ABSTRACT:Since the trend in infiltration modeling is currently toward process‐based approaches such as the Green‐Ampt equation, more emphasis is being placed on methods of determining appropriate parameters for this approach. The SCS curve number method is an accepted and commonly used empirical approach for estimating surface runoff, and is based on numerous data from a variety of sources. The time and expense of calibrating process‐based infiltration parameters to measured data are often prohibitive. This study uses curve number predictions of runoff to develop equations to estimate the “baseline” hydraulic conductivities (Kb) for use in the Green‐Ampt equation. Curve number predictions of runoff were made for 43 soils. Kbvalues in the Water Erosion Prediction Project (WEPP) model were then calibrated so that the annual runoff predicted by WEPP was equal to the curve number predictions. These calibrated values were used to derive an equation that estimated Kbbased on the percent sand, percent clay, and cation exchange capacity of the soil. Estimated values of Kbfrom this equation compared favorably with measured values and values calibrated to measured natural runoff plot data. WEPP predictions of runoff using both optimized and estimated values of Kbwere compared to curve number predictions of runoff and the measured values. The WEPP predictions using the optimized values of Kbwere the best in terms of both average error and model efficiency. WEPP predictions using estimated values of Kbwere shown to be superior to predictions obtained from the curve number method. The runoff predictions all tended to be biased high for small events and low for larger events when compared to the measured data. Confidence intervals for runoff predictions on both an annual and event basis were also developed for the
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