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ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #151619
Title: OPTIMIZING BEST MANAGEMENT PRACTICE SELECTION TO INCREASE COST-EFFECTIVENESS

Author
item GITAU, MARGARET - PENN STATE UNIV.
item Veith, Tameria - Tamie
item Gburek, William

Submitted to: ASAE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 7/27/2003
Publication Date: 7/30/2003
Citation: Gitau, M., Veith, T.L., Gburek, W.J. 2003. Optimizing best management practice selection to increase cost-effectiveness. ASAE Annual International Meeting. Paper # 32110.

Interpretive Summary: It is possible to estimate the extent to which a specific group of best management practices can improve water quality at a watershed outlet. However, it is more complex to select and place best management practices across the watershed in combinations that are both inexpensive and highly effective at reducing pollution. This paper presents a tool for sorting through the possible combinations of best management practices. The water quality improvement and cost for each best management practice combination is estimated. The tool determines which combinations reduce pollution to target levels and cost the least. This tool is important in helping to identify low cost ways of improving water quality.

Technical Abstract: 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 watershed-level 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.