Abstract
The uncertainty on model predictions to evaluate river water quality is often high to delineate appropriate conclusions. This study presents the statistical evaluation of the water quality modeling system Hydrologic Simulation Program FORTRAN as a tool to improve monitoring planning and mitigate uncertainty in water quality predictions. It also presents findings in determining HSPF model’s sensitivity analysis concerning water quality predictions. The computer model was applied to Ave River watershed, Portugal. The hydrology was calibrated at two stations from January 1990 to December 1994 and validated from January 1995 to December 1999. A two-step statistical evaluation framework is presented based on the most common hydrology criteria for model calibration and validation and, a Monte Carlo methodology uncertainty evaluation approach coupled with multi parametric sensitivity analyses to assess model uncertainty and parameter sensitivity. Fourteen HSPF water quality parameters probability distributions are used as input factors for the Monte Carlo simulation. The simulation results for in stream fecal coliform concentrations was found to be most sensitive to parameters that represent first order decay rate and surface runoff that removes 90 percent of fecal coliform from pervious land surface rather than accumulation and maximum storage rates. Regarding oxygen governing process (DO, BOD, NO3, PO4), benthal oxygen demand and nitrification/denitrification rates were the most sensitive parameters.
Applying Monte Carlo and classification tree sensitivity analysis to the Zayandehrood River
