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United States Department of Agriculture

Agricultural Research Service

Title: Wepp Testing and Evaluation

Author
item Nearing, Mark

Submitted to: Current and Emerging Erosion Prediction Technology Symposium
Publication Type: Abstract Only
Publication Acceptance Date: August 7, 1995
Publication Date: N/A

Technical Abstract: Thorough evaluation and testing of the WEPP model is critical to acceptance of the technology. It is very important to understand how well the model results match existing data and information on rates of erosion, including both soil loss and sediment yield. This type of model evaluation is the most critical aspect of scientific acceptability and is also very important to the land owner and the conservation planner. WEPP is a conservation planning tool, which implies that land management decisions, which always have associated monetary and social costs, will be based in part on the results of the model. It is important that the WEPP model results be critically and thoroughly evaluated relative to the best existing information on rates of soil erosion. Approx. 2000 plot yrs. of data from natural runoff plots at 11 locations were selected from the NRSED, located at the ARS-NSERL in W. Lafayette, IN to evaluate the WEPP model. The average period of record for the data sets was 9 yrs. In addition, 24-year records from conventional and conservation tilled corn plots at MO were used in a separate study. Historical climate and mgmt. information, as well as representative slope and soil information, was used to build input files for the model. These data are some of the most reliable from the database. Each sub-model of WEPP has been validated individually, including models of plant growth, residue management and decomposition, evapotranspiration and water balance, winter processes, irrigation, and climate generation. Also, sensitivity analyses have been made to determine the most important model input parameter for obtaining reliable responses. Error propagation and confidence ranges have been determined using Monte-Carlo, first-order, and point estimate techniques.

Last Modified: 8/31/2014
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