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ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #144398
Title: DEVELOPMENT OF OPTIMIZATION PROCEDURE FOR COST-EFFECTIVE BMP PLACEMENT

Author
item Veith, Tameria - Tamie
item WOLFE, MARY - VIRGINIA TECH
item HEATWOLE, CONRAD - VIRGINIA TECH

Submitted to: Journal of the American Water Resources Association
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/22/2003
Publication Date: 12/20/2003
Citation: Veith, T.L., Wolfe, M.L., Heatwole, C.D. 2003. Development of optimization procedure for cost-effective BMP placement. Journal of the American Water Resources Association. 39(6):1331-1343

Interpretive Summary: Current methods to improve water quality in agricultural watersheds do not also focus on minimizing associated costs. A procedure was developed to identify watershed management plans that meet water quality improvement criteria at the least possible cost. For two watersheds the procedure identified multiple solutions that meet the desired pollution reduction criteria while reducing costs and, in doing so, provided an indication of which fields and which management techniques may have a more critical impact on overall cost-effectiveness. The optimization procedure could aid watershed planners in meeting pollution reduction criteria in a more cost-effective way while still allowing farmers flexibility in their management practices.

Technical Abstract: A combinatorial optimization procedure for best management practice (BMP) placement at the watershed level was developed. This procedure facilitates selection of cost-effective BMP scenarios to control nonpoint source (NPS) pollution. A genetic algorithm (GA) was selected from among several optimization heuristics. The GA combines an optimization component written in the C++ language with spatially variable NPS pollution prediction and economic analysis components written within the ArcView geographic information system. The procedure is modular in design, allowing for component modifications while maintaining the basic conceptual framework. An objective function was developed to lexicographically optimize pollution reduction followed by cost increase. Scenario cost-effectiveness can then be calculated for scenario comparisons. The NPS pollutant fitness score allows for evaluation of multiple pollutants, based on prioritization of each pollutant. The economic component considers farm-level public and private costs, cost distribution, and land area requirements. Development of a sediment transport function, used with the Universal Soil Loss Equation, allows the optimization procedure to run within a reasonable timeframe. The procedure identifies multiple near optimal solutions, providing an indication of which fields have a more critical impact on overall cost-effectiveness and flexibility in the final solution selected for implementation. The procedure was demonstrated for two watersheds.