Bijay Kumar Pokhrel Louisiana State University, Baton Rouge, USA
Nonpoint source (NPS) pollution is one of the major sources of water pollution in the United States. Pollution from agriculture sources primarily from fertilizer and manure applications has been contributing substantial amount of nutrient pollution in water bodies. Critical source area (CSA) is the area which contributes the utmost amounts of pollutants in water bodies from sub-watershed level is primarily important for implementing the cost-effective BMPs. Several watersheds models are available to identify CSA. Various papers pointed out SWAT model perform better because it uses Modified Universal Soil Loss Equation (MUSLE) for soil erosion, which improves the prediction accuracy and uses runoff volume and peak flow rate to simulate sediment erosion and yields. Realizing this fact, SWAT model is used in this research.
Adoption of Best Management Practices (BMPs) in the CSA can potentially help to reduce pollutants in the water bodies. However, identification of CSA and adoption of optimal BMPs within the CSA are a challenging part. The objective of this study is to identify these areas by implementing sediment and nutrients output of SWAT to reduce nonpoint source pollution and Implement various BMPs on the CSAs to evaluate its cost effectiveness. SWAT is a semi-distributed watershed model that was primarily developed to predict the impact of land management practices on water, sediment, and agricultural chemical yields. For this research work, a Saline Bayou (HUC 11140208) (Fig.1) is selected which is located in the north-western part of Louisiana and predominated by poultry forms. This watershed is shared with Bienville and Lincoln Parishes. Model is calibrated and validated for discharge and sediment for monthly time step. Due to the limited BMPs implementation option in the SWAT model, we utilized MAPSHED model for BMPs analysis which is an open source biophysical simulation model developed by Penn State University. Analysis shows that phosphorus level which is a prime source of pollution can be reduced substantially by adopting of different BMPs combinations with least cost.
Key words – BMP, SWAT, CSA, MAPSHED.