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MODELING THE BIG BLACK RIVER: EVALUATION OF A SIMPLISTIC WATER QUALITY MODEL

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Watershed Management to Meet Water Quality Standards and Emerging TMDL (Total Maximum Daily Load) Proceedings of the Third Conference 5-9 March 2005 (Atlanta, Georgia USA) Publication Date 5 March 2005  701P0105.(doi:10.13031/2013.18108)
Authors:   Kimberly S. Caviness, Garey A. Fox, and Patrick N. Deliman
Keywords:   Dissolved Oxygen, Numerical Modeling, Rivers/Streams, Total Maximum Daily Load, Wastewater Discharge, Water Quality Modeling

The Mississippi Department of Environmental Quality (MDEQ) uses the Steady Riverine Environmental Assessment Model (STREAM) to establish permitted effluent limitations for industrial, commercial, and municipal facilities. While the U.S. Environmental Protection Agency (EPA) has approved of its use, questions arise regarding the model’s simplicity. This research first evaluated STREAM using a statistical evaluation procedure based on sensitivity analyses, input probability distribution functions, and Monte Carlo simulation with site-specific data from a 46-mile reach of the Big Black River in central Mississippi. STREAM reasonably predicted dissolved oxygen (DO) based on a comparison of output probability distributions with observed DO. The observed DO was consistently within 80% confidence intervals of model predictions. This research also evaluated STREAM by comparing observed DO with predictions by both STREAM and the Enhanced Stream Water Quality Model (QUAL2E). One version of the QUAL2E and STREAM models utilized site-specific input data. A second version of each model involved additional calibration. A third version of STREAM was an uncalibrated model developed following MDEQ Regulations (1995) for cases where intensive input data are unavailable. All versions of the models were simulated at the 7Q10 flow for the Big Black River, the minimum flow expected for seven consecutive days during a period of ten years. STREAM over predicted while QUAL2E under predicted DO with the site-specific input data. Percent errors ranged between 4.8% and 11.2% for STREAM and 3.3% and 5.1% for QUAL2E. The uncalibrated STREAM model predicted the lowest DO for all scenarios and correspondingly provided the most conservative DO predictions.

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