Formatting the bib file lowercased the citations - oops

documentation/controls.rst

@@ -6,7 +6,7 @@ Water network controls
 ======================================
 
 One of the key features of water network models is the ability to control pipes, pumps, and valves using simple and complex conditions.  
-EPANET uses "controls" and "rules" to define conditions :cite:p:`Ross00`. WNTR replicates EPANET functionality, and includes additional options, as described below. The EPANET user manual provides more information on simple controls and rule-based controls (controls and rules, respectively in WNTR) :cite:p:`Ross00`.
+EPANET uses "controls" and "rules" to define conditions :cite:p:`ross00`. WNTR replicates EPANET functionality, and includes additional options, as described below. The EPANET user manual provides more information on simple controls and rule-based controls (controls and rules, respectively in WNTR) :cite:p:`ross00`.
 
 **Controls** are defined using an "IF condition; THEN action" format.  
 Controls use a single action (i.e., closing/opening a link or changing the setting) based on a single condition (i.e., time based or tank level based).

documentation/criticality.rst

@@ -13,7 +13,7 @@ In threat agnostic analysis, the cause of the disruption is not modeled directly
 Rather, a series of simulations can be used to perform N-k contingency analysis, where N is the number 
 of elements and k elements fail.
 
-In water distribution systems analysis, N-1 contingency analysis is commonly called criticality analysis :cite:p:`WaWC06`.
+In water distribution systems analysis, N-1 contingency analysis is commonly called criticality analysis :cite:p:`wawc06`.
 WNTR is commonly used to run criticality analysis, where a series of simulations are run to determine the impact of 
 individual failures on the system.  
 This framework can be expanded to include analysis where two or more elements fail at one time or in succession.

documentation/disaster_models.rst

@@ -30,14 +30,14 @@ and change demands for fire conditions, as described in the sections below.
 The :class:`~wntr.scenario.earthquake.Earthquake` class includes methods 
 to compute peak ground acceleration, peak ground velocity, and repair rate based on the earthquake
 location and magnitude.  
-Alternatively, external earthquake models or databases (e.g., ShakeMap :cite:p:`WWQP06`) can be used to compute earthquake properties and 
+Alternatively, external earthquake models or databases (e.g., ShakeMap :cite:p:`wwqp06`) can be used to compute earthquake properties and 
 those properties can be loaded into Python for analysis in WNTR.
 
 When simulating the effects of an earthquake, fragility curves are commonly used to define the probability that a component is 
 damaged with respect to 
 peak ground acceleration, peak ground velocity, 
 or repair rate.
-The American Lifelines Alliance report :cite:p:`ALA01` includes seismic fragility curves 
+The American Lifelines Alliance report :cite:p:`ala01` includes seismic fragility curves 
 for water system components.
 See :ref:`fragility_curves` for more information.
 
@@ -131,7 +131,7 @@ Power outage
 -------------
 Power outages can be small and brief, or they can also span over several days and 
 affect whole regions as seen in the 2003 Northeast Blackout. 
-While the Northeast Blackout was an extreme case, a 2012 Lawrence Berkeley National Laboratory study :cite:p:`ELLT12` 
+While the Northeast Blackout was an extreme case, a 2012 Lawrence Berkeley National Laboratory study :cite:p:`ellt12` 
 showed the frequency and duration of power outages are increasing domestically by a 
 rate of two percent annually. In water distribution systems, 
 a power outage can cause pump stations to shut down and result in 
@@ -163,7 +163,7 @@ Fires
 WNTR can be used to simulate damage caused to system components due to fire and/or to simulate water usage due to fighting fires. To fight fires, additional water is drawn from the system. Fire codes vary by 
 state. Minimum required fire flow and duration are generally based on the building's area and purpose.
 While small residential fires might require 1500 gallons/minute for 2 hours, large commercial
-spaces might require 8000 gallons/minute for 4 hours :cite:p:`ICC12`. This additional demand can 
+spaces might require 8000 gallons/minute for 4 hours :cite:p:`icc12`. This additional demand can 
 have a large impact on water pressure in the system.  
 
