Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 9/1/2007
Publication Date: 11/4/2007
Citation: Flanagan, D.C., Frankenberger, J.R., Fox, F.A., Wagner, L.E., Ascough Ii, J.C. 2007. Combining ARS Process-Based Water and Wind Erosion Prediction Technologies. Soil Science Society of America Annual Meeting Abstracts, November 4-8, 2007, New Orleans, Louisiana. 2007 CDROM.
Technical Abstract: Erosion process research in the United States has long been separated by location, experimental data collection, and prediction technologies. Erosion experiment stations were established in the l930’s throughout the country, however most examined erosion by water while a few in the Plains states were devoted to wind erosion research. The Universal Soil Loss Equation (USLE) and the Wind Erosion Equation (WEQ) were empirical equations developed from field experiment station data during the 1950’s-1960’s. Process-based technologies (WEPP - Water Erosion Prediction Project and WEPS - Wind Erosion Prediction System) have been created during the past 20 years, though the existing separation within the ARS research system and project management has resulted in two separate computer simulation models, each containing many similar components. A project is underway to combine technologies from WEPP and WEPS into a single system, containing many common components (e.g. water balance, plant growth, etc.). Two development paths are currently being followed. The first is utilizing the WEPS code as the framework and merging selected WEPP components (water balance, infiltration, runoff, water erosion) within it. The second is extracting individual components from WEPP, WEPS and other models, incorporating these as modules within the ARS Object Modeling System (OMS), and creating a combined wind and water model within the OMS framework. The direct WEPS-WEPP combination approach has progressed rapidly over the past 18 months, but is limited by the current WEPS single accounting region logic. The OMS approach will take substantially longer, due to the difficulty and time involved in creation of individual modules from legacy code. However, within the OMS system it should be much easier to create the necessary logic for the spatial heterogeneity that is typical of real-life field situations. Details and progress on this project, along with description of current prototype model software will be described.