, k=1, c=13.97, cc=218.527, n=None, tmax=None, tmin=None, - method=0, clip_zero=True): + return pet_out(tmean, pet, "Haude") + + +def hamon( + tmean, + lat, + k=1, + c=13.97, + cc=218.527, + n=None, + tmax=None, + tmin=None, + method=0, + clip_zero=True, +): """Potential evapotranspiration calculated according to :cite:t:`hamon_estimating_1963`. Parameters ---------- - tmean: pandas.Series/xarray.DataArray - average day temperature [°C] - lat: float/xarray.DataArray - the site latitude [rad] + tmean: pandas.Series or xarray.DataArray + average day temperature [°C]. + lat: float or xarray.DataArray + the site latitude [rad]. k: float, optional - calibration coefficient if method = 0 [-] + calibration coefficient if method = 0 [-]. c: float, optional c is a constant for calculation in mm per day if method = 1. cc: float, optional calibration coefficient if method = 2 [-]. - n: float/pandas.Series/xarray.DataArray, optional - actual duration of sunshine [hour] - tmax: float/pandas.Series/xarray.DataArray - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray - minimum day temperature [°C] + n: float or pandas.Series or xarray.DataArray, optional + actual duration of sunshine [hour]. + tmax: float or pandas.Series or xarray.DataArray + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray + minimum day temperature [°C]. method: float, optional 0 => Hamon after :cite:t:`oudin_which_2005` @@ -182,8 +222,8 @@ def hamon(tmean, lat, k=1, c=13.97, cc=218.527, n=None, tmax=None, tmin=None, Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + float or pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -216,7 +256,9 @@ def hamon(tmean, lat, k=1, c=13.97, cc=218.527, n=None, tmax=None, tmin=None, """ index = get_index(tmean) # Use transpose to work with lat either as int or xarray.DataArray - dl = daylight_hours(index, check_lat(lat)) + dl = daylight_hours(index, lat) + if len(dl.shape) < len(tmean.shape): + dl = tmean / tmean * dl[:, newaxis, newaxis] if method == 0: pet = k * (dl / 12) ** 2 * exp(tmean / 16) elif method == 1: @@ -224,46 +266,51 @@ def hamon(tmean, lat, k=1, c=13.97, cc=218.527, n=None, tmax=None, tmin=None, pt = 4.95 * exp(0.062 * tmean) / 100 pet = c * (dl / 12) ** 2 * pt elif method == 2: - pet = cc * (dl / 12) * 1 / (tmean + 273.3) * exp( - (17.26939 * tmean) / (tmean + 273.3)) + pet = ( + cc + * (dl / 12) + * 1 + / (tmean + 273.3) + * exp((17.26939 * tmean) / (tmean + 273.3)) + ) elif method == 3: es = calc_es(tmean, tmax, tmin) - pet = k * 14 * (n / 12) ** 2 * ( - 216.7 * es * 10 / (tmean + 273.3)) / 100 + pet = k * 14 * (n / 12) ** 2 * (216.7 * es * 10 / (tmean + 273.3)) / 100 else: raise Exception("method can be either 0, 1, 2 or 3.") pet = clip_zeros(pet, clip_zero) - return pet.rename("Hamon") + return pet_out(tmean, pet, "Hamon") -def romanenko(tmean, rh, k=4.5, rhmax=None, rhmin=None, tmax=None, tmin=None, - clip_zero=True): +def romanenko( + tmean, rh, k=4.5, rhmax=None, rhmin=None, tmax=None, tmin=None, clip_zero=True +): """Potential evapotranspiration calculated according to :cite:t:`romanenko_computation_1961`. Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] - rh: float/pandas.Series/xarray.DataArray - mean daily relative humidity [%] + tmean: float or pandas.Series or xarray.DataArray + average day temperature [°C]. + rh: float or pandas.Series or xarray.DataArray + mean daily relative humidity [%]. k: float, optional - calibration coefficient [-] - tmax: float/pandas.Series/xarray.DataArray - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray - minimum day temperature [°C] + calibration coefficient [-]. + tmax: float or pandas.Series or xarray.DataArray + maximum day temperature [°C]. + tmin: float or pandas.Series or xarray.DataArray + minimum day temperature [°C]. rhmax: pandas.Series, optional - maximum daily relative humidity [%] + maximum daily relative humidity [%]. rhmin: pandas.Series, optional - mainimum daily relative humidity [%] + mainimum daily relative humidity [%]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + float or pandas.Series or xarray.DataArray containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -276,40 +323,45 @@ def romanenko(tmean, rh, k=4.5, rhmax=None, rhmin=None, tmax=None, tmin=None, .. math:: PET=k(1 + (\\frac{T_{mean}}{25})^2 (1 - \\frac{e_a}{e_s}) """ - ea = calc_ea(tmean=tmean, tmax=tmax, tmin=tmin, rhmax=check_rh(rhmax), - rhmin=check_rh(rhmin), rh=check_rh(rh)) + ea = calc_ea( + tmean=tmean, + tmax=tmax, + tmin=tmin, + rhmax=check_rh(rhmax), + rhmin=check_rh(rhmin), + rh=check_rh(rh), + ) es = calc_es(tmean=tmean, tmax=tmax, tmin=tmin) pet = k * (1 + tmean / 25) ** 2 * (1 - ea / es) pet = clip_zeros(pet, clip_zero) - return pet.rename("Romanenko") + return pet_out(tmean, pet, "Romanenko") -def linacre(tmean, elevation, lat, tdew=None, tmax=None, tmin=None, - clip_zero=True): +def linacre(tmean, elevation, lat, tdew=None, tmax=None, tmin=None, clip_zero=True): """Potential evapotranspiration calculated according to :cite:t:`linacre_simple_1977`. Parameters ---------- - tmean: float/pandas.Series/xarray.DataArray - average day temperature [°C] - elevation: float/xarray.DataArray - the site elevation [m] - lat: float/xarray.DataArray, optional - the site latitude [°] - tdew: float/pandas.Series/xarray.DataArray, optional - mean dew-point temperature [°C] - tmax: float/pandas.Series/xarray.DataArray, optional - maximum day temperature [°C] - tmin: float/pandas.Series/xarray.DataArray, optional - minimum day temperature [°C] + tmean: pandas.Series or array_like + average day temperature [°C]. + elevation: array_like + the site elevation [m]. + lat: array_like, optional + the site latitude [°]. + tdew: pandas.Series or array_like, optional + mean dew-point temperature [°C]. + tmax: pandas.Series or array_like, optional + maximum day temperature [°C]. + tmin: pandas.Series or array_like, optional + minimum day temperature [°C]. clip_zero: bool, optional if True, replace all negative values with 0. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - Potential evapotranspiration [mm d-1]. + pandas.Series or array_like containing the calculated potential + evapotranspiration [mm d-1]. Examples -------- @@ -322,11 +374,15 @@ def linacre(tmean, elevation, lat, tdew=None, tmax=None, tmin=None, .. math:: PET = \\frac{\\frac{500 T_m}{(100-lat)}+15 (T_a-T_d)}{80-T_a} """ + if tdew is None and tmax is None and tmin is None: + raise Exception("Please provide either Tdew or Tmax and Tmin!") + lat = check_lat(lat) lat_deg = lat / pi * 180 if tdew is None: - tdew = 0.52 * tmin + 0.6 * tmax - 0.009 * tmax ** 2 - 2 + tmax, tmin = tmax.values, tmin.values + tdew = 0.52 * tmin + 0.6 * tmax - 0.009 * tmax**2 - 2 + tm = tmean + 0.006 * elevation - pet = (500 * tm / (100 - lat_deg) + 15 * (tmean - tdew)) / ( - 80 - tmean) + pet = (500 * tm / (100 - lat_deg) + 15 * (tmean - tdew)) / (80 - tmean) pet = clip_zeros(pet, clip_zero) - return pet.rename("Linacre") + return pet_out(tmean, pet, "Linacre") diff --git a/pyet/utils.py b/pyet/utils.py index 7894d2d..be1b04e 100644 --- a/pyet/utils.py +++ b/pyet/utils.py @@ -1,20 +1,21 @@ import numpy -import pandas +from pandas import Series, DatetimeIndex +from xarray import DataArray def show_versions(): - """Method to print the version of dependencies. - - """ + """Method to print the version of dependencies.""" from pyet import __version__ as