 WNTR can be used to simulate firefighting conditions in the system.  

documentation/fragility.rst

@@ -11,7 +11,7 @@ of exceeding a given damage state as a function of environmental change.
 Fragility curves are closely related to survival curves, which are used to define the probability of component failure due to age.  
 For example, to estimate earthquake damage, fragility curves are defined as a function of peak
 ground acceleration, peak ground velocity, or repair rate.  
-The American Lifelines Alliance report :cite:p:`ALA01`
+The American Lifelines Alliance report :cite:p:`ala01`
 includes seismic fragility curves for water network components.
 Fragility curves can also
 be defined as a function of flood stage, wind speed, and temperature for other

documentation/framework.rst

@@ -82,7 +82,7 @@ These classes are listed in :numref:`table-sim-subpackage`.
    =================================================  =============================================================================================================================================================================================================================================================================
    Class                                              Description
    =================================================  =============================================================================================================================================================================================================================================================================
-   :class:`~wntr.sim.epanet.EpanetSimulator`          The EpanetSimulator can run both the EPANET 2.00.12 Programmer's Toolkit :cite:p:`Ross00` and EPANET 2.2.0 Programmer's Toolkit :cite:p:`RWTS20` to run hydraulic and water quality simulations.  
+   :class:`~wntr.sim.epanet.EpanetSimulator`          The EpanetSimulator can run both the EPANET 2.00.12 Programmer's Toolkit :cite:p:`ross00` and EPANET 2.2.0 Programmer's Toolkit :cite:p:`rwrs20` to run hydraulic and water quality simulations.  
                                                       EPANET 2.2.0 (which is used by default) includes both demand-driven and pressure dependent analysis, while EPANET 2.00.12 includes only demand-driven analysis. 
                                                       When using the EpanetSimulator, the water network model is written to an EPANET INP file which is used to run an EPANET simulation. This allows the user to run 
                                                       EPANET simulations, while taking advantage of additional analysis options in WNTR. 

documentation/gis.rst

@@ -46,7 +46,7 @@ Open source GIS platforms include QGIS and GRASS GIS.
 The following section describes capabilities in WTNR that use GeoPandas GeoDataFrames.  
 
 .. note:: 
-   Functions that use GeoDataFrames require the Python package **geopandas** :cite:p:`JVFM21` 
+   Functions that use GeoDataFrames require the Python package **geopandas** :cite:p:`jvfm21` 
    and **rtree** :cite:p:`rtree`. Both are optional dependencies of WNTR.
    Note that **shapely** is installed with geopandas.
 

documentation/graphics.rst

@@ -137,7 +137,7 @@ As with basic network graphics, a wide range of plotting options can be supplied
 However, link attributes currently cannot be displayed on the graphic.
 
 .. note:: 
-   This function requires the Python package **plotly** :cite:p:`SPHC16`, which is an optional dependency of WNTR.
+   This function requires the Python package **plotly** :cite:p:`sphc16`, which is an optional dependency of WNTR.
 
 The following example plots the network along with node population (:numref:`fig-plotly`).
 
@@ -164,10 +164,10 @@ See :ref:`modify_node_coords` for more information on converting node coordinate
 As with basic network graphics, a wide range of plotting options can be supplied. 
 
 .. note:: 
-   This function requires the Python package **folium** :cite:p:`Folium`, which is an optional dependency of WNTR.
+   This function requires the Python package **folium** :cite:p:`folium`, which is an optional dependency of WNTR.
 
 The following example using EPANET Example Network 3 (Net3) converts node coordinates to longitude/latitude and plots the network along 
-with pipe length over the city of Albuquerque (for demonstration purposes only) (:numref:`fig-leaflet`). The longitude and latitude for two locations are needed to plot the network. For the EPANET Example Network 3, these locations are the reservoir 'Lake' and node '219'. This example requires the Python package **utm** :cite:p:`Bieni19` to convert the node coordinates.
+with pipe length over the city of Albuquerque (for demonstration purposes only) (:numref:`fig-leaflet`). The longitude and latitude for two locations are needed to plot the network. For the EPANET Example Network 3, these locations are the reservoir 'Lake' and node '219'. This example requires the Python package **utm** :cite:p:`bieni19` to convert the node coordinates.
 
 .. doctest::
 
@@ -246,7 +246,7 @@ Interactive time series graphics are useful when visualizing large datasets.
 Basic time series graphics can be converted to interactive time series graphics using the ``plotly.express`` module.
 
