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The Water Erosion Prediction Project (WEPP) was used to predict event-based sediment yield and runoff for rainfall experiments on six stream-crossing approaches with different intensities of best management practice (BMP) implementation (i.e., different proportions of gravel on the road surface). WEPP was calibrated for three different BMP intensities at each site using a Markov chain Monte Carlo approach to explore parameter uncertainty and prediction performance. WEPP predictions of sediment yield showed clear differences among the different road surface treatments, but prediction intervals (or the range of possible simulation results) were wide, reflecting substantial parameter and prediction uncertainty. The posterior distribution analysis for rill erodibility, interrill erodibility, and critical shear indicated that we cannot recommend parameter ranges specific to different surface treatments. Results suggest that the utility of WEPP for estimating BMP effectiveness is limited to predicting relative differences in sediment yield among vastly different surface treatments (e.g., native surfaced versus completely graveled roads). Sediment predictions from models should always include information regarding the range of possible outcomes, given the many sources of uncertainty.

Can the Water Erosion Prediction Project Model Be Used to Estimate Best Management Practice Effectiveness from Forest Roads?