EVALUATION OF ANNAGNPS ON MISSISSIPPI DELTA MSEA WATERSHEDS

Abstract

Sediment and its associated pollutants entering a water body can be very destructive to the health of that system.Best Management Practices (BMPs) can be used to reduce these pollutants, but understanding the most effective practicesis very difficult. Watershed models are the most costeffective tools to aid in the decisionmaking process of selecting the BMPthat is most effective in reducing the pollutant loadings. The Annualized Agricultural NonPoint Source Pollutant Loadingmodel (AnnAGNPS) is one such tool. The objectives of this study were to assemble all necessary data from the MississippiDelta Management System Evaluation Area (MDMSEA) Deep Hollow watershed to validate AnnAGNPS, and to use thevalidated AnnAGNPS to evaluate the effectiveness of BMPs for sediment reduction.In this study, AnnAGNPS predictions were compared with three years of field observations from the MDMSEA DeepHollow watershed. Using no calibrated parameters, AnnAGNPS underestimated observed runoff for extreme events, but therelationship between simulated and observed runoff on an event basis was significant (R2 = 0.9). In contrast, the lower R2of 0.5 for event comparison of predicted and observed sediment yields demonstrated that the model was not best suited forshortterm individual event sediment prediction. This may be due to the use of Revised Universal Soil Loss Equation (RUSLE)within AnnAGNPS, and parameters associated with determining soil loss were derived from longterm average annual soilloss estimates. The agreement between monthly average predicted sediment yield and monthly average observed sedimentyield had an R2 of 0.7. Threeyear predicted total runoff was 89% of observed total runoff, and threeyear predicted totalsediment yield was 104% of observed total sediment yield. Alternative scenario simulations showed that winter cover cropsand impoundments are promising BMPs for sediment reduction.