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Int. J. Environ. Res. Public Health 2014, 11(3), 2992-3014; doi:10.3390/ijerph110302992
Article

Comparing the Selection and Placement of Best Management Practices in Improving Water Quality Using a Multiobjective Optimization and Targeting Method

1
, 2,* , 3
 and 1
1 Department of Civil and Disaster Prevention Engineering, National United University, Miaoli 36003, Taiwan 2 Department of Earth, Atmospheric, and Planetary Sciences, Department of Agricultural and Biological Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, USA 3 Risk Modeling Unit, Zurich Financial Services Ltd., Mythenquai 2, Zurich 8002, Switzerland
* Author to whom correspondence should be addressed.
Received: 16 December 2013 / Revised: 3 March 2014 / Accepted: 3 March 2014 / Published: 11 March 2014
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Abstract

Suites of Best Management Practices (BMPs) are usually selected to be economically and environmentally efficient in reducing nonpoint source (NPS) pollutants from agricultural areas in a watershed. The objective of this research was to compare the selection and placement of BMPs in a pasture-dominated watershed using multiobjective optimization and targeting methods. Two objective functions were used in the optimization process, which minimize pollutant losses and the BMP placement areas. The optimization tool was an integration of a multi-objective genetic algorithm (GA) and a watershed model (Soil and Water Assessment Tool—SWAT). For the targeting method, an optimum BMP option was implemented in critical areas in the watershed that contribute the greatest pollutant losses. A total of 171 BMP combinations, which consist of grazing management, vegetated filter strips (VFS), and poultry litter applications were considered. The results showed that the optimization is less effective when vegetated filter strips (VFS) are not considered, and it requires much longer computation times than the targeting method to search for optimum BMPs. Although the targeting method is effective in selecting and placing an optimum BMP, larger areas are needed for BMP implementation to achieve the same pollutant reductions as the optimization method.
Keywords: best management practice; nonpoint source pollution; multiobjective optimization; genetic algorithm; Soil and Water Assessment Tool best management practice; nonpoint source pollution; multiobjective optimization; genetic algorithm; Soil and Water Assessment Tool
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Chiang, L.-C.; Chaubey, I.; Maringanti, C.; Huang, T. Comparing the Selection and Placement of Best Management Practices in Improving Water Quality Using a Multiobjective Optimization and Targeting Method. Int. J. Environ. Res. Public Health 2014, 11, 2992-3014.

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