The Regional Watershed Spreadsheet Model (RWSM) was developed to estimate average annual regional and sub-regional scale loads for the San Francisco Bay Area. It is part of a class of deterministic empirical models based on the volume-concentration method. The strengths of volume-concentration models include relatively fewer data input requirements than more complex dynamic simulation models such as Storm Water Management Model (SWMM) or Hydrological Stimulation Program-Fortran (HSPF), explicit selection of land uses, suitability for hypothesis testing, and manual and automated calibration or verification procedures that enable estimates of error and bias as a component of the outputs. These strengths make it a useful tool for providing regional (Bay wide) and sub-regional (e.g. individual county, Bay segment, or priority margin unit) estimates of pollutant loads. It can also be used to provide hypotheses about which watersheds may be exporting relatively higher or lower loads to the Bay relative to watershed area and for estimating regionally averaged land use specific event mean concentrations (e.g. ng/L) and exports (e.g. g/km2). The RWSM also presents an appropriate baseline and a flexible platform for analyzing the potential for flow and load changes in response to management measures at a gross scale (e.g. large scale land use changes associated with redevelopment and new development), and runoff changes in relation to climate change and changes in impoundment (again at gross scales). Although not the focus of the output, numerous useful watershed statistics are generated with the model.
RWSM Toolbox v1.0
Source code for the RWSM ArcGIS Toolbox, see the user manual for instructions.
rwsm_v1.1.zip (30 K)
Geodatabase contains a soils feature class.
input_features.gdb.zip (23 MB)
The analysis requires slope and precipitation data in raster format. The linked geodatabase contains a slope raster as well as three choices for precipitation. You can see a description for each precipitation raster in the table below.
input_rasters.gdb.zip (290 MB)
|prismppt_1980to2010||The 30-yr annual average precipitation for the period 1980 - 2010. This dataset was developed by The PRISM Climate Group, Oregon State University. http://prism.oregonstate.edu/normals/|
|prismppt_1980to2010minus5||This dataset takes the 30-yr annual average precipitation for the period 1980 - 2010, and subtracts 5 inches to account for initial abstraction over the course of the rainfall year.|
This dataset is the prismppt_1980to2010minus5 dataset except resampled in GIS to produce a smaller gridsize. This action is described in the manual as necessary if your watersheds are very small.
Test data set containing polygons for example watersheds:
input_watersheds.gdb.zip (74 K)
Land Use Layers
There are three options for land use layers, you can download them all here (461 MB), or download them individually below:
|File||Description||File Size (zip)|
|ABAG2005_orig.gdb.zip||Land use in the Bay Area as of 2005.||148 MB|
|ABAG2005_OldUrbanSAs.gdb.zip||This is the ABAG2005_OldUrban.gdb but includes source areas burned into the layer.||159 MB|
|ABAG2005_OldUrban.gdb.zip||This is the ABAG2005_orig.gdb except distinguishes between newer and older urban areas.||
* Association of Bay Area Governments (ABAG), 2006. Existing Land Use in 2005: Data for Bay Area Counties. Oakland, California USA. DVD.
They hydrology model requires both land use lookup and runoff coefficient CSV files:
|LandUse.csv||Contains classification names, classification codes, and descriptions for land use codes used in the Land Use Vector Layer.||8.5 K|
|RunoffCoeff.csv||Contains runoff coefficient data.||30 K|
While the RWSM Hydrology Model requires feature classes, rasters, and CSV files the Pollutant Model leverages a series of CSV files to calculate pollutant loads using Hydrology Model outputs.
Pollutant_Model.zip (535 K)
For more comprehensive information about the RWSM analysis, as well as instructions for running the model, view the RWSM Toolkit User Manual:
RWSM Tool-Kit User Manual.pdf (750 KB)