Spatial application of WEPS for estimating wind erosion in the Pacific Northwest

Authors: GAO, JINCHENG - Kansas State University; Wagner, Larry; Fox, Jr, Fred; CHUNG, SERENA - Washington State University; VAUGHN, JOSEPH - Washington State University; LAMB, BRIAN - Washington State University

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/12/2013
Publication Date: 5/1/2013
Citation: Gao, J., Wagner, L.E., Fox, F.A., Chung, S., Vaughn, J., Lamb, B.K. 2013. Spatial application of WEPS for estimating wind erosion in the Pacific Northwest. Transactions of the ASABE. 56(2):613-624.

Interpretive Summary: The Wind Erosion Prediction System (WEPS) was designed by the USDA-ARS to simulate soil erosion on cropland with uniform soil and a single crop. We modified the WEPS source code to allow it not only to run on multiple grids, but also to “save the state” of the model so it can be re-initiated from that state in future runs to allow the model to be started and “stepped through time” incrementally under various future climate or forecast weather scenarios. This modified version of WEPS was applied to estimate emissions for Washington State as the basis for input of emissions into the AIRPACT regional air quality forecast system for the Northwest. For a specific dust storm, the results from WEPS showed reasonable agreement with satellite images of the dust storm. The study shows that WEPS can be successfully extended to run from one field grid to multiple grids and the model can identify the regions with high potential for soil erosion. The WEPS can be used for real-time monitoring of soil erosion and air quality in a large region if actual and forecast weather inputs are available.

Technical Abstract: The Wind Erosion Prediction System (WEPS) is used to simulate soil erosion on cropland and was originally designed to run simulations on a field-scale size. This study extended WEPS to run on multiple fields (grids) independently to cover a large region and to conduct an initial investigation to assess how well WEPS performed in that environment by comparing simulations for two historical dust events with field observations and satellite images in the Columbia Plateau region of Washington. We modified the WEPS source code to “save the state” of the model so it can be re-initiated from that state in future runs to allow the model to be started and “stepped through time” incrementally under various future climate or forecast weather scenarios. We initially ran WEPS for all of Washington, with the entire Pacific Northwest region as our ultimate target area to provide PM10 and PM2.5 emissions as input to the chemical transport model CMAQ that is used by the AIRPACT regional air-quality modeling system for the Pacific Northwest. Three principal inputs to WEPS are: a) meteorological data, b) soil data, and c) crop management practices. The overlap of those data at a 1-km x 1-km grid size is the basic data input for running the spatial model. The climatic data from a three-year period were stochastically generated based on statistical representations of past meteorological measurements from stations in the region and were used for initializing WEPS; then a three-day set of meteorological data corresponding with dust storm events were selected for simulation of WEPS for wind erosion in Washington. The crop management data were selected based on the land-use cover and crop management zones, and the soil data were derived from the US SSURGO database. We aggregated the outputs from 1-km x 1-km grids into 12-km x 12-km grids for easier visualization, then mapped the total surface soil erosion, suspension, and PM10 for a 12-km x 12-km grid. The study shows that WEPS can be successfully extended to run from one field grid to multiple grids and the model can identify the regions with high potential for soil erosion. It also demonstrates that WEPS can be used for real-time monitoring of soil erosion and air quality in a large region if actual and forecast weather inputs are available.