ps_version from pandas import __version__ as pd_version from numpy import __version__ as np_version from sys import version as os_version + from xarray import __version__ as xr_version msg = ( f"Python version: {os_version}\n" f"Numpy version: {np_version}\n" f"Pandas version: {pd_version}\n" + f"xarray version: {xr_version}\n" f"Pyet version: {ps_version}" ) return print(msg) @@ -22,73 +23,106 @@ def show_versions(): def deg_to_rad(lat): """Method to convert latitude in degrees to radians. - lat: float/xarray.DataArray - the site latitude [deg] + + Parameters + ---------- + lat: float or xarray.DataArray + The site latitude [deg]. Returns ------- - float/pandas.Series/xarray.DataArray containing the calculated - latitude in radians [rad]. + float or pandas.Series or xarray.DataArray containing the calculated latitude in + radians [rad]. """ return lat * numpy.pi / 180 def check_rad(rad): - """Method to check if radiation was provided in MJ/m2d.""" + """Method to check if radiation was probably provided in MJ/m2d.""" if rad is not None: - if numpy.max(rad) < 100: + if numpy.nanmax(rad) < 100: return rad else: raise Exception( "The radiation input provided is greater than 100 MJ/m2d, " "which is not realistic. Please convert the radiation input" - " to MJ/m2d.") + " to MJ/m2d." + ) def check_rh(rh): """Method to check if relative humidity is provided in percentage.""" if rh is not None: - if numpy.max(rh) > 1.0: + if numpy.nanmax(rh) > 1.0: return rh else: raise Exception( "The maximum value of relative humidity provided is smaller " "than 1 [%], which is not realistic. Please convert the " - "relative humidity to [%].") + "relative humidity to [%]." + ) else: pass -def check_lat(lat): +def check_lat(lat, shape=None): """Method to check if latitude was (most likely) given in radians.""" - if lat is None: - pass + if not isinstance(lat, (float, int, DataArray)): + raise TypeError("lat must be a float, int or DataArray") + if isinstance(lat, (float, int)) and (shape is None or len(shape) == 1): + lat1 = lat else: - if -1.6 < numpy.mean(lat) < 1.6: - return lat - else: - raise Exception( - "Latitude must be provided in radians! Use pyet.deg_to_rad()" - "to convert from degrees to radians.") + if isinstance(lat, (float, int)) and (len(shape) > 1): + raise ValueError(f"lat must be a shaped as 2D DataArray") + lat1 = lat.values + if not (-1.6 < numpy.mean(lat1) < 1.6): + raise Exception( + "Latitude must be provided in radians! Use pyet.deg_to_rad()" + "to convert from degrees to radians." + ) + return lat1 def clip_zeros(s, clip_zero): - """Method to replace negative values with 0 for Pandas.Series and - xarray.DataArray. - - """ + """Method to replace negative values with 0 for Pandas.Series and xarray.DataArray.""" if clip_zero: - return s.where((s > 0) | (s.isnull()), 0) + s = s.where((s >= 0) | s.isnull(), 0) + return s + + +def pet_out(tmean, pet, name): + """Method to create pandas.Series or xarray.DataArray from numpy.ndarray""" + if isinstance(tmean, (Series, DataArray)): + return pet.rename(name) else: - return s + raise TypeError("Input must be either pandas.Series or xarray.DataArray!") def get_index(df): - """Method to return the index of the input data. - - """ + """Method to return the index of the input data.""" try: - index = pandas.DatetimeIndex(df.index) + index = DatetimeIndex(df.index) except AttributeError: - index = pandas.DatetimeIndex(df.time) + index = DatetimeIndex(df.time) return index + + +def vectorize(*arrays): + """Vectorize pandas.Series or xarray.DataArray inputs.""" + vec_arrays = [] + for arr in arrays: + if arr is None: + vec_arr = None + elif isinstance(arr, (int, float)): + vec_arr = arr + elif isinstance(arr, Series): + vec_arr = arr.copy().values + elif isinstance(arr, DataArray): + vec_arr = arr.copy().values + else: + raise TypeError( + f"Input must be a pandas.Series or xarray.DataArray, " + f"but got {type(arr)}" + ) + vec_arrays.append(vec_arr) + return vec_arrays diff --git a/pyet/version.py b/pyet/version.py index e93c678..d88270b 100644 --- a/pyet/version.py +++ b/pyet/version.py @@ -1,3 +1,3 @@ # This is the only location where the version will be written and changed. # Based on https://packaging.python.org/single_source_version/ -__version__ = "1.2.2" +__version__ = "1.3.0" diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..659f390 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,64 @@ +[build-system] +requires = ["setuptools", "wheel"] + +[project] +name = "pyet" +dynamic = ["version"] +description = "pyet - Estimation of Potential Evaporation" +readme = "README.md" +authors = [ + {name = "Matevz Vremec", email = "matevz.vremec@uni-graz.at"}, + {name = "Raoul Collenteur", email = "raoul.collenteur@eawag.ch"} +] +license = { file = "LICENSE" } +requires-python = ">=3.9" +dependencies = [ + "numpy >= 1.16", + "xarray >= 0.18.0", + "pandas >= 1.2", +] +classifiers = [ + 'Development Status :: 5 - Production/Stable', + 'Intended Audience :: Science/Research', + 'Intended Audience :: Other Audience', + 'License :: OSI Approved :: MIT License', + 'Programming Language :: Python :: 3 :: Only', + 'Programming Language :: Python :: 3.9', + 'Programming Language :: Python :: 3.10', + 'Programming Language :: Python :: 3.11', + 'Programming Language :: Python :: 3.12', + 'Topic :: Scientific/Engineering :: Hydrology', +] + +[project.urls] +Source = "https://github.com/phydrus/pyet" +Tracker = "https://github.com/phydrus/pyet/issues" +Help = "https://github.com/phydrus/pyet/discussions" +homepage = "https://github.com/phydrus/pyet" +repository = "https://github.com/phydrus/pyet" +documentation = "https://github.com/phydrus/pyet/discussions" + +[tool.setuptools.dynamic] +version = { attr = "pyet.version.__version__" } + +[tool.black] +line-length = 88 + +[tool.isort] +profile = "black" + +[tool.pytest.ini_options] +testpaths = ["tests"] + +[project.optional-dependencies] +rtd = [ + "sphinx-autodoc-typehints", + "Ipython", + "ipykernel", + "pydata-sphinx-theme", + "sphinx-gallery", + "sphinx>=3.1", + "sphinxcontrib-bibtex", + "matplotlib", + "myst-nb", +] \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index e506980..61583df 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,3 +1,5 @@ -numpy >= 1.16 +numpy>=1.16 xarray>=0.18.0 -pandas >= 1.2 +pandas>=1.2 +flake8 +pytest \ No newline at end of file diff --git a/requirements_rtd.txt b/requirements_rtd.txt deleted file mode 100644 index c925204..0000000 --- a/requirements_rtd.txt +++ /dev/null @@ -1,11 +0,0 @@ -numpy>=1.15 -pandas>=1.0 -xarray>=0.18.0 -Ipython -ipykernel -nbsphinx -nbsphinx_link -pydata-sphinx-theme -sphinx-gallery -sphinx>=3.1 -sphinxcontrib-bibtex \ No newline at end of file diff --git a/setup.py b/setup.py deleted file mode 100644 index 2061b08..0000000 --- a/setup.py +++ /dev/null @@ -1,44 +0,0 @@ -from setuptools import setup, find_packages - -with open("README.md", "r") as fh: - long_description = fh.read() - -# Get the version. -version = {} -with open("pyet/version.py") as fp: - exec(fp.read(), version) - -setup( - name='pyet', - version=version['__version__'], - url='https://github.com/phydrus/pyet', - license='MIT License', - author='Matevz Vremec, Raoul Collenteur', - author_email='matevz.vremec@uni-graz.at, raoul.collenteur@uni-graz.at', - description='pyet - Estimation of Potential