Parameter Uncertainty Propagation on Streamflow Simulations and Parameter Sensitivity Evaluation of a Lumped Watershed Model: A Case Study

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Abstract
The lumped watershed model, Hydrologic Simulation Program FORTRAN — HSPF, was used to simulate hydrologic processes in the Luxapallila Creek watershed in Mississippi and Alabama. Analysis of parameter uncertainty propagation on streamflow simulations from 12 HSPF parameters was accomplished using 5,000 Monte Carlo random samples. Parameter sensitivity was performed individually using Monte Carlo simulations for each parameter. Triangular distributions were developed for each parameter and the most probable value for each parameter extracted from previous model calibration efforts. Daily simulated certainty bounds were evaluated using two criteria: the percentage of observed flows within the HSPF 90% certainty bounds (Reliability) and the width of the HSPF 90% certainty bounds (Sharpness). Three years of daily observed streamflow data were clustered into three groups to assess the model Reliability and Sharpness by each class: below normal, normal, and above normal flows. In general, the model Reliability was better for below normal flows than normal and above normal flows. Four out of 12 parameters were found to account the majority of parameter uncertainty propagation. Median model Sharpness was reduced by 8% using four parameters instead of 12 parameters while model Reliability decreased just 0.5%.

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