Skip to main content
ARS Home » Research » Publications at this Location » Publication #268331

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

item GAO, JINCHENG - Kansas State University
item Wagner, Larry
item Fox, Jr, Fred
item CHUNG, SERENA - Washington State University
item LAMB, BRIAN - Washington State University

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/15/2011
Publication Date: 9/1/2011
Citation: Gao, J., Wagner, L.E., Fox, F.A., Chung, S.H., Lamb, B.K. 2011. Spatial application of WEPS for estimating wind erosion in the Pacific Northwest. In: Proceedings International Symposium on Erosion and Landscape Evolution (ISELE), 18-21 September 2011, Anchorage, Alaska. ISELE Paper No. 11023. D.C. Flanagan, J.C. Ascough II, and J.L Nieber (eds.). St. Joseph, MI ASABE.

Interpretive Summary:

Technical Abstract: The Wind Erosion Prediction System (WEPS) is used to simulate soil erosion on croplands and was originally designed to run field scale simulations. This research is an extension of the WEPS model to run on multiple fields (grids) covering a larger region. We modified the WEPS source code to allow it to run not only on multiple grids, but also to “save the state” of the model so that it can be re-initiated from that state in future runs. The Pacific Northwest region is the target area with the state of Washington being the initial study region. Three principle inputs to WEPS are: a) climate data, b) soil data and c) management practices. The climate data were generated from the closest weather station. The soil data were derived from the NRCS SSURGO database. A crop management file was selected from crop management zone files developed by USDA-NRCS and was based on the crop grown in the region. The overlap of those data at 1-km by 1-km grids is the basic data input for running the spatial model. A one-year period was selected for the WEPS model simulation at each grid for the whole state of Washington. The outputs from 1-km grids were aggregated into 12-km grids for easier visualization. The total surface soil erosion, suspension, and PM10 for a 12-km grid were mapped. The research shows that the WEPS model could be successfully extended to run from one field grid to multiple grids and demonstrates that regions with high potential for soil erosion can be identified. The WEPS model could also be used for real-time monitoring of soil erosion and air quality in a large region.