FARM-LEVEL OPTIMIZATION OF BMP PLACEMENT FOR COST-EFFECTIVE POLLUTION REDUCTION.

With best management practices (BMPs) being used increasingly to control agricultural pollutant losses to surface waters, establishing the environmental effectiveness of these practices has become important. Additionally; cost implications of 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 cost-effective farm- or watershed-level scenarios through optimization. This optimization technique uniquely, incorporates three existing 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 efficiencies from the BMP tool and with BMP costs to determine cost-effective watershed scenarios. The methodology was successfully applied to a 300 ha farm within the Cannonsville Reservoir watershed, a phosphorus (P) restricted reservoir within New York City's water supply system. An average reduction in dissolved P of 60% over the lifetime of the BMPs was set as the pollutant target. A baseline scenario was established to represent practices on the farm before BMP implementation. The most cost-effective scenario for the farm, under the presented methodology, achieved a cost-effectiveness of 0.6 kg dissolved P reduction per dollar spent per year. Additionally, the methodology determined alternative scenarios for the farm, which met the pollution reduction criterion cost-effectively. The methodology, as developed, is extendable to multi-farm or watershed-level evaluations. [ABSTRACT FROM AUTHOR]