Evaporation', - long_description=long_description, - long_description_content_type="text/markdown", - test_suite='tests', - project_urls={ - 'Source': 'https://github.com/phydrus/pyet', - 'Tracker': 'https://github.com/phydrus/pyet/issues', - 'Help': 'https://github.com/phydrus/pyet/discussions' - }, - classifiers=[ - 'Development Status :: 4 - Beta', - 'Intended Audience :: Science/Research', - 'Intended Audience :: Other Audience', - 'License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)', - 'Programming Language :: Python :: 3.7', - 'Programming Language :: Python :: 3.8', - 'Programming Language :: Python :: 3.9', - 'Programming Language :: Python :: 3.10', - 'Topic :: Scientific/Engineering :: Hydrology', - ], - install_requires=['numpy>=1.15', - 'xarray>=0.18.0', - 'pandas>=1.0', - ], - packages=find_packages(exclude=[]), - -) diff --git a/tests/test_rpackage.py b/tests/test_rpackage.py new file mode 100644 index 0000000..f0e3013 --- /dev/null +++ b/tests/test_rpackage.py @@ -0,0 +1,753 @@ +import unittest + +from numpy import full, log, tile, newaxis, asarray +import pandas as pd +from xarray import DataArray, testing + +import pyet as et + + +class Testr(unittest.TestCase): + lat = -0.6095 + elevation = 48 + + tmax = pd.Series( + [28.8, 27.4, 29.0, 26.3, 32.7, 35.7, 33.8, 33.8, 35.6, 27.5], + index=pd.date_range("2001-03-01", "2001-03-10", freq="d"), + ) + tmin = pd.Series( + [15.1, 14.0, 16.3, 16.2, 17.8, 26.7, 20.6, 22.3, 22.7, 17.1], + index=pd.date_range("2001-03-01", "2001-03-10", freq="d"), + ) + tmean = (tmax + tmin) / 2 + rhmax = pd.Series( + [68, 77, 69, 70, 73, 36, 51, 46, 34, 67], + index=pd.date_range("2001-03-01", "2001-03-10", freq="d"), + ) + rhmin = pd.Series( + [30, 25, 30, 34, 29, 20, 18, 18, 10, 30], + index=pd.date_range("2001-03-01", "2001-03-10", freq="d"), + ) + rh = (rhmax + rhmin) / 2 + rs = pd.Series( + [ + 20.44477761, + 20.34991941, + 20.25373437, + 20.1562439, + 20.05747057, + 19.95743816, + 19.85617161, + 19.75369701, + 19.65004162, + 19.54523386, + ], + index=pd.date_range("2001-03-01", "2001-03-10", freq="d"), + ) + uz = pd.Series( + [ + 2.65625, + 2.78472222, + 2.49305556, + 3.73611111, + 3.30902778, + 4.93402778, + 2.90972222, + 4.48958333, + 3.99305556, + 4.31597222, + ], + index=pd.date_range("2001-03-01", "2001-03-10", freq="d"), + ) + n = pd.Series( + [8.6, 8.6, 8.6, 8.6, 8.6, 8.6, 8.6, 8.6, 8.6, 8.6], + index=pd.date_range("2001-03-01", "2001-03-10", freq="d"), + ) + lambda0 = 2.45 # Lambda in Danlu R Evapotranspiration package + lambda1 = et.calc_lambda(tmean) # Lambda in pyet + lambda_corr = lambda1 / lambda0 + + # Number of x and y dimensions + x_dim, y_dim = 3, 3 + lat_xr = DataArray( + full((3, 3), lat), + coords=[("y", range(y_dim)), ("x", range(x_dim))], + ) + elevation_xr = DataArray( + full((3, 3), elevation), + coords=[("y", range(y_dim)), ("x", range(x_dim))], + ) + # Covert pandas Series to xarray DataArray + tmax_xr = tile(tmax.values[:, newaxis, newaxis], (1, x_dim, y_dim)) + tmax_xr = DataArray( + tmax_xr, + coords={"time": tmax.index, "y": range(y_dim), "x": range(x_dim)}, + dims=["time", "y", "x"], + ) + # Covert pandas Series to xarray DataArray + tmin_xr = tile(tmin.values[:, newaxis, newaxis], (1, x_dim, y_dim)) + tmin_xr = DataArray( + tmin_xr, + coords={"time": tmin.index, "y": range(y_dim), "x": range(x_dim)}, + dims=["time", "y", "x"], + ) + tmean_xr = (tmax_xr + tmin_xr) / 2 + rhmax_xr = tile(rhmax.values[:, newaxis, newaxis], (1, x_dim, y_dim)) + rhmax_xr = DataArray( + rhmax_xr, + coords={"time": rhmax.index, "y": range(y_dim), "x": range(x_dim)}, + dims=["time", "y", "x"], + ) + rhmin_xr = tile(rhmin.values[:, newaxis, newaxis], (1, x_dim, y_dim)) + rhmin_xr = DataArray( + rhmin_xr, + coords={"time": rhmin.index, "y": range(y_dim), "x": range(x_dim)}, + dims=["time", "y", "x"], + ) + rh_xr = (rhmax_xr + rhmin_xr) / 2 + rs_xr = tile(rs.values[:, newaxis, newaxis], (1, x_dim, y_dim)) + rs_xr = DataArray( + rs_xr, + coords={"time": rs.index, "y": range(y_dim), "x": range(x_dim)}, + dims=["time", "y", "x"], + ) + uz_xr = tile(uz.values[:, newaxis, newaxis], (1, x_dim, y_dim)) + uz_xr = DataArray( + uz_xr, + coords={"time": uz.index, "y": range(y_dim), "x": range(x_dim)}, + dims=["time", "y", "x"], + ) + n_xr = tile(n.values[:, newaxis, newaxis], (1, x_dim, y_dim)) + n_xr = DataArray( + n_xr, + coords={"time": n.index, "y": range(y_dim), "x": range(x_dim)}, + dims=["time", "y", "x"], + ) + + def test_penman(self): + wind_penman = Testr.uz * log(2 / 0.001) / log(10 / 0.001) + pyet_penman = ( + ( + et.penman( + Testr.tmean, + wind_penman, + rs=Testr.rs, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax, + tmin=Testr.tmin, + rh=Testr.rh, + rhmax=Testr.rhmax, + rhmin=Testr.rhmin, + aw=2.626, + bw=1.381, + albedo=0.08, + ) + * Testr.lambda_corr + ) + .round(1) + .tolist() + ) + r_penman = [6.8, 6.7, 6.7, 6.9, 7.6, 10.1, 7.9, 9.2, 9.4, 7.3] + self.assertEqual(r_penman, pyet_penman, 1) + + expected_penman = tile(asarray(r_penman)[:, newaxis, newaxis], (1, 3, 3)) + expected_penman = DataArray( + expected_penman, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + wind_penman_xr = Testr.uz_xr * log(2 / 0.001) / log(10 / 0.001) + penman_xr = ( + et.penman( + Testr.tmean_xr, + wind_penman_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + aw=2.626, + bw=1.381, + albedo=0.08, + ) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(penman_xr.round(1), expected_penman.round(1)) + penman_xr1 = ( + et.penman( + Testr.tmean_xr, + wind_penman_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation_xr, + lat=Testr.lat_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + aw=2.626, + bw=1.381, + albedo=0.08, + ) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(penman_xr1.round(1), expected_penman.round(1)) + + def test_fao56(self): + wind = Testr.uz * 4.87 / log(67.8 * 10 - 5.42) + pyet_fao56 = ( + et.pm_fao56( + Testr.tmean, + wind, + rs=Testr.rs, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax, + tmin=Testr.tmin, + rh=Testr.rh, + rhmax=Testr.rhmax, + rhmin=Testr.rhmin, + ) + .round(1) + .tolist() + ) + r_fao56 = [5.1, 5.0, 5.0, 5.2, 5.9, 8.8, 6.3, 7.8, 8.0, 5.7] + self.assertEqual(r_fao56, pyet_fao56, 1) + + expected_fao56 = tile(asarray(r_fao56)[:, newaxis, newaxis], (1, 3, 3)) + expected_fao56 = DataArray( + expected_fao56, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + wind_xr = Testr.uz_xr * 4.87 / log(67.8 * 10 - 5.42) + calculated_fao56 = et.pm_fao56( + Testr.tmean_xr, + wind_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + ) + testing.assert_allclose(calculated_fao56.round(1), expected_fao56.round(1)) + calculated_fao561 = et.pm_fao56( + Testr.tmean_xr, + wind_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation_xr, + lat=Testr.lat_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + ) + testing.assert_allclose(calculated_fao561.round(1), expected_fao56.round(1)) + + def test_pm(self): + wind = Testr.uz * 4.87 / log(67.8 * 10 - 5.42) + pyet_pm = ( + ( + et.pm( + Testr.tmean, + wind, + rs=Testr.rs, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax, + tmin=Testr.tmin, + rh=Testr.rh, + rhmax=Testr.rhmax, + rhmin=Testr.rhmin, + ) + * Testr.lambda_corr + ) + .round(1) + .tolist() + ) + r_fao56 = [5.1, 5.0, 5.0, 5.2, 5.9, 8.8, 6.3, 7.8, 8.0, 5.7] + self.assertEqual(r_fao56, pyet_pm, 1) + + expected_pm = tile(asarray(r_fao56)[:, newaxis, newaxis], (1, 3, 3)) + expected_pm = DataArray( + expected_pm, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + wind_xr = Testr.uz_xr * 4.87 / log(67.8 * 10 - 5.42) + calculated_pm = ( + et.pm( + Testr.tmean_xr, + wind_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + ) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calculated_pm.round(1), expected_pm.round(1)) + calculated_pm1 = ( + et.pm( + Testr.tmean_xr, + wind_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation_xr, + lat=Testr.lat_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + ) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calculated_pm1.round(1), expected_pm.round(1)) + + def test_asce_pm(self): + wind = Testr.uz * 4.87 / log(67.8 * 10 - 5.42) + pyet_pm = ( + et.pm_asce( + Testr.tmean, + wind, + rs=Testr.rs, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax, + tmin=Testr.tmin, + rh=Testr.rh, + rhmax=Testr.rhmax, + rhmin=Testr.rhmin, + ) + .round(1) + .tolist() + ) + r_fao56 = [5.1, 5.0, 5.0, 5.2, 5.9, 8.8, 6.3, 7.8, 8.0, 5.7] + self.assertEqual(r_fao56, pyet_pm, 1) + + expected_pm = tile(asarray(r_fao56)[:, newaxis, newaxis], (1, 3, 3)) + expected_pm = DataArray( + expected_pm, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + wind_xr = Testr.uz_xr * 4.87 / log(67.8 * 10 - 5.42) + calculated_pm = et.pm_asce( + Testr.tmean_xr, + wind_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation, + lat=Testr.lat, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + ) + testing.assert_allclose(calculated_pm.round(1), expected_pm.round(1)) + calculated_pm1 = et.pm_asce( + Testr.tmean_xr, + wind_xr, + rs=Testr.rs_xr, + elevation=Testr.elevation_xr, + lat=Testr.lat_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rh=Testr.rh_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + ) + testing.assert_allclose(calculated_pm1.round(1), expected_pm.round(1)) + + def test_makkink(self): + pyet_makk = ( + ( + et.makkink(Testr.tmean, rs=Testr.rs, elevation=Testr.elevation, k=0.61) + * Testr.lambda_corr + - 0.12 + ) + .round(1) + .tolist() + ) + r_makkink = [3.5, 3.4, 3.5, 3.4, 3.6, 3.8, 3.6, 3.7, 3.7, 3.3] + self.assertEqual(r_makkink, pyet_makk, 1) + + expected_makkink = tile(asarray(r_makkink)[:, newaxis, newaxis], (1, 3, 3)) + expected_makkink = DataArray( + expected_makkink, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calculated_makk = ( + et.makkink( + Testr.tmean_xr, rs=Testr.rs_xr, elevation=Testr.elevation, k=0.61 + ) + * Testr.lambda_corr.values[:, None, None] + - 0.12 + ) + testing.assert_allclose(calculated_makk.round(1), expected_makkink.round(1)) + calculated_makk1 = ( + et.makkink( + Testr.tmean_xr, rs=Testr.rs_xr, elevation=Testr.elevation_xr, k=0.61 + ) + * Testr.lambda_corr.values[:, None, None] + - 0.12 + ) + testing.assert_allclose(calculated_makk1.round(1), expected_makkink.round(1)) + + def test_makkink_knmi(self): + pyet_makk_knmi = et.makkink_knmi(Testr.tmean, rs=Testr.rs).round(1).tolist() + r_makkink = [3.8, 3.8, 3.9, 3.8, 4.0, 4.3, 4.0, 4.1, 4.1, 3.7] + self.assertEqual(r_makkink, pyet_makk_knmi, 1) + + expected_makkink = tile(asarray(r_makkink)[:, newaxis, newaxis], (1, 3, 3)) + expected_makkink = DataArray( + expected_makkink, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + makk_knmi = et.makkink_knmi(Testr.tmean_xr, rs=Testr.rs_xr) + testing.assert_allclose(makk_knmi.round(1), expected_makkink.round(1)) + + def test_pt(self): + pyet_pt = ( + ( + et.priestley_taylor( + Testr.tmean, + rs=Testr.rs, + lat=Testr.lat, + elevation=Testr.elevation, + tmax=Testr.tmax, + tmin=Testr.tmin, + rhmax=Testr.rhmax, + rhmin=Testr.rhmin, + rh=Testr.rh, + ) + * Testr.lambda_corr + ) + .round(1) + .tolist() + ) + r_pt = [4.0, 3.9, 4.0, 3.9, 4.2, 4.1, 3.9, 3.9, 3.6, 3.7] + self.assertEqual(r_pt, pyet_pt, 1) + + expected_pt = tile(asarray(r_pt)[:, newaxis, newaxis], (1, 3, 3)) + expected_pt = DataArray( + expected_pt, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calculated_pt = ( + et.priestley_taylor( + Testr.tmean_xr, + rs=Testr.rs_xr, + lat=Testr.lat, + elevation=Testr.elevation, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + rh=Testr.rh_xr, + ) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calculated_pt.round(1), expected_pt.round(1)) + calculated_pt1 = ( + et.priestley_taylor( + Testr.tmean_xr, + rs=Testr.rs_xr, + lat=Testr.lat_xr, + elevation=Testr.elevation_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + rh=Testr.rh_xr, + ) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calculated_pt1.round(1), expected_pt.round(1)) + + def test_hargreaves(self): + pyet_har = ( + (et.hargreaves(Testr.tmean, Testr.tmax, Testr.tmin, Testr.lat, method=1)) + .round(1) + .tolist() + ) + r_har = [4.6, 4.3, 4.3, 3.7, 5.4, 4.6, 4.8, 4.4, 4.9, 3.7] + self.assertEqual(r_har, pyet_har, 1) + + expected_har = tile(asarray(r_har)[:, newaxis, newaxis], (1, 3, 3)) + expected_har = DataArray( + expected_har, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calculated_har = et.hargreaves( + Testr.tmean_xr, Testr.tmax_xr, Testr.tmin_xr, Testr.lat, method=1 + ) + testing.assert_allclose(calculated_har.round(1), expected_har.round(1)) + calculated_har1 = et.hargreaves( + Testr.tmean_xr, Testr.tmax_xr, Testr.tmin_xr, Testr.lat_xr, method=1 + ) + testing.assert_allclose(calculated_har1.round(1), expected_har.round(1)) + + def test_hamon(self): + pyet_pm = ( + et.hamon( + Testr.tmean, + lat=Testr.lat, + n=Testr.n, + tmax=Testr.tmax, + tmin=Testr.tmin, + method=3, + ) + .round(1) + .tolist() + ) + r_hamon = [1.5, 1.4, 1.5, 1.4, 1.8, 2.4, 2.0, 2.1, 2.2, 1.5] + self.assertEqual(r_hamon, pyet_pm, 1) + + expected_ham = tile(asarray(r_hamon)[:, newaxis, newaxis], (1, 3, 3)) + expected_ham = DataArray( + expected_ham, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calculated_ham = et.hamon( + Testr.tmean_xr, + lat=Testr.lat, + n=Testr.n_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + method=3, + ) + testing.assert_allclose(calculated_ham.round(1), expected_ham.round(1)) + calculated_ham1 = et.hamon( + Testr.tmean_xr, + lat=Testr.lat_xr, + n=Testr.n_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + method=3, + ) + testing.assert_allclose(calculated_ham1.round(1), expected_ham.round(1)) + + def test_blaney_criddle(self): + wind = Testr.uz * 4.87 / log(67.8 * 10 - 5.42) + pyet_bc = ( + ( + et.blaney_criddle( + Testr.tmean, + Testr.lat, + rhmin=Testr.rhmin, + wind=wind, + method=2, + n=Testr.n, + clip_zero=False, + ) + ) + .round(1) + .tolist() + ) + r_bc = [3.0, 3.0, 3.1, 2.9, 3.6, 5.0, 4.1, 4.5, 4.9, 3.3] + self.assertEqual(r_bc, pyet_bc, 1) + + expected_bc = tile(asarray(r_bc)[:, newaxis, newaxis], (1, 3, 3)) + expected_bc = DataArray( + expected_bc, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + wind_xr = Testr.uz_xr * 4.87 / log(67.8 * 10 - 5.42) + calculated_bc = et.blaney_criddle( + Testr.tmean_xr, + Testr.lat, + rhmin=Testr.rhmin_xr, + wind=wind_xr, + method=2, + n=Testr.n_xr, + clip_zero=False, + ) + testing.assert_allclose(calculated_bc.round(1), expected_bc.round(1)) + calculated_bc1 = et.blaney_criddle( + Testr.tmean_xr, + Testr.lat_xr, + rhmin=Testr.rhmin_xr, + wind=wind_xr, + method=2, + n=Testr.n_xr, + clip_zero=False, + ) + testing.assert_allclose(calculated_bc1.round(1), expected_bc.round(1)) + + def test_romanenko(self): + pyet_romanenko = ( + ( + et.romanenko( + Testr.tmean, + rh=Testr.rh, + tmax=Testr.tmax, + tmin=Testr.tmin, + rhmax=Testr.rhmax, + rhmin=Testr.rhmin, + ) + ) + .round(1) + .tolist() + ) + r_romanenko = [9.3, 8.9, 9.4, 8.2, 10.6, 16.8, 14.0, 14.7, 17.4, 9.2] + self.assertEqual(r_romanenko, pyet_romanenko, 1) + + expected_rm = tile(asarray(r_romanenko)[:, newaxis, newaxis], (1, 3, 3)) + expected_rm = DataArray( + expected_rm, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calculated_rm = et.romanenko( + Testr.tmean_xr, + rh=Testr.rh_xr, + tmax=Testr.tmax_xr, + tmin=Testr.tmin_xr, + rhmax=Testr.rhmax_xr, + rhmin=Testr.rhmin_xr, + ) + testing.assert_allclose(calculated_rm.round(1), expected_rm.round(1)) + + def test_mcguinnessbordne(self): + pyet_mgb = ( + (et.mcguinness_bordne(Testr.tmean, lat=Testr.lat) * Testr.lambda_corr) + .round(1) + .tolist() + ) + r_mgb = [5.8, 5.5, 5.9, 5.6, 6.4, 7.6, 6.7, 6.8, 7.0, 5.6] + self.assertEqual(r_mgb, pyet_mgb, 1) + + expected_mb = tile(asarray(r_mgb)[:, newaxis, newaxis], (1, 3, 3)) + expected_mb = DataArray( + expected_mb, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calc_mb = ( + et.mcguinness_bordne(Testr.tmean_xr, lat=Testr.lat) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calc_mb.round(1), expected_mb.round(1)) + calc_mb1 = ( + et.mcguinness_bordne(Testr.tmean_xr, lat=Testr.lat_xr) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calc_mb1.round(1), expected_mb.round(1)) + + def test_jensen_haise(self): + pyet_jh = ( + (et.jensen_haise(Testr.tmean, Testr.rs) * Testr.lambda_corr) + .round(1) + .tolist() + ) + r_jh = [5.2, 4.9, 5.3, 5.0, 5.8, 7.0, 6.1, 6.3, 6.4, 5.0] + self.assertEqual(r_jh, pyet_jh, 1) + + expected_jh = tile(asarray(r_jh)[:, newaxis, newaxis], (1, 3, 3)) + expected_jh = DataArray( + expected_jh, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calc_jh = ( + et.jensen_haise(Testr.tmean_xr, Testr.rs_xr) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calc_jh.round(1), expected_jh.round(1)) + + def test_linacre(self): + tdew = [ + 10.2375, + 8.8375, + 11.5125, + 10.2875, + 11.9875, + 9.475, + 7.7625, + 7.2375, + 3.0125, + 11.325, + ] + pyet_linacre = ( + (et.linacre(Testr.tmean, Testr.elevation, Testr.lat, tdew=tdew)) + .round(1) + .tolist() + ) + r_linacre = [4.4, 4.3, 4.4, 4.2, 5.4, 9.1, 7.5, 8.0, 9.9, 4.3] + self.assertEqual(r_linacre, pyet_linacre, 1) + + expected_l = tile(asarray(r_linacre)[:, newaxis, newaxis], (1, 3, 3)) + expected_l = DataArray( + expected_l, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + tdew_xr = tile(asarray(tdew)[:, newaxis, newaxis], (1, 3, 3)) + tdew_xr = DataArray( + tdew_xr, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calc_l = et.linacre(Testr.tmean_xr, Testr.elevation, Testr.lat, tdew=tdew_xr) + testing.assert_allclose(calc_l.round(1), expected_l.round(1)) + calc_l1 = et.linacre( + Testr.tmean_xr, Testr.elevation_xr, Testr.lat_xr, tdew=tdew_xr + ) + testing.assert_allclose(calc_l1.round(1), expected_l.round(1)) + + def test_abtew(self): + pyet_abtew = ( + (et.abtew(Testr.tmean, Testr.rs, k=0.52) * Testr.lambda_corr) + .round(1) + .tolist() + ) + r_abtew = [4.3, 4.3, 4.3, 4.3, 4.3, 4.2, 4.2, 4.2, 4.2, 4.1] + self.assertEqual(r_abtew, pyet_abtew, 1) + + expected_a = tile(asarray(r_abtew)[:, newaxis, newaxis], (1, 3, 3)) + expected_a = DataArray( + expected_a, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calc_a = ( + et.abtew(Testr.tmean_xr, Testr.rs_xr, k=0.52) + * Testr.lambda_corr.values[:, None, None] + ) + testing.assert_allclose(calc_a.round(1), expected_a.round(1)) + + def test_turc(self): + pyet_turc = (et.turc(Testr.tmean, Testr.rs, Testr.rh)).round(1).tolist() + # There is a mistake in the R-Package + # The R-Package does not consider RH < 50 + # if pyet.turc also does nonsider this, the result is the same + r_turc = [4.2, 4.0, 4.2, 4.0, 4.3, 6.1, 5.4, 5.6, 6.2, 4.1] + self.assertEqual(r_turc, pyet_turc, 1) + + expected_t = tile(asarray(r_turc)[:, newaxis, newaxis], (1, 3, 3)) + expected_t = DataArray( + expected_t, + coords={"time": Testr.tmean.index, "y": range(3), "x": range(3)}, + dims=["time", "y", "x"], + ) + calc_turc = et.turc(Testr.tmean_xr, Testr.rs_xr, Testr.rh_xr) + testing.assert_allclose(calc_turc.round(1), expected_t.round(1)) diff --git a/tests/test_temperature.py b/tests/test_temperature.py deleted file mode 100644 index 00d2413..0000000 --- a/tests/test_temperature.py +++ /dev/null @@ -1,34 +0,0 @@ -"""This file tests for the temperature methods for a minimal functioning.""" - -import numpy as np -import pandas as pd - -import pyet as et - -tmean = pd.Series(data=20 * np.sin(np.linspace(0, 1, 365) * 2 * np.pi), - index=pd.date_range("2001-01-01", "2001-12-31", freq="D")) - - -def test_blaney_criddle(): - et.blaney_criddle(tmean, lat=0.9) - return True - - -def test_haude(): - et.haude(tmean, rh=0.5) - return True - - -def test_hamon(): - et.hamon(tmean, lat=0.9) - return True - - -def test_romanenko(): - et.romanenko(tmean, rh=0.5) - return True - - -def test_linacre(): - et.linacre(tmean, 0, lat=0.9) - return True diff --git a/tests/testalternative.py b/tests/testalternative.py index 6159aac..21aa03d 100644 --- a/tests/testalternative.py +++ b/tests/testalternative.py @@ -1,7 +1,8 @@ import unittest -import numpy as np -import pandas as pd +from numpy import full, pi +from pandas import Series, DatetimeIndex, date_range +from xarray import testing, DataArray import pyet as et @@ -9,82 +10,428 @@ class Testalternative(unittest.TestCase): def test_hargreaves(self): # Based on example S19.46,p 78 TestFAO56 - tmax = pd.Series([26.6], index=pd.DatetimeIndex(["2015-07-15"])) - tmin = pd.Series([14.8], index=pd.DatetimeIndex(["2015-07-15"])) + tmax = Series([26.6], index=DatetimeIndex(["2015-07-15"])) + tmin = Series([14.8], index=DatetimeIndex(["2015-07-15"])) tmean = (tmax + tmin) / 2 - lat = 45.72 * np.pi / 180 + lat = 45.72 * pi / 180 har = et.hargreaves(tmean, tmax, tmin, lat) - self.assertAlmostEqual(float(har), 5.0, 1) + self.assertAlmostEqual(float(har.iloc[0]), 5.0, 1) + + tmax_xr = DataArray( + full((2, 3, 3), 26.6), + coords=[ + ("time", date_range(start="2015-07-15", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + tmin_xr = DataArray( + full((2, 3, 3), 14.8), + coords=[ + ("time", date_range(start="2015-07-15", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + tmean_xr = (tmax_xr + tmin_xr) / 2 + calculated_har = et.hargreaves(tmean_xr, tmax_xr, tmin_xr, lat) + expected_har = DataArray( + full((2, 3, 3), 5.0), + coords=[ + ("time", date_range(start="2015-07-15", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_har.round(1), expected_har.round(1)) + lat_xr = DataArray( + full((3, 3), lat), + coords=[("y", [1, 2, 3]), ("x", [1, 2, 3])], + ) + calculated_har1 = et.hargreaves(tmean_xr, tmax_xr, tmin_xr, lat_xr) + testing.assert_allclose(calculated_har1.round(1), expected_har.round(1)) def test_makkink(self): # Based on example S19.91, p 80 McMahon_etal_2013 - tmean = pd.Series([11.5], index=pd.DatetimeIndex(["1980-07-20"])) - rs = pd.Series([17.194], index=pd.DatetimeIndex(["1980-07-20"])) + tmean = Series([11.5], index=DatetimeIndex(["1980-07-20"])) + rs = Series([17.194], index=DatetimeIndex(["1980-07-20"])) elevation = 546 lambda0 = 2.45 # Lambda in McMahon lambda1 = et.calc_lambda(tmean) # Lambda in pyet lambda_corr = lambda1 / lambda0 n = -0.12 # correction for different formula in McMahon_2013 - mak = (et.makkink(tmean, rs, elevation=elevation, - k=0.61) * lambda_corr) + n + mak = (et.makkink(tmean, rs, elevation=elevation, k=0.61) * lambda_corr) + n self.assertAlmostEqual(float(mak), 2.3928, 2) + tmean_xr = DataArray( + full((2, 3, 3), 11.5), + coords=[ + ("time", date_range(start="2015-07-15", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + rs_xr = DataArray( + full((2, 3, 3), 17.194), + coords=[ + ("time", date_range(start="2015-07-15", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_mak = ( + et.makkink(tmean_xr, rs_xr, elevation=elevation, k=0.61) + * lambda_corr.values + ) + n + + expected_mak = DataArray( + full((2, 3, 3), 2.3928), + coords=[ + ("time", date_range(start="2015-07-15", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_mak.round(2), expected_mak.round(2)) + elevation_xr = DataArray( + full((3, 3), elevation), + coords=[("y", [1, 2, 3]), ("x", [1, 2, 3])], + ) + calculated_mak1 = ( + et.makkink(tmean_xr, rs_xr, elevation=elevation_xr, k=0.61) + * lambda_corr.values + ) + n + testing.assert_allclose(calculated_mak1.round(2), expected_mak.round(2)) + + def test_makkink_knmi(self): + # Based on knmi station 260 (de Bilt) + tmean = Series([0.9], index=DatetimeIndex(["1980-01-01"])) + rs = Series([2.53], index=DatetimeIndex(["1980-01-01"])) + mak = et.makkink_knmi(tmean, rs).round(1) + self.assertAlmostEqual(float(mak.iloc[0]), 0.3, 2) + + tmean_xr = DataArray( + full((2, 3, 3), 0.9), + coords=[ + ("time", date_range(start="1980-01-01", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + rs_xr = DataArray( + full((2, 3, 3), 2.53), + coords=[ + ("time", date_range(start="1980-01-01", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_mak1 = et.makkink_knmi(tmean_xr, rs_xr) + + expected_mak1 = DataArray( + full((2, 3, 3), 0.3), + coords=[ + ("time", date_range(start="1980-01-01", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_mak1.round(1), expected_mak1.round(1)) + def test_blaney_criddle(self): # Based on example S19.93, McMahon_etal_2013 - tmean = pd.Series([11.5], index=pd.DatetimeIndex(["1980-07-20"])) - rhmin = pd.Series([25], index=pd.DatetimeIndex(["1980-07-20"])) - wind = pd.Series([0.5903], index=pd.DatetimeIndex(["1980-07-20"])) - n = pd.Series([10.7], index=pd.DatetimeIndex(["1980-07-20"])) - py = pd.Series([0.2436], index=pd.DatetimeIndex(["1980-07-20"])) - lat = -23.7951 * np.pi / 180 - bc = et.blaney_criddle(tmean, lat, wind=wind, n=n, rhmin=rhmin, - py=py, method=2) - self.assertAlmostEqual(float(bc), 3.1426, 2) + tmean = Series([11.5], index=DatetimeIndex(["1980-07-20"])) + rhmin = Series([25], index=DatetimeIndex(["1980-07-20"])) + wind = Series([0.5903], index=DatetimeIndex(["1980-07-20"])) + n = Series([10.7], index=DatetimeIndex(["1980-07-20"])) + py = Series([0.2436], index=DatetimeIndex(["1980-07-20"])) + lat = -23.7951 * pi / 180 + bc = et.blaney_criddle(tmean, lat, wind=wind, n=n, rhmin=rhmin, py=py, method=2) + self.assertAlmostEqual(float(bc.iloc[0]), 3.1426, 2) + + tmean_xr = DataArray( + full((2, 3, 3), 11.5), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + rhmin_xr = DataArray( + full((2, 3, 3), 25), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + wind_xr = DataArray( + full((2, 3, 3), 0.5903), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + n_xr = DataArray( + full((2, 3, 3), 10.7), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + py_xr = DataArray( + full((2, 3, 3), 0.2436), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_bc = et.blaney_criddle( + tmean_xr, lat, wind=wind_xr, n=n_xr, rhmin=rhmin_xr, py=py_xr, method=2 + ) + expected_bc = DataArray( + full((2, 3, 3), 3.1426), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_bc.round(2), expected_bc.round(2)) + lat_xr = DataArray( + full((3, 3), lat), + coords=[("y", [1, 2, 3]), ("x", [1, 2, 3])], + ) + calculated_bc1 = et.blaney_criddle( + tmean_xr, lat_xr, wind=wind_xr, n=n_xr, rhmin=rhmin_xr, py=py_xr, method=2 + ) + testing.assert_allclose(calculated_bc1.round(2), expected_bc.round(2)) def test_turc(self): # Based on example S19.99, McMahon_etal_2013 - tmean = pd.Series([11.5], index=pd.DatetimeIndex(["1980-07-20"])) - rhmean = pd.Series([48], index=pd.DatetimeIndex(["1980-07-20"])) - rs = pd.Series([17.194], index=pd.DatetimeIndex(["1980-07-20"])) - turc = et.turc(tmean, rs, rhmean, k=0.32) - self.assertAlmostEqual(float(turc), 2.6727, 1) + tmean = Series([11.5], index=DatetimeIndex(["1980-07-20"])) + rhmean = Series([48], index=DatetimeIndex(["1980-07-20"])) + rs = Series([17.194], index=DatetimeIndex(["1980-07-20"])) + turc = et.turc(tmean, rs, rhmean) + self.assertAlmostEqual(float(turc.iloc[0]), 2.6727, 1) + + tmean_xr = DataArray( + full((2, 3, 3), 11.5), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + rh_xr = DataArray( + full((2, 3, 3), 48), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + rs_xr = DataArray( + full((2, 3, 3), 17.194), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_turc1 = et.turc(tmean_xr, rs_xr, rh_xr) + + expected_turc1 = DataArray( + full((2, 3, 3), 2.6727), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_turc1.round(1), expected_turc1.round(1)) def test_hargreaves_samani(self): # Based on example S19.101, McMahon_etal_2013 - tmean = pd.Series([11.5], index=pd.DatetimeIndex(["1980-07-20"])) - tmax = pd.Series([21], index=pd.DatetimeIndex(["1980-07-20"])) - tmin = pd.Series([2], index=pd.DatetimeIndex(["1980-07-20"])) + tmean = Series([11.5], index=DatetimeIndex(["1980-07-20"])) + tmax = Series([21], index=DatetimeIndex(["1980-07-20"])) + tmin = Series([2], index=DatetimeIndex(["1980-07-20"])) lambda0 = 2.45 # Lambda in McMahon lambda1 = et.calc_lambda(tmean) # Lambda in pyet lambda_corr = lambda1 / lambda0 - lat = -23.7951 * np.pi / 180 + lat = -23.7951 * pi / 180 har = et.hargreaves(tmean, tmax, tmin, lat, method=1) - self.assertAlmostEqual(float(har * lambda_corr), 4.1129, 2) + self.assertAlmostEqual(float(har.iloc[0] * lambda_corr), 4.1129, 2) + + tmean_xr = DataArray( + full((2, 3, 3), 11.5), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + tmax_xr = DataArray( + full((2, 3, 3), 21), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + tmin_xr = DataArray( + full((2, 3, 3), 2), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_har = ( + et.hargreaves(tmean_xr, tmax_xr, tmin_xr, lat, method=1) + * lambda_corr.values + ) + expected_har1 = DataArray( + full((2, 3, 3), 4.1129), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + expected_har1.loc[{"time": "1980-07-21"}] = 4.13 + testing.assert_allclose(calculated_har.round(2), expected_har1.round(2)) + lat_xr = DataArray( + full((3, 3), lat), + coords=[("y", [1, 2, 3]), ("x", [1, 2, 3])], + ) + calculated_har1 = ( + et.hargreaves(tmean_xr, tmax_xr, tmin_xr, lat_xr, method=1) + * lambda_corr.values + ) + testing.assert_allclose(calculated_har1.round(2), expected_har1.round(2)) def test_priestley_taylor(self): # Based on example S19.109, McMahon_etal_2013 - tmean = pd.Series([11.5], index=pd.DatetimeIndex(["1980-07-20"])) - rn = pd.Series([8.6401], index=pd.DatetimeIndex(["1980-07-20"])) + tmean = Series([11.5], index=DatetimeIndex(["1980-07-20"])) + rn = Series([8.6401], index=DatetimeIndex(["1980-07-20"])) elevation = 546 lambda0 = 2.45 # Lambda in McMahon lambda1 = et.calc_lambda(tmean) # Lambda in pyet lambda_corr = lambda1 / lambda0 pt = et.priestley_taylor(tmean, rn=rn, elevation=elevation, alpha=1.26) - self.assertAlmostEqual(float(pt * lambda_corr), 2.6083, 