Best Management Practice Effects for Phosphorus Control on a Dairy Farm: The Cannonsville Reservoir Watershed, New York
Gitau, M.W., Gburek, W.J.
Best Management Practices (BMPs) have been implemented on a farm-by-farm basis within the Cannonsville Reservoir Watershed (CRW), as part of a New York City watershed-wide BMP implementation effort to reduce phosphorus (P) losses to the water supply reservoirs. Monitoring studies have been carried out at selected locations and at the watershed outlet on one of the farms which spans an entire sub-watershed within the CRW, with the aim of quantifying effectiveness of the BMPs installed on the farm. This study applied the Soil and Water Assessment Tool (SWAT) and a recently developed BMP characterization tool to the farm over pre- and post- BMP installation periods with a view to determining the extent to which model results incorporating all installed BMPs match observed data, and the individual impact of each of the BMPs installed on the farm. The SWAT model generally performed well at the watershed level, with annual Nash-Sutcliffe coefficients ranging between 0.56 and 0.80 and monthly coefficients ranging between 0.45 and 0.78. The model also performed well at the field level, with simulated in-field P losses closely matching observed data. Because BMPs were included in the model as part of the input data, it was difficult to separate out individual BMP impacts based on SWAT simulations. It was, however, possible to determine the effects of BMP combinations such as nutrient management plans and rotations (31% dissolved P; 25% total P). For dissolved P, integration of BMP tool efficiencies allowed individual BMP impacts to be incorporated while still maintaining the same level of representation as was obtained using model simulations. As the SWAT model is often used with little or no post-BMP data to verify simulation results, this study served to validate SWAT model suitability for evaluating BMP impacts. The BMP tool was found to suitably complement the model by providing insights into individual BMP impacts, and providing BMP efficiency data where the model was lacking.