 .. note:: 
-   This functionality requires the Python package **plotly** :cite:p:`SPHC16`, which is an optional dependency of WNTR.
+   This functionality requires the Python package **plotly** :cite:p:`sphc16`, which is an optional dependency of WNTR.
 
 The following example uses simulation results from above, and converts the graphic to an interactive graphic  (:numref:`fig-interactive-timeseries`).
 

documentation/hydraulics.rst

@@ -12,7 +12,7 @@ See :ref:`software_framework` for more information on features and limitations o
 
 EpanetSimulator
 -----------------
-The EpanetSimulator can be used to run EPANET 2.00.12 Programmer's Toolkit :cite:p:`Ross00` or EPANET 2.2.0 Programmer's Toolkit :cite:p:`RWTS20`.  
+The EpanetSimulator can be used to run EPANET 2.00.12 Programmer's Toolkit :cite:p:`ross00` or EPANET 2.2.0 Programmer's Toolkit :cite:p:`rwts20`.  
 EPANET 2.2.0 is used by default and runs demand-driven and pressure dependent hydraulic analysis.  
 EPANET 2.00.12 runs demand-driven hydraulic analysis only.
 Both versions can also run water quality simulations, as described in :ref:`water_quality_simulation`.  
@@ -111,7 +111,7 @@ More information on water network options can be found in :ref:`options`.
 
 Mass balance at nodes
 -------------------------
-Both simulators use the mass balance equations from EPANET :cite:p:`Ross00`:
+Both simulators use the mass balance equations from EPANET :cite:p:`ross00`:
 
 .. math::
 
@@ -127,7 +127,7 @@ If water is flowing out of node :math:`n` and into pipe :math:`p`, then
 
 Headloss in pipes
 -------------------------
-Both simulators use conservation of energy formulas from EPANET :cite:p:`Ross00`. 
+Both simulators use conservation of energy formulas from EPANET :cite:p:`ross00`. 
 While the EpanetSimulator can use the Hazen-Williams and Chezy-Manning pipe head loss formulas, 
 the WNTRSimulator uses only the Hazen-Williams head loss formula, shown below.
 
@@ -225,7 +225,7 @@ The mass balance and headloss equations described above are solved by
 simultaneously determining demand along with the network pressures and flow rates.  
 
 Both simulators can run hydraulics using a pressure dependent demand simulation
-according to the following pressure-demand relationship :cite:p:`WaSM88`:
+according to the following pressure-demand relationship :cite:p:`wasm88`:
 
 .. math::
 
@@ -308,7 +308,7 @@ Users interested in using the EpanetSimulator to model leaks can still do so by
 emitter coefficients. 
 
 When using the WNTRSimulator, leaks are modeled with a general form of the equation proposed by Crowl and Louvar
-:cite:p:`CrLo02` where the mass flow rate of fluid through the hole is expressed as:
+:cite:p:`crlo02` where the mass flow rate of fluid through the hole is expressed as:
 
 .. math::
 
@@ -328,9 +328,9 @@ where
 :math:`g` is the acceleration of gravity (m/s²), and 
 :math:`\rho` is the density of the fluid (kg/m³).
 
-The default discharge coefficient is 0.75 (assuming turbulent flow) :cite:p:`Lamb01`, but 
+The default discharge coefficient is 0.75 (assuming turbulent flow) :cite:p:`lamb01`, but 
 the user can specify other values if needed.  
-The value of :math:`\alpha` is set to 0.5 (assuming large leaks out of steel pipes) :cite:p:`Lamb01` and currently cannot be changed by the user.
+The value of :math:`\alpha` is set to 0.5 (assuming large leaks out of steel pipes) :cite:p:`lamb01` and currently cannot be changed by the user.
 
 Leaks can be added to junctions and tanks.  
 A pipe break is modeled using a leak area large enough to drain the pipe.  

documentation/installation.rst

@@ -237,15 +237,15 @@ Requirements
 Requirements for WNTR include 64-bit Python (tested on versions 3.7, 3.8, 3.9, and 3.10) along with several Python packages. 
 Users should have experience using Python (https://www.python.org/), including the installation of additional Python packages. The following Python packages are required:
 
