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United States Department of Agriculture

Agricultural Research Service

Title: Practical Application of Sensitivity and Uncertainty Analysis Techniques: Lessons Learned with Two Agricultural System Models

Authors
item Ascough, James
item Ma, Liwang

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: October 1, 2004
Publication Date: November 1, 2004
Citation: Ascough Ii, J.C., Ma, L. 2004. Practical application of sensitivity and uncertainty analysis techniques: lessons learned with two agricultural system models. Meeting Abstract. www.asa-cssa-ssa.org/anmeet. Seattle, WA. Oct.31-11/4/2004.

Interpretive Summary: Many complex agricultural system models have been developed, but a detailed description of expectations in model response and how they may be applied are rarely provided. We apply a sensitivity and uncertainty [first order error analysis (FOA) and Monte Carlo Latin Hypercube Sampling (LHS) simulation] analysis framework for evaluation of the WEPP and RZWQM erosion and water quality models. 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. RZWQM plant uptake, yield, and nitrate leaching output responses were most sensitive to plant growth input parameters and manure application rates. RZWQM output responses were also more sensitive to the average saturated conductivity of the entire soil profile than to individual soil layers. 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 agricultural system models. Derivation of output response error variances through Monte Carlo LHS simulation is also suggested for agricultural system models.

Technical Abstract: Many complex agricultural system models have been developed, but a detailed description of expectations in model response and how they may be applied are rarely provided. We apply a sensitivity and uncertainty [first order error analysis (FOA) and Monte Carlo Latin Hypercube Sampling (LHS) simulation] analysis framework for evaluation of the WEPP and RZWQM erosion and water quality models. 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. RZWQM plant uptake, yield, and nitrate leaching output responses were most sensitive to plant growth input parameters and manure application rates. RZWQM output responses were also more sensitive to the average saturated conductivity of the entire soil profile than to individual soil layers. 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 agricultural system models. Derivation of output response error variances through Monte Carlo LHS simulation is also suggested for agricultural system models.

Last Modified: 9/20/2014
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