SOIL EROSION AND SEDIMENT YIELD PREDICTION ACCURACY USING WEPP1

ABSTRACT: The objectives of this paper are to discuss expectations for the Water Erosion Prediction Project (WEPP) accuracy, to review published studies related to WEPP goodness of fit, and to evaluate these in the context of expectations for WEPP's goodness of fit. WEPP model erosion predictions have been compared in numerous studies to observed values for soil loss and sediment delivery from cropland plots, forest roads, irrigated lands and small watersheds. A number of different techniques for evaluating WEPP have been used, including one recently developed where the ability of WEPP to accurately predict soil erosion can be compared to the accuracy of replicated plots to predict soil erosion. In one study involving 1,594 years of data from runoff plots, WEPP performed similarly to the Universal Soil Loss Erosion (USLE) technology, indicating that WEPP has met the criteria of results being “at least as good with respect to observed data and known relationships as those from the USLE,” particularly when the USLE technology was developed using relationships derived from that data set, and using soil erodibility values measured on those plots using data sets from the same period of record. In many cases, WEPP performed as well as could be expected, based on comparisons with the variability in replicate data sets. One major finding has been that soil erodibility values calculated using the technology in WEPP for rainfall conditions may not be suitable for furrow irrigated conditions. WEPP was found to represent the major storms that account for high percentages of soil loss quite well—a single storm application that the USLE technology is unsuitable for—and WEPP has performed well for disturbed forests and forest roads. WEPP has been able to reflect the extremes of soil loss, being quite responsive to the wide differences in cropping, tillage, and other forms of management, one of the requirements for WEPP validation. WEPP was also found to perform well on a wide range of small watersheds, an area where USLE technology cannot be used.     

USING CURVE NUMBERS TO DETERMINE BASELINE VALUES OF GREEN-AMPT EFFECTIVE HYDRAULIC CONDUCTIVITIES1

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 (K_b) for use in the Green-Ampt equation. Curve number predictions of runoff were made for 43 soils. K_b values 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 K_b based on the percent sand, percent clay, and cation exchange capacity of the soil. Estimated values of K_b from 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 K_b were compared to curve number predictions of runoff and the measured values. The WEPP predictions using the optimized values of K_b were the best in terms of both average error and model efficiency. WEPP predictions using estimated values of K_b were 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 WEPP model.