ANALYSIS OF THE HSPF WATER QUALITY PARAMETER UNCERTAINTY IN PREDICTING PEAK IN-STREAM FECAL COLIFORM CONCENTRATIONS

Abstract

Salado Creek in Bexar County, Texas, is one of 65 streams listed in section 303(d) of the Clean Water Act as an impaired waterbody for its high concentration of fecal coliform bacteria. The Hydrological Simulation Program-FORTRAN (HSPF) in Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) 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 land use 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 a period from January 1, 1994, to December 31, 1996. 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% of fecal coliform from the land surface, the temperature correction coefficient for the 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 five 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 land use class may result in large errors in predicted coliform counts.