2) + self.assertAlmostEqual(float(pt.iloc[0] * lambda_corr), 2.6083, 2) + + tmean_xr = DataArray( + full((2, 3, 3), 11.5), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + rn_xr = DataArray( + full((2, 3, 3), 8.6401), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_pt = ( + et.priestley_taylor(tmean_xr, rn=rn_xr, elevation=elevation, alpha=1.26) + * lambda_corr.values + ) + + expected_pt1 = DataArray( + full((2, 3, 3), 2.6083), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_pt.round(2), expected_pt1.round(2)) + elevation_xr = DataArray( + full((3, 3), elevation), + coords=[("y", [1, 2, 3]), ("x", [1, 2, 3])], + ) + calculated_pt1 = ( + et.priestley_taylor(tmean_xr, rn=rn_xr, elevation=elevation_xr, alpha=1.26) + * lambda_corr.values + ) + testing.assert_allclose(calculated_pt1.round(2), expected_pt1.round(2)) def test_blaney_criddle1(self): # Based on example 5.1, P89 Schrodter 1985 - tmean = pd.Series([17.3], index=pd.DatetimeIndex(["1980-07-20"])) - lat = 50 * np.pi / 180 + tmean = Series([17.3], index=DatetimeIndex(["1980-07-20"])) + lat = 50 * pi / 180 bc = et.blaney_criddle(tmean, lat, method=0) - self.assertAlmostEqual(float(bc), 3.9, 1) + self.assertAlmostEqual(float(bc.iloc[0]), 3.9, 1) + + tmean_xr = DataArray( + full((2, 3, 3), 17.3), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_bc1 = et.blaney_criddle(tmean_xr, lat, method=0) + + expected_bc1 = DataArray( + full((2, 3, 3), 3.9), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_bc1.round(1), expected_bc1.round(1)) + lat_xr = DataArray( + full((3, 3), lat), + coords=[("y", [1, 2, 3]), ("x", [1, 2, 3])], + ) + calculated_bc2 = et.blaney_criddle(tmean_xr, lat_xr, method=0) + testing.assert_allclose(calculated_bc2.round(1), expected_bc1.round(1)) def test_haude(self): # Based on example 5.2, P95 Schrodter 1985 - tmean = pd.Series([21.5], index=pd.DatetimeIndex(["1980-07-20"])) - ea = pd.Series([1.19], index=pd.DatetimeIndex(["1980-07-20"])) + tmean = Series([21.5], index=DatetimeIndex(["1980-07-20"])) + ea = Series([1.19], index=DatetimeIndex(["1980-07-20"])) k = 0.26 / 0.35 # 0.35 value is taken in pyet e0 = et.calc_e0(tmean) rh = ea / e0 * 100 haude = et.haude(tmean, rh=rh, k=k) - self.assertAlmostEqual(float(haude), 3.6, 1) + self.assertAlmostEqual(float(haude.iloc[0]), 3.6, 1) + + tmean_xr = DataArray( + full((2, 3, 3), 21.5), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + rh_xr = DataArray( + full((2, 3, 3), rh.iloc[0]), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + calculated_haude1 = et.haude(tmean_xr, rh=rh_xr, k=k) + + expected_haude1 = DataArray( + full((2, 3, 3), 3.6), + coords=[ + ("time", date_range(start="1980-07-20", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + testing.assert_allclose(calculated_haude1.round(1), expected_haude1.round(1)) diff --git a/tests/testfao56.py b/tests/testfao56.py index 977f50a..f2234f7 100644 --- a/tests/testfao56.py +++ b/tests/testfao56.py @@ -1,60 +1,185 @@ import unittest -import numpy as np -import pandas as pd - +from numpy import pi, array, full, testing +from pandas import date_range, DatetimeIndex, Series +from xarray import DataArray, Dataset import pyet as et class TestFAO56(unittest.TestCase): def test_press_calc(self): # Based on Example 2 and 4, p. 32 FAO. - p1 = et.calc_press(1800) - p2 = et.calc_press(1200) - self.assertAlmostEqual(p1, 81.8, 1) - self.assertAlmostEqual(p2, 87.9, 1) - # Basen on Table C-2 in ASCE(2001). - p3 = et.calc_press(1462.4) - self.assertAlmostEqual(p3, 85.17, 1) + elevation_s = Series( + data=[1800, 1200, 1462.4], index=date_range(start="2020-1-1", periods=3) + ) + calculated_pressures0 = et.calc_press(elevation_s) + expected_pressures = Series( + data=[81.8, 87.9, 85.17], index=date_range(start="2020-1-1", periods=3) + ) + testing.assert_allclose( + expected_pressures.round(1), calculated_pressures0.round(1) + ) + + # Create a 3D DataArray with dimensions 'x', 'y', and 'time' + elevation_xr = DataArray( + full((2, 3, 3), 1800), + coords=[ + ("time", date_range(start="1/1/2020", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + elevation_xr.loc[{"time": "2020-01-02"}] = 1200 + # Apply the et.calc_press function to each element of the DataArray + calculated_pressures = et.calc_press(elevation_xr) + # Create expected results as DataArrays + expected_pressures = DataArray( + full((2, 3, 3), 81.8), + coords=[ + ("time", date_range(start="1/1/2020", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + expected_pressures.loc[{"time": "2020-01-02"}] = 87.9 + # Check that the results are as expected + testing.assert_allclose(calculated_pressures.round(1), expected_pressures) def test_vpc(self): # Based on ASCE Table C-3 - tmean = np.array([21.65, 22.9, 23.7, 22.8, 24.3, - 26.0, 26.1, 26.4, 23.9, 24.2]) - vpc1 = et.calc_vpc(tmean).round(3).tolist() - vpcr = np.array([0.1585, 0.1692, 0.1762, 0.1684, 0.1820, - 0.199, 0.1996, 0.2027, 0.1781, 0.1809]).round( - 3).tolist() - self.assertAlmostEqual(vpc1, vpcr, 1) + tmean = [21.65, 22.9, 23.7, 22.8, 24.3, 26.0, 26.1, 26.4, 23.9, 24.2] + tmean_s = Series(tmean, index=date_range(start="2020-1-1", periods=10)) + calculated_vpc1 = et.calc_vpc(tmean_s) + vpc1 = [ + 0.1585, + 0.1692, + 0.1762, + 0.1684, + 0.1820, + 0.199, + 0.1996, + 0.2027, + 0.1781, + 0.1809, + ] + expected_vpc1 = Series(vpc1, index=date_range(start="2020-1-1", periods=10)) + testing.assert_allclose(expected_vpc1.round(2), calculated_vpc1.round(2)) + + # Create a 3D DataArray with dimensions 'x', 'y', and 'time' + tmean_xr = DataArray( + full((4, 3, 3), 21.65), + coords=[ + ("time", date_range(start="2020-1-1", periods=4)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + tmean_xr.loc[{"time": ["2020-01-02", "2020-01-03", "2020-01-04"]}] = [ + 22.9, + 23.7, + 22.8, + ] + # Apply the et.calc_press function to each element of the DataArray + calculated_vpc = et.calc_vpc(tmean_xr) + # Create expected results as DataArrays + expected_vpc = DataArray( + full((4, 3, 3), 0.158), + coords=[ + ("time", date_range(start="2020-1-1", periods=4)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + expected_vpc.loc[{"time": ["2020-01-02", "2020-01-03", "2020-01-04"]}] = [ + 0.1692, + 0.1762, + 0.1684, + ] + # Check that the results are as expected + testing.assert_allclose(calculated_vpc.round(3), expected_vpc.round(3)) def test_psy_calc(self): - # Based on Example 2, p. 32 FAO. - psy = et.calc_psy(81.8) - self.assertAlmostEqual(psy, 0.054, 3) - # Basen on Table C-2 in ASCE(2001). - psy1 = et.calc_psy(85.17) - self.assertAlmostEqual(psy1, 0.0566, 3) + # Based on Example 2, p. 32 FAO. and Table C-2 in ASCE(2001) + p0 = Series([81.8, 85.17], index=date_range(start="2020-1-1", periods=2)) + calculated_psy = et.calc_psy(p0) + expected_psy = Series( + [0.054, 0.0566], index=date_range(start="2020-1-1", periods=2) + ) + testing.assert_allclose(expected_psy.round(3), calculated_psy.round(3)) + # Create a 3D DataArray with dimensions 'x', 'y', and 'time' + press_xr = DataArray( + full((2, 3, 3), 81.8), + coords=[ + ("time", date_range(start="2020-1-1", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + press_xr.loc[{"time": "2020-01-02"}] = 85.17 + # Apply the et.calc_press function to each element of the DataArray + calculated_psy = et.calc_psy(press_xr) + # Create expected results as DataArrays + expected_psy = DataArray( + full((2, 3, 3), 0.054), + coords=[ + ("time", date_range(start="2020-1-1", periods=2)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + expected_psy.loc[{"time": "2020-01-02"}] = 0.0566 + # Check that the results are as expected + testing.assert_allclose(calculated_psy.round(3), expected_psy.round(3)) def test_e0_calc(self): # Based on Example 3 and 4, p. 36 FAO. - e0_1 = et.calc_e0(24.5) - e0_2 = et.calc_e0(15.) - e0_3 = et.calc_e0(19.75) - e0_4 = et.calc_e0(19.5) - self.assertAlmostEqual(e0_1, 3.075, 2) - self.assertAlmostEqual(e0_2, 1.705, 2) - self.assertAlmostEqual(e0_3, 2.3, 2) - self.assertAlmostEqual(e0_4, 2.267, 2) + tmean0 = Series( + [24.5, 15, 19.75, 19.5], index=date_range(start="2020-1-1", periods=4) + ) + calculated_e0 = et.calc_e0(tmean0) + expected_e0 = Series( + [3.075, 1.705, 2.3, 2.267], index=date_range(start="2020-1-1", periods=4) + ) + testing.assert_allclose(expected_e0.round(1), calculated_e0.round(1)) + + # Create a 3D DataArray with dimensions 'x', 'y', and 'time' + tmean_xr = DataArray( + full((4, 3, 3), 24.5), + coords=[ + ("time", date_range(start="2020-1-1", periods=4)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + tmean_xr.loc[{"time": "2020-01-02"}] = 15 + tmean_xr.loc[{"time": "2020-01-03"}] = 19.75 + tmean_xr.loc[{"time": "2020-01-04"}] = 19.5 + # Apply the et.calc_press function to each element of the DataArray + calculated_e0 = et.calc_e0(tmean_xr) + # Create expected results as DataArrays + expected_e0 = DataArray( + full((4, 3, 3), 3.075), + coords=[ + ("time", date_range(start="2020-1-1", periods=4)), + ("y", [1, 2, 3]), + ("x", [1, 2, 3]), + ], + ) + expected_e0.loc[{"time": "2020-01-02"}] = 1.705 + expected_e0.loc[{"time": "2020-01-03"}] = 2.3 + expected_e0.loc[{"time": "2020-01-04"}] = 2.267 + # Check that the results are as expected + testing.assert_allclose(calculated_e0.round(1), expected_e0.round(1)) def test_es_calc(self): # Based on Example 3 and 6, p. 36 FAO. - es = et.calc_es(tmax=24.5, tmin=15.) + es = et.calc_es(tmax=24.5, tmin=15.0) self.assertAlmostEqual(es, 2.39, 3) def test_ea_calc(self): # Based on Example 5, p. 39 FAO. - ea1 = et.calc_ea(tmax=25., tmin=18., rhmax=82., rhmin=54.) + ea1 = et.calc_ea(tmax=25.0, tmin=18.0, rhmax=82.0, rhmin=54.0) rhmean = (82 + 54) / 2 - ea2 = et.calc_ea(tmax=25., tmin=18., rh=rhmean) + ea2 = et.calc_ea(tmax=25.0, tmin=18.0, rh=rhmean) self.assertAlmostEqual(ea1, 1.70, 2) self.assertAlmostEqual(ea2, 1.78, 2) @@ -75,46 +200,100 @@ def test_sunset_angle(self): def test_day_of_year(self): # Based on Example 8, p. 47 FAO. - doy = et.day_of_year(pd.DatetimeIndex(["2015-09-03"])) - self.assertAlmostEqual(doy.values, 246, 1) + doy = et.day_of_year(DatetimeIndex(["2015-09-03"])) + self.assertAlmostEqual(float(doy.iloc[0]), 246, 1) # Based on ASCD Table C-3 - dindex = pd.date_range("2020-07-01", "2020-07-10") + dindex = date_range("2020-07-01", "2020-07-10") doy1 = et.day_of_year(dindex).tolist() - doyr = [183, 184, 185, 186, 187, - 188, 189, 190, 191, 192] + doyr = [183, 184, 185, 186, 187, 188, 189, 190, 191, 192] self.assertEqual(doy1, doyr, 1) def test_extraterrestrial_r(self): # Based on Example 8, p. 47 FAO. - extrar = et.extraterrestrial_r(pd.DatetimeIndex(["2015-09-03"]), -0.35) + extrar = et.extraterrestrial_r(DatetimeIndex(["2015-09-03"]), -0.35) self.assertAlmostEqual(float(extrar), 32.2, 1) def test_daylight_hours(self): # Based on Example 9, p. 47 FAO. - dayhours = et.daylight_hours(pd.DatetimeIndex(["2015-09-03"]), -0.35) + dayhours = et.daylight_hours(DatetimeIndex(["2015-09-03"]), -0.35) self.assertAlmostEqual(float(dayhours), 11.7, 1) - # Check - # def test_calc_rad_long(self): - # # Based on Example 10, p. 52 FAO. - # rs = pd.Series([14.5], index=pd.DatetimeIndex(["2015-05-15"])) - # rnl = et.calc_rad_long(rs, tmax=25.1, tmin=19, ea=2.1, rso=18.8) - # self.assertAlmostEqual(float(rnl), 3.6, 1) + def test_calc_rad_long(self): + # Based on Example 10, p. 52 FAO. + rs = Series([14.5], index=DatetimeIndex(["2015-05-15"])) + tmax = Series([25.1], index=DatetimeIndex(["2015-05-15"])) + tmin = Series([19], index=DatetimeIndex(["2015-05-15"])) + ea = Series([2.1], index=DatetimeIndex(["2015-05-15"])) + rso = Series([18.8], index=DatetimeIndex(["2015-05-15"])) + rnl = et.calc_rad_long(rs, tmax=tmax, tmin=tmin, ea=ea, rso=rso) + self.assertAlmostEqual(float(rnl), 3.5, 1) + + def test_calc_rad_sol_in(self): + # Based on example 10, p 50 TestFAO56 + lat = -22.9 * pi / 180 + n = Series(7.1, DatetimeIndex(["2021-5-15"])) + rad_sol_in = et.calc_rad_sol_in(n, lat) + self.assertAlmostEqual(float(rad_sol_in.iloc[0]), 14.5, 1) def test_et_fao56(self): # Based on Example 18, p. 72 FAO. - wind = pd.Series([2.078], index=pd.DatetimeIndex(["2015-07-06"])) - tmax = pd.Series([21.5], index=pd.DatetimeIndex(["2015-07-06"])) - tmin = pd.Series([12.3], index=pd.DatetimeIndex(["2015-07-06"])) + wind = Series([2.078], index=DatetimeIndex(["2015-07-06"])) + tmax = Series([21.5], index=DatetimeIndex(["2015-07-06"])) + tmin = Series([12.3], index=DatetimeIndex(["2015-07-06"])) tmean = (tmax + tmin) / 2 - rhmax = pd.Series([84], index=pd.DatetimeIndex(["2015-07-06"])) - rhmin = pd.Series([63], index=pd.DatetimeIndex(["2015-07-06"])) - rs = pd.Series([22.07], index=pd.DatetimeIndex(["2015-07-06"])) + rhmax = Series([84], index=DatetimeIndex(["2015-07-06"])) + rhmin = Series([63], index=DatetimeIndex(["2015-07-06"])) + rs = Series([22.07], index=DatetimeIndex(["2015-07-06"])) n = 9.25 nn = 16.1 elevation = 100 - lat = 50.80 * np.pi / 180 - et56 = et.pm_fao56(tmean, wind, elevation=elevation, lat=lat, rs=rs, - tmax=tmax, tmin=tmin, rhmax=rhmax, - rhmin=rhmin, n=n, nn=nn) - self.assertAlmostEqual(float(et56), 3.9, 1) + lat = 50.80 * pi / 180 + et56 = et.pm_fao56( + tmean, + wind, + elevation=elevation, + lat=lat, + rs=rs, + tmax=tmax, + tmin=tmin, + rhmax=rhmax, + rhmin=rhmin, + n=n, + nn=nn, + ) + self.assertAlmostEqual(float(et56.iloc[0]), 3.9, 1) + # Create an xarray Dataset with DataArrays + # Create an xarray Dataset with DataArrays + data = { + "wind": DataArray(wind, dims=("time",)), + "tmax": DataArray(tmax, dims=("time",)), + "tmin": DataArray(tmin, dims=("time",)), + "tmean": DataArray(tmean, dims=("time",)), + "rhmax": DataArray(rhmax, dims=("time",)), + "rhmin": DataArray(rhmin, dims=("time",)), + "rs": DataArray(rs, dims=("time",)), + "et0": DataArray([3.9], dims=("time",)), + } + + # Create the xarray Dataset + dataset = Dataset(data) + # Add additional variables (n, nn, elevation, lat) + dataset["n"] = n + dataset["nn"] = nn + dataset["elevation"] = elevation + dataset["lat"] = lat + et56_xr = et.pm_fao56( + dataset["tmean"], + dataset["wind"], + elevation=dataset["elevation"], + lat=dataset["lat"], + rs=dataset["rs"], + tmax=dataset["tmax"], + tmin=dataset["tmin"], + rhmax=dataset["rhmax"], + rhmin=dataset["rhmin"], + n=dataset["n"], + nn=dataset["nn"], + ) + + testing.assert_allclose(et56_xr.round(1), dataset["et0"]) diff --git a/tests/testmeteo.py b/tests/testmeteo.py deleted file mode 100644 index 4583f18..0000000 --- a/tests/testmeteo.py +++ /dev/null @@ -1,15 +0,0 @@ -import unittest - -import numpy as np -import pandas as pd - -import pyet as et - - -class Testmeteo(unittest.TestCase): - def test_calc_rad_sol_in(self): - # Based on example 10, p 50 TestFAO56 - lat = -22.9 * np.pi / 180 - n = pd.Series(7.1, pd.DatetimeIndex(["2021-5-15"])) - rad_sol_in = et.calc_rad_sol_in(n, lat) - self.assertAlmostEqual(float(rad_sol_in.values), 14.5, 1)