-* NumPy :cite:p:`VaCV11`: used to support large, multi-dimensional arrays and matrices, 
+* NumPy :cite:p:`vacv11`: used to support large, multi-dimensional arrays and matrices, 
   http://www.numpy.org/
-* SciPy :cite:p:`VaCV11`: used to support efficient routines for numerical integration, 
+* SciPy :cite:p:`vacv11`: used to support efficient routines for numerical integration, 
   http://www.scipy.org/
-* NetworkX :cite:p:`HaSS08`: used to create and analyze complex networks, 
+* NetworkX :cite:p:`hass08`: used to create and analyze complex networks, 
   https://networkx.github.io/
-* pandas :cite:p:`Mcki13`: used to analyze and store time series data, 
+* pandas :cite:p:`mcki13`: used to analyze and store time series data, 
   http://pandas.pydata.org/
-* Matplotlib :cite:p:`Hunt07`: used to produce graphics, 
+* Matplotlib :cite:p:`hunt07`: used to produce graphics, 
   http://matplotlib.org/
 
 These packages are included in the Anaconda Python distribution.
@@ -257,17 +257,17 @@ Optional dependencies
 
 The following Python packages are optional:
 
-* plotly :cite:p:`SPHC16`: used to produce interactive scalable graphics, 
+* plotly :cite:p:`sphc16`: used to produce interactive scalable graphics, 
   https://plot.ly/
-* folium :cite:p:`Folium`: used to produce Leaflet maps, 
+* folium :cite:p:`folium`: used to produce Leaflet maps, 
   http://python-visualization.github.io/folium/
-* utm :cite:p:`Bieni19`: used to translate node coordinates to utm and lat/long,
+* utm :cite:p:`bieni19`: used to translate node coordinates to utm and lat/long,
   https://pypi.org/project/utm/
-* geopandas :cite:p:`JVFM21`: used to work with geospatial data,
+* geopandas :cite:p:`jvfm21`: used to work with geospatial data,
   https://geopandas.org/
 * rtree :cite:p:`rtree`: used for overlay operations in geopandas,
   https://rtree.readthedocs.io/
-* openpyxl :cite:p:`GaCl18`: used to read/write to Microsoft® Excel® spreadsheets,
+* openpyxl :cite:p:`gacl18`: used to read/write to Microsoft® Excel® spreadsheets,
   https://openpyxl.readthedocs.io
 
 All of these packages **except geopandas** are included in the Anaconda Python distribution.

documentation/layers.rst

@@ -89,7 +89,7 @@ The valve layer can be included in water network graphics (:numref:`fig-random-v
    Valve layer using random placement.
 
 The **strategic** placement specifies the number of pipes (n) from each node that do NOT contain a valve.  
-In this case, n is generally 0, 1, or 2 (i.e., N, N-1, or N-2 valve placement) :cite:p:`WaWC06` :cite:p:`LWFZ17`.
+In this case, n is generally 0, 1, or 2 (i.e., N, N-1, or N-2 valve placement) :cite:p:`wawc06` :cite:p:`lwfz17`.
 For example, if three pipes connect to a node and n = 2, then two of those pipes will not contain a valve and one pipe will contain a valve.
 The following example generates a strategic N-2 valve placement.
 The valve layer can be included in water network graphics (:numref:`fig-strategic-valve-layer`).

documentation/morph.rst

@@ -13,7 +13,7 @@ splitting or breaking pipes.
 Network skeletonization
 ----------------------------
 The goal of network skeletonization is to reduce the size of a water network model with minimal impact on system behavior.
-Network skeletonization in WNTR follows the procedure outlined in :cite:p:`WCSG03`.  
+Network skeletonization in WNTR follows the procedure outlined in :cite:p:`wcsg03`.  
 The skeletonization process retains all tanks, reservoirs, valves, and pumps, along with all junctions and pipes that are associated with controls.
 Junction demands and demand patterns are retained in the skeletonized model, as described below.
 Merged pipes are assigned equivalent properties for diameter, length, and roughness to approximate the updated system behavior.
@@ -241,7 +241,7 @@ WNTR includes several options to modify node coordinates, denoted as :math:`(x,
   the nodes could be in the upper right and lower left).
 
 .. note:: 
-   Functions that convert coordinates to UTM and longitude/latitude require the Python package **utm** :cite:p:`Bieni19`, which is an optional dependency of WNTR.
+   Functions that convert coordinates to UTM and longitude/latitude require the Python package **utm** :cite:p:`bieni19`, which is an optional dependency of WNTR.
 
 The following example returns a copy of the water network model with 
 node coordinates scaled by 100 m.