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- W2286928102 abstract "Targeting is the practice of locating best management practices (BMPs) where non-pointsource pollution control will be most cost-effective. While targeting should reduce thenumber of interventions needed in a watershed, BMPs are often applied to all areas satisfyingtargeting criteria. The research goal was to increase, relative to uniform targeting recommen-dations,BMP cost-effectiveness within a watershed. A genetic algorithm (GA) optimizationstrategy was developed to select, in a two-step method, the most cost-effective combination ofmanagement practices. First, the optimal solution must meet user-identified pollutant reductioncriteria. Second, of all solutions meeting these criteria, the least-cost solution is preferred.The strategy was demonstrated on a 686-ha watershed in Rockingham County, Virginia for apollution load target of 8.96 Mg/ha, the soil loss tolerance of the majority of the area. The steadystate GA was run for 200 generations with a population size of 50 under three replacementlevels: 10%, 25%, and 50%. The 50% strategy performed best, converging within 163 genera-tionsto a fitness score of 1.71 out of 2 and achieving a cost-effectiveness of 0.0914 Mg/$.Given the computational speed with which the 25 and 50% replacement levels converged,application of this strategy to larger or more complex watersheds is potentially feasible. Futuretesting will include sensitivity analysis of different GA parameters." @default.
- W2286928102 created "2016-06-24" @default.
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- W2286928102 date "2001-01-01" @default.
- W2286928102 modified "2023-09-26" @default.
- W2286928102 title "Watershed Level Optimization of BMP Placement for Cost-effective NPS Pollution Reduction" @default.
- W2286928102 doi "https://doi.org/10.13031/2013.5528" @default.
- W2286928102 hasPublicationYear "2001" @default.
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