Watershed Workflow Workshop

This workshop was developed for the IDEAS-Watersheds Phase 2 All Hands.

Facilitators: Saubhagya Rathore and Ethan Coon
Date: November 15, 2024
Location: Denver, CO

1. Learning Objectives

At the end of the workshop, participants will be able to:

• Describe the fundamental principles and components of Watershed Workflow (WW).
• Use different simplify and redensify methods and manipulate reaches to identify and resolve data inconsistencies and errors.
• Leverage various refinement methods and constraints during triangulation to generate a high-quality mesh.
• Define labeled sets in the river mesh at different levels of granularity.
• Condition the river mesh using different methods.

2. Prerequisites

To maximize the learning experience from the workshop, participants are encouraged to have:

• Essential Python skills and experience with Jupyter Notebook
• Familiarity with the shapely package, particularly for debugging
• Basic knowledge of watershed hydrology modeling

3. Materials and Resources

3.1. Readings

• WW release paper: Coon, E.T., Shuai, P., 2022. Watershed Workflow: A toolset for parameterizing data-intensive, integrated hydrologic models. Environmental Modeling & Software: 105502. https://doi.org/10.1016/j.envsoft.2022.105502
• Stream-Aligned Meshing paper: Rathore, S. S., Coon, E. T., & Painter, S. L. (2024). A stream-aligned mixed polyhedral meshing strategy for integrated surface-subsurface hydrological models. Computers & Geosciences, 188, 105617. https://doi.org/10.1016/j.cageo.2024.105617
• Watershed Workflow Documentation: https://environmental-modeling-workflows.github.io/watershed-workflow/build/html/index.html
• shapely User Manual: https://shapely.readthedocs.io/en/stable/manual.html

3.2. Course files and containers

To save time during the workshop, participants are expected to have the following material downloaded and set up on their computers:

• git clone https://github.com/environmental-modeling-workflows/workshop-watershed-workflow-2024
• cd workshop-watershed-workflow-2024

Next, run the container to get a working Watershed Workflow master installation (or use your own):

• . ./run_jupyter.sh

  OR

  docker run --platform=linux/amd64 -it -v $(pwd):/home/jovyan/workdir:delegated -w /home/jovyan/workdir -p 8888:8888 ecoon/watershed_workflow:master

• Open the link displayed in your browser

Some common gotchas here include:

• For OSX, make sure you clone the repository in your home directory somewhere -- otherwise docker does not have OSX's permission to see it.
• Be sure to close any local jupyter lab engines; these will conflict with the jupyer lab engine running in the container and your browser will get confused.

4. Workshop Outline

• Introduction: (20 minutes)

  • Outline of the workshop
  • Watershed_Workflow_Introduction

• Module 1: Exploring Key Conceptual Objects: (20 minutes)

  • Dive into WW components like RiverTree and SplitHucs critical to mixed-polyhedral meshing, understanding their roles in meshing.
  • Understand basics of manipulating WW objects.

• Module 2: Simplify and Redensify (30 minutes)

  • Explore different simplify and redensify methods including variable quad lengths.
  • Manipulate reaches to identify and resolve data inconsistencies and errors like dual intersection problem

• Module 3: Mesh Generation (30 minutes)

  • Leverage various refinement methods and constraints during triangulation to generate a high-quality mesh.
  • Provide river widths using multiple methods.
  • Troubleshoot mesh generation.

• Module 4: Labeled Sets (10 minutes)

  • Define labeled sets in the river mesh at different levels of granularity (e.g., stream network, stream order, individual reaches).

• Module 5: Hydrologic Conditioning (20 minutes)

  • Condition the river mesh using different methods.
  • Provide supplemental depth to the stream mesh.

• Module 6: Full Workflow (30 mins)

  • Execute full workflow

• Module 6: Office Hours (20 mins)

  • Attendees work on their watersheds and troubleshoot issues with the help of the facilitators and fellow attendees.
  • Discussions and feedback on the workshop.

Acknowledgements:

Thanks to Rich Fiorella (LANL) for helping with Docker Container for the training.