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

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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.

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          The Role of Riparian Corridors in Maintaining Regional Biodiversity

          Riparian corridors possess an unusually diverse array of species and environmental processes. This "ecological" diversity is related to variable flood regimes, geomorphic channel processes, altitudinal climate shifts, and upland influences on the fluvial corridor. This dynamic environment results in a variety of life history strategies, and a diversity of biogeochemical cycles and rates, as organisms adapt to disturbance regimes over broad spatio-temporal scales. These facts suggest that effective riparian management could ameliorate many ecological issues related to land use and environmental quality. We contend that riparian corridors should play an essential role in water and landscape planning, in the restoration of aquatic systems, and in catalyzing institutional and societal cooperation for these efforts.
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            Differences in phosphorus and nitrogen delivery to the Gulf of Mexico from the Mississippi River Basin.

            Seasonal hypoxia in the northern Gulf of Mexico has been linked to increased nitrogen fluxes from the Mississippi and Atchafalaya River Basins, though recent evidence shows that phosphorus also influences productivity in the Gulf. We developed a spatially explicit and structurally detailed SPARROW water-quality model that reveals important differences in the sources and transport processes that control nitrogen (N) and phosphorus (P) delivery to the Gulf. Our model simulations indicate that agricultural sources in the watersheds contribute more than 70% of the delivered N and P. However, corn and soybean cultivation is the largest contributor of N (52%), followed by atmospheric deposition sources (16%); whereas P originates primarily from animal manure on pasture and rangelands (37%), followed by corn and soybeans (25%), other crops (18%), and urban sources (12%). The fraction of in-stream P and N load delivered to the Gulf increases with stream size, but reservoir trapping of P causes large local- and regional-scale differences in delivery. Our results indicate the diversity of management approaches required to achieve efficient control of nutrient loads to the Gulf. These include recognition of important differences in the agricultural sources of N and P, the role of atmospheric N, attention to P sources downstream from reservoirs, and better control of both N and P in close proximity to large rivers.
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              SENSITIVITY ANALYSIS, CALIBRATION, AND VALIDATIONS FOR A MULTISITE AND MULTIVARIABLE SWAT MODEL

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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                11 March 2014
                March 2014
                : 11
                : 3
                : 2992-3014
                Affiliations
                [1 ]Department of Civil and Disaster Prevention Engineering, National United University, Miaoli 36003, Taiwan; E-Mails: lchiang@ 123456nuu.edu.tw (L.-C.C.); r99622021@ 123456ntu.edu.tw (T.H.)
                [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; E-Mail: ichaubey@ 123456purdue.edu
                [3 ]Risk Modeling Unit, Zurich Financial Services Ltd., Mythenquai 2, Zurich 8002, Switzerland; E-Mail: chetan.maringanti@ 123456zurich.com
                Author notes
                [* ] Author to whom correspondence should be addressed; E-Mail: ichaubey@ 123456purdue.edu ; Tel.: +1-765-494-3258; Fax: +1-765-496-1210.
                Article
                ijerph-11-02992
                10.3390/ijerph110302992
                3987017
                24619160
                c60c8e29-2d8c-4dd4-a858-a61871daba91
                © 2014 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 16 December 2013
                : 03 March 2014
                : 03 March 2014
                Categories
                Article

                Public health
                best management practice,nonpoint source pollution,multiobjective optimization,genetic algorithm,soil and water assessment tool

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