Optimizing Best Management Practice Selection to Increase Cost-effectiveness

With Best Management Practices (BMPs) being used increasingly to control losses of major agricultural pollutants to surface waters, establishing the effectiveness of these practices has become important. A methodology was developed for determining cost-effective watershed scenarios. This technique combines three existing tools: a genetic algorithm (GA), a watershedlevel nonpoint source model (Soil and Water Assessment Tool, SWAT), and a BMP assessment tool. The GA combines initial pollutant loadings from SWAT with literature-based pollution reduction efficiencies provided by the assessment tool and BMP costs appropriate to the study area to determine cost-effective watershed scenarios. The methodology was successfully applied to a 300-ha farm within the Cannonsville Reservoir watershed in New York. The Cannonsville Reservoir is phosphorous (P) restricted, and planners are implementing BMPs to reduce P loading to the reservoir. The optimal scenario for the farm, under the presented methodology, achieved a cost-effectiveness of 0.6 kg dissolved P reduction per dollar spent. Additionally, the methodology determined alternative scenarios which met the pollution reduction criteria cost-effectively.