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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Impact of Parameter Uncertainty Assessment of Critical SWAT Output Simulations

Authors
item Sexton, Aisha -
item Shirmohammadi, Adel -
item Sadeghi, Ali
item Montas, Hubert -

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 15, 2011
Publication Date: April 21, 2011
Citation: Sexton, A.M., Shirmohammadi, A., Sadeghi, A.M., Montas, H.J. 2011. Impact of parameter uncertainty assessment of critical SWAT output simulations. Transactions of the American Society of Agriculture and Biological Engineers. 54(2):461-471.

Interpretive Summary: Output uncertainty of watershed models is a major concern especially because of the legal, financial, and environmental ramifications of making decisions based on model results. The U.S. EPA’s Total Maximum Daily Load (TMDL) program leans heavily on these models to assist in meeting water quality standards for the reduction of impairing pollutants in waterbodies. We used statistical method (called MFORM) to tabulate total model uncertainties influencing streamflow, sediment, nitrate, and phosphate simulated by the Soil Water Assessment Tool (SWAT) watershed model. SWAT is one of the major USDA watershed models and is also one of the watershed model's used for TMDL analysis. Overall, the results showed the largest amount of uncertainty is the sediment component estimations, which reflects a lack of knowledge regarding the true value of input parameters with regard to the erosion aspects of the model. This research points to a need for improved model algorithms as well as better information about the true value of the erosion related input parameters.

Technical Abstract: Watershed models are increasingly being utilized to evaluate alternate management scenarios for improving water quality. The concern for using these tools in extensive programs such as the National Total Maximum Daily Load (TMDL) program is that the certainty of model results and efficacy of management scenarios are not often measured and therefore are not well known. In this study we used Mean Value First Order Reliability Method (MFORM), a computationally efficient uncertainty analysis method, to determine the contribution of parameter uncertainty to total model uncertainty in stream flow, sediment, and nutrient outputs in a small Maryland watershed. Examination of sensitive and uncertain parameters revealed that parameters not considered highly sensitive, contributed model output uncertainty to a large extent. Therefore, highly sensitive parameters should not be the only parameters considered in uncertainty or calibration analyses. Measures of output uncertainty showed that sediment had the largest amount of variance from its mean value (CV=28%), while nitrate, phosphate, and stream flow had considerably less variance with annual average CVs of 19%, 17%, and 15%, respectively. The largest amounts of model uncertainty occurred during wet periods. This study concluded that with improved knowledge of the true value and associated uncertainty of input parameters, and improved algorithms to capture the variability of rainfall and associated flow, watershed water quality models will be of much greater use to TMDL studies and studies alike.

Last Modified: 8/29/2014
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