Development of a multiobjective optimization tool for the selection and placement of best management practices for nonpoint source pollution control

Abstract

[1] Best management practices (BMPs) are effective in reducing the transport of agricultural nonpoint source pollutants to receiving water bodies. However, selection of BMPs for placement in a watershed requires optimization of the available resources to obtain maximum possible pollution reduction. In this study, an optimization methodology is developed to select and place BMPs in a watershed to provide solutions that are both economically and ecologically effective. This novel approach develops and utilizes a BMP tool, a database that stores the pollution reduction and cost information of different BMPs under consideration. The BMP tool replaces the dynamic linkage of the distributed parameter watershed model during optimization and therefore reduces the computation time considerably. Total pollutant load from the watershed, and net cost increase from the baseline, were the two objective functions minimized during the optimization process. The optimization model, consisting of a multiobjective genetic algorithm (NSGA-II) in combination with a watershed simulation tool (Soil Water and Assessment Tool (SWAT)), was developed and tested for nonpoint source pollution control in the L'Anguille River watershed located in eastern Arkansas. The optimized solutions provided a trade-off between the two objective functions for sediment, phosphorus, and nitrogen reduction. The results indicated that buffer strips were very effective in controlling the nonpoint source pollutants from leaving the croplands. The optimized BMP plans resulted in potential reductions of 33%, 32%, and 13% in sediment, phosphorus, and nitrogen loads, respectively, from the watershed.Citation: Maringanti, C., I. Chaubey, and J. Popp (2009), Development of a multiobjective optimization tool for the selection and placement of best management practices for nonpoint source pollution control, Water Resour. Res., 45, W06406,

Optimizing conservation practices in watersheds: Do community preferences matter?

“…For example, approaches for optimization of spatial distribution of conservation practices and best management practices in agricultural landscape have been investigated by multiple studies, such as Newbold [2002,2005], Kaini et al [2007], Artita et al [2008], Cutter et al [2008], Maringanti et al [2009], and Tilak et al [2011a]. However, the inclusion of sociological factors in the design of optimized combinations of conservation practices in the watershed has been mostly absent in these studies and approaches.…”

“…[8] Similarly, other researchers, such as Bekele and Nicklow [2005], Artita et al [2008], and Maringanti et al [2009], have incorporated economic objectives and criteria along with environmental benefits as part of the optimization of conservation practices. For example, Bekele and Nicklow [2005] studied the effect of different agricultural land uses (i.e., no tillage for row crops) that provide ecosystem services such as sediments, phosphorus and nitrogen reductions in the watershed.…”

“…[9] On the other hand, Maringanti et al [2009] tried to incorporate some aspects of landowner preferences in their optimization approach that used a combination of NSGA-II and the SWAT hydrologic model to optimize multiple best management practices in a watershed. They incorporated landowner preferences by using the records from stakeholders and county agents to identify most popular and commonly adopted BMPs in their watershed sites and then use those BMPs (i.e., nutrient management, buffers, conservation till, and no-till) within the optimization approach.…”

“…One may argue that obtaining socioeconomic data on attitudes and preferences of individual stakeholders toward practices, along with the spatial distribution of decision makers in a watershed is extremely challenging, if not impossible. Hence, many watershed plans are developed based on averaged data on farmer preferences of practices (such as in the approach of Maringanti et al [2009]), obtained from a socioeconomic survey conducted at a particular point in time in the watershed. An underlying assumption is made in such approaches that a survey provides some aggregated view of stakeholder preferences that are sufficient to identify which practices will be adopted by the community.…”

“…[14] Three are the main objectives of this study: (a) how landowner tenure and attitudes of farming communities affect the preference of individual conservation practices in agricultural watersheds, (b) how spatial distribution of landowner tenure affects the spatial optimization of conservation practices on a watershed scale, and (c) how underlying land tenures and farmer attitudes can modify the effectiveness of alternatives obtained via classic optimization approaches that do not include existing social attitudes in typical optimization approaches (such as those undertaken by Newbold [2002Newbold [ , 2005, Kaini et al [2007], Artita et al [2008], Cutter et al [2008], Maringanti et al [2009], andTilak et al [2011a]). The following sections describe the methodology comprised of the case study, the hydrologic and water quality model, the optimization formulation, and the different experiments performed.…”