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Title: A stochastic method to characterize model uncertainty for a Nutrient TMDL

Author
item SEXTON, AISHA - University Of Maryland
item SHIRMOHAMMADI, ADEL - University Of Maryland
item Sadeghi, Ali
item MONTAS, HUBERT - University Of Maryland

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/15/2011
Publication Date: 11/9/2011
Citation: Sexton, A.M., Shirmohammadi, A., Sadeghi, A.M., Montas, H.J. 2011. A stochastic method to characterize model uncertainty for a Nutrient TMDL. Transactions of the ASABE. 54(6):2197-2207.

Interpretive Summary: The U.S. EPA’s Total Maximum Daily Load (TMDL) program uses computer models to determine the amount of contaminants that streams or other water bodies can receive. One of the main problems with using models is that the uncertainties associated with the model output is normally not known and often a vlaue is arbitrarily selected as part of the Margin of Safety (MOS) portion of TMDLs. In this study, we describe and demonstrate a formal method to scientifically derive the MOS value. This methodology is an improvement over current methods of tabulating MOS because it provides a scientifically derived measure of model uncertainty for TMDL analysis.

Technical Abstract: The U.S. EPA’s Total Maximum Daily Load (TMDL) program has encountered resistances in its implementation partly because of its strong dependence on mathematical models to set limitations on the release of impairing substances. The uncertainty associated with predictions of such models is often not scientifically quantified and typically assigned as an arbitrary margin of safety (MOS) in the TMDL allocation. The Soil Water Assessment Tool (SWAT) model was evaluated to determine its applicability to identify the impairment status and tabulate a nutrient TMDL for a water body located in the Piedmont physiographic region of Maryland. The methodology for tabulating the nutrient TMDL is an enhancement over current methods used in Maryland. The mean-value first-order reliability method (MFORM) was paired with a stochastic approach to tabulate a formal estimate of model uncertainty and MOS. Monthly streamflow estimates were quite good with Nash-Sutcliff Efficiency (NSE) coefficients of 0.75 and 0.70, for calibration and validation respectively. Sediment and nutrients were not estimated as well on a monthly basis, however large improvements were observed on annual time scales. MOS was determined based on the desired level of confidence in meeting the water quality standard. The water quality standard was met at 20% nitrate reduction (9.9 kg N/d) with a 37.5% level of confidence. The water quality goal, a 75% level of confidence, was met by a 30% nitrate reduction (8.6 kg N/d). Therefore, the MOS load (the difference between the standard and the goal) was 1.3 kg N/d or 10% of the baseline load. These results indicate that SWAT is a suitable model for use in TMDL assessments of impaired water bodies, especially assessments based on long term observations. In addition, the stochastic method used to quantify MOS for a nitrate TMDL is an improvement over current methods because it provides a formal, scientifically derived measure of model uncertainty.