Application of Tabu search algorithm with a coupled AnnAGNPS-CCHE1D model to optimize agricultural land use. J Am Water Resour Assoc (AWRA)

JAWRA Journal of the American Water Resources Association (Impact Factor: 1.35). 07/2008; 44(4):866 - 878. DOI: 10.1111/j.1752-1688.2008.00209.x

ABSTRACT

  A principal contributor to soil erosion and nonpoint source pollution, agricultural activities have a major influence on the environmental quality of a watershed. Impact of agricultural activities on the quality of water resources can be minimized by implementing suitable agriculture land-use types. Currently, land uses are designed (location, type, and operational schedule) based on field study results, and do not involve a science-based approach to ensure their efficiency under particular regional, climatic, geological, and economical conditions. At present, there is a real need for new methodologies that can optimize the selection, design, and operation of agricultural land uses at the watershed scale by taking into account environmental, technical, and economical considerations, based on realistic simulations of watershed response. In this respect, the present study proposes a new approach, which integrates computational modeling of watershed processes, fluvial processes in the drainage network, and modern heuristic optimization techniques to design cost effective land-use plans. The watershed model AnnAGNPS and the channel network model CCHE1D are linked together to simulate the sediment and pollutant transport processes. Based on the computational results, a multi-objective function is set up to minimize soil losses, nutrient yields, and total associated costs, while the production profits from agriculture are maximized. The selected iterative optimization algorithm uses adaptive Tabu Search heuristic to flip (switching from one alternative to another) land-change variables. USDA’s Goodwin Creek experimental watershed, located in Northern Mississippi, is used to demonstrate the capabilities of the proposed approach. The results show that the optimized land-use design with BMPs using an integrated approach at the watershed level can provide efficient and cost-effective conservation of the environmental quality by taking into account both productivity and profitability.

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Available from: Mustafa S. Altinakar
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    • "However, the previously mentioned literatures all focus on optimization of land use and BMP on particularly based case study without providing a general framework to allow various stakeholder's participations and land owner's preferences in the process. The major optimization method used was based GA, which could lead to only local optima solutions (Qi et al., 2008). Developing a new Multi-Objective Decision Making (MODM) framework for land use planning comes from the notion of Problem Solving Environment (PSE), which is an active area of research in computer science. "
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    ABSTRACT: Land use planning is an important element of the integrated watershed management approach. It not only influences the environmental processes such as soil and stream bed erosion, sediment and nutrient concentrations in streams, quality of surface and ground waters in a watershed, but also affects social and economic development in that region. Although its importance in achieving sustainable development has long been recognized, a land use planning methodology based on a systems approach involving realistic computational modeling and meta-heuristic optimization is still lacking in the current practice of integrated watershed management. The present study proposes a new approach which attempts to combine computational modeling of upland watershed processes, fluvial processes and modern heuristic optimization techniques to address the water-land use interrelationship in its full complexity. The best land use allocation is decided by a multi-objective function that minimizes sediment yields and nutrient concentrations as well as the total operation/implementation cost, while the water quality and the production benefits from agricultural exploitation are maximized. The proposed optimization strategy considers also the preferences of land owners. The runoff model AnnAGNPS (developed by USDA), and the channel network model CCHE1D (developed by NCCHE), are linked together to simulate sediment/pollutant transport process at watershed scale based on any assigned land use combination. The greedy randomized adaptive Tabu search heuristic is used to flip the land use options for finding an optimum combination of land use allocations. The approach is demonstrated by applying it to a demonstrative case study involving USDA Goodwin Creek experimental watershed located in northern Mississippi. The results show the improvement of the tradeoff between benefits and costs for the watershed, after implementing the proposed optimal land use planning.
    Full-text · Article · Jan 2011 · Journal of Environmental Management
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    • "Unlike GA which is " population based " approach, TS incorporates the idea of responsive search of the solution domain. GA approaches are predicated on the idea of randomly choosing parents to produce offspring, and further introduce randomization to determine which components of the parents should be combined (Qi et al. 2008). By contrast, the TS approach does not emphasize randomization, particularly in the sense of being indifferent to choices among alternatives. "
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    ABSTRACT: Management of agriculture-induced water quality problems requires an integrated approach involving selection of the most suitable and economical Best Management Practices (BMP). Vegetation Buffer Strips (VBS), one of the commonly used off-field structural BMPs, when designed and placed correctly, can significantly improve the water quality. However, VBS takes up agricultural land used for crop production and the implementation/maintenance costs are of concern. Currently, the standards for design of VBS (location and width) are normally set on field study basis, and they do not involve science-based approach to guarantee their efficiency under regional variations, geological and economical conditions. The present study proposes a new approach which integrates computational modeling of watershed processes, fluvial processes and modern heuristic optimization techniques to design a cost effective VBSs in a watershed. The watershed model AnnAGNPS (Annual AGricultural Non-Point Source Pollution Model) and channel network model CCHE1D (Center for Computational Hydroscience and Engineering One(1) Dimensional Model) are linked together to simulate the sediment/pollutant transport processes. Based on the computational results, a multi-objective function is set up, which aims to minimize soil losses, nutrient concentrations as well as total costs associated with installation and maintenance of VBS, while the production profits from agriculture production are being maximized. The solution procedure involves the use of iterative Tabu Search (TS) algorithm to flip VBS design parameters (switching from one alternative to another). The search for the optimal solution follows an iterative procedure. An illustrative case study of USDA’s Goodwin Creek experimental watershed located in Northern Mississippi is used to demonstrate the capabilities of the proposed approach. The results show that the optimized design of VBS using an integrated approach at the watershed level can provide efficient and cost-effective conservation of the environmental quality by taking into account productivity and profitability.
    Full-text · Article · Jan 2011 · Water Resources Management
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    ABSTRACT: A critical review of the peer-reviewed literature published in 2008 on topics related to nonpoint source pollution (NPS) is presented. This review is divided into three sections: sources of NPS pollution, modeling of NPS pollution, and NPS control strategies.
    Full-text · Article · Sep 2009 · Water Environment Research
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