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Title: Sensitivity and first-order/Monte Carlo uncertainty analysis of the WEPP hillslope erosion model

Author
item Ascough Ii, James
item Flanagan, Dennis
item Nearing, Mark
item ENGEL, BERNARD - PURDUE UNIVERSITY

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/7/2013
Publication Date: 4/30/2013
Citation: Ascough II, J.C., Flanagan, D.C., Nearing, M.A., Engel, B.A. 2013. Sensitivity and first-order/Monte Carlo uncertainty analysis of the WEPP hillslope erosion model. Transactions of the ASABE. 56(2)/437-452.

Interpretive Summary: Many complex hydrologic/water quality (H/WQ) models have been developed, but a detailed description of expectations in model response and how they may be applied are rarely provided. Performing a comprehensive evaluation is a valuable step towards understanding and using a predictive model. This paper applies an evaluation framework for analysis of a complex, process-based water erosion prediction tool, the USDA Water Erosion Prediction Project (WEPP) model (Version 2004.7). The evaluation framework combines sensitivity analysis and the uncertainty analysis techniques of first order error analysis (FOA) and Monte Carlo simulation with Latin Hypercube Sampling (LHS). Assessment of the WEPP hillslope profile model on a Midwestern Miami silt loam soil for three separate erosion process cases (as defined by slope length and steepness) is described. WEPP model runoff, soil loss, and corn (Zea Mays L.) yield output responses in the form of expected values and error variances were determined to illustrate model prediction uncertainty. Sensitivity analysis results show the WEPP model response for runoff to be most sensitive to effective hydraulic conductivity and soil parameters used in the crusting factor adjustment. The soil loss response was most sensitive to erodibility factors and soil and management parameters influencing infiltration. The FOA did not approximate the WEPP model responses for runoff and soil loss well due to model nonlinearity. Recommendations based on sensitivity analysis in conjunction with Monte Carlo LHS simulation are presented for evaluating H/WQ models. Derivation of output response error variances through Monte Carlo LHS simulation is also suggested for WEPP and other H/WQ models.

Technical Abstract: Many complex hydrologic/water quality (H/WQ) models have been developed, but a detailed description of expectations in model response and how they may be applied are rarely provided. Performing a comprehensive evaluation is a valuable step towards understanding and using a predictive model. This paper applies an evaluation framework for analysis of a complex, process-based water erosion prediction tool, the USDA Water Erosion Prediction Project (WEPP) model (Version 2004.7). The evaluation framework combines sensitivity analysis and the uncertainty analysis techniques of first order error analysis (FOA) and Monte Carlo simulation with Latin Hypercube Sampling (LHS). Assessment of the WEPP hillslope profile model on a Midwestern Miami silt loam soil for three separate erosion process cases (as defined by slope length and steepness) is described. WEPP model runoff, soil loss, and corn (Zea Mays L.) yield output responses in the form of expected values and error variances were determined to illustrate model prediction uncertainty. Sensitivity analysis results show the WEPP model response for runoff to be most sensitive to effective hydraulic conductivity and soil parameters used in the crusting factor adjustment. The soil loss response was most sensitive to erodibility factors and soil and management parameters influencing infiltration. The FOA did not approximate the WEPP model responses for runoff and soil loss well due to model nonlinearity. Recommendations based on sensitivity analysis in conjunction with Monte Carlo LHS simulation are presented for evaluating H/WQ models. Derivation of output response error variances through Monte Carlo LHS simulation is also suggested for WEPP and other H/WQ models.