Farmlevel Optimization of BMP Placement for Costeffective Pollution Reduction

With best management practices (BMPs) being used increasingly to control agricultural pollutant losses to surfacewaters, establishing the environmental effectiveness of these practices has become important. Additionally, cost implicationsof establishing and maintaining environmentally effective BMPs are often a crucial factor in selecting and adopting BMPs.This article considers both water quality and economic concerns and presents a methodology developed for determining costeffectivefarm- or watershed-level scenarios through optimization. This optimization technique uniquely incorporates threeexisting tools: a genetic algorithm (GA), a watershed-level nonpoint-source model (Soil and Water Assessment Tool, SWAT),and a BMP tool. The GA combines initial pollutant loadings from SWAT with literature-based pollution reduction efficienciesfrom the BMP tool and with BMP costs to determine cost-effective watershed scenarios. The methodology was successfullyapplied to a 300 ha farm within the Cannonsville Reservoir watershed, a phosphorus (P) restricted reservoir within New YorkCitys water supply system. An average reduction in dissolved P of 60% over the lifetime of the BMPs was set as the pollutanttarget. A baseline scenario was established to represent practices on the farm before BMP implementation. The most costeffectivescenario for the farm, under the presented methodology, achieved a cost-effectiveness of 0.6 kg dissolved P reductionper dollar spent per year. Additionally, the methodology determined alternative scenarios for the farm, which met the pollutionreduction criterion cost-effectively. The methodology, as developed, is extendable to multi-farm or watershed-level evaluations.