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ARS Home » Midwest Area » West Lafayette, Indiana » National Soil Erosion Research Laboratory » Research » Publications at this Location » Publication #63671


item RISSE, L
item Nearing, Mark
item LIU, B
item Zhang, Xunchang
item Baffaut, Claire
item Laflen, John

Submitted to: International Erosion Control Association Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 10/12/1995
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The USDA-Water Erosion Prediction Project (WEPP) was initiated in 1985 to develop a new generation of water erosion prediction technology for use in soil and water conservation planning and assessment. The WEPP computer model is based on the fundamentals of hydrology, plant sciences, soil physics, and erosion mechanics. By including components to consider processes such as climate generation, snowmelt, irrigation, crop growth, residue decomposition, rill hydraulics, and transport and deposition of sediment in both rill and interrill areas, the model offers several advantages over existing erosion prediction technology. It also has the capability of accommodating spatial and temporal variability in topography, soil properties, cropping and management, and sediment detachment and deposition. As the WEPP project approaches its delivery to the user agencies, considerable validation is being conducted to insure that the model produces reliable results. This paper shall present an overview of some of these results. Initially, the paper will assess the ability of the model to produce reasonable results compared to other models such as the USLE and RUSLE. Several combinations of climates, soils, cropping, and slope lengths and steepnesses were run using the WEPP model. The predicted soil loss factors were compared to RUSLE El, K, C, and LS factors to determine if both models predict the same expected the trends relating to the factors that control soil erosion. In the second part of the testing, WEPP predictions of runoff and soil loss from natural runoff plots at 11 different locations were compared to measured data. This allowed for an assessment of the model accuracy and located potential sources of error.