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Analysis of the HSPF Model for Predicting In-stream Fecal Coliform Concentrations

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

Citation:  Paper number  022157,  2002 ASAE Annual Meeting . (doi: 10.13031/2013.10412) @2002
Authors:   Sabu Paul, Patricia Haan, Marty D. Matlock, Saqib Mukhtar
Keywords:   Water quality, watershed, modeling, HSPF, fecal coliform, uncertainty analysis

Salado Creek in Bexar County, Texas is one of 65 streams listed in Clean Water Acts 303(d), as an impaired waterbody for its high concentration of fecal coliform bacteria. The Hydrological Simulation Program-FORTRAN (HSPF) was applied to the Salado Creek watershed for studying its applicability as a prediction tool for in-stream fecal coliform bacterial concentration from both point and nonpoint sources associated with different landuse types in the watershed. The sensitivity of simulated peak values of in-stream fecal coliform concentrations to changes in parameters associated with the bacterial simulation was evaluated. The hydrology of the watershed was calibrated for a period from January 1, 1990 to December 31, 1993. The model was validated for hydrology for the year of 1995. The simulated peak value of in-stream fecal coliform concentrations was found to be most sensitive to the first order decay constant, the rate of accumulation of fecal coliform on the land surface, the rate of surface runoff that is required to remove 90 percent of fecal coliform from the land surface, the temperature correction coefficient for first order decay rate of fecal coliform, and in-stream water temperature. A First Order Analysis (FOA) was conducted to determine the fraction of the variance of the simulated peak in-stream fecal coliform concentration that can be attributed to the uncertainty in these most sensitive parameters. The FOA indicated that the major portion of the variance in simulated in-stream peak fecal coliform concentration was caused by the variance and sensitivity of the maximum storage of fecal coliform on the pervious land surface. Thus, small errors in parameterizing the maximum storage of fecal coliform over a given landuse class may result in large errors in predicted coliform counts.

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