HYDROLOGIC SIMULATION ON AGRICULTURAL WATERSHEDS: CHOOSING BETWEEN TWO MODELS

摘要

Strengths and limitations of hydrologic simulation models are used as criteria for selecting a particular model for a given water resources application. The performance of the Soil and Water Assessment Tool (SWAT) and the Hydrologic Simulation Program-Fortran (HSPF) continuous simulation models was compared on eight nested agricultural watersheds within the Little Washita River Experimental Watershed (LWREW) and two agricultural watersheds adjacent to the LWREW within the Washita River Basin in southwestern Oklahoma. Two subwatersheds within the LWREW were first used to calibrate parameters in both models for a “wetter than average” period of record. Both models were then applied to six other subwatersheds within the LWREW and the two adjacent watersheds, under varying climatic conditions. Three quantitative and two qualitative evaluation criteria were used to assess streamflow simulated by SWAT and HSPF: computation of (1) deviation of streamflow volume, (2) coefficient of efficiency, and (3) prediction efficiency and visual inspection of (4) hydrographs and (5) flow duration curves. A comparison of model performance showed that while HSPF performed better on the watersheds used for calibration, SWAT gave better results on the validation watersheds. On one of the validation subwatersheds adjacent to the LWREW, values of deviation of streamflow volume were -38.7%, -13.3%, and -1.3% for SWAT and -64.3%, -81.1%, and -8.2% for HSPF under “much dryer than average,” “dryer than average,” and “near average” climatic conditions, respectively. Differences in model performance were mainly attributed to the runoff production mechanism in the two models. Results of this study showed that SWAT exhibited an element of robustness in that it gave more consistent results than HSPF in estimating streamflow for agricultural watersheds under various climatic conditions. SWAT may therefore be better suited for investigating the long-term impacts of climate variability on surface-water resources