National Center for Computational Hydroscience and Engineering, The University of Mississippi, University, MS 38677, USA.
J Environ Manage. 2011 Jan;92(1):149-55. doi: 10.1016/j.jenvman.2010.08.023. Epub 2010 Sep 22.
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.
土地利用规划是综合流域管理方法的一个重要组成部分。它不仅影响土壤和河床侵蚀、溪流中泥沙和养分浓度、地表和地下水质量等环境过程，还影响该地区的社会和经济发展。尽管其在实现可持续发展方面的重要性早已得到认可，但在综合流域管理的当前实践中，仍然缺乏基于系统方法的土地利用规划方法，该方法涉及现实的计算建模和元启发式优化。本研究提出了一种新方法，试图将旱地流域过程、河流过程和现代启发式优化技术的计算建模相结合，以充分复杂的方式解决水-土地利用相互关系。最佳土地利用分配由一个多目标函数决定，该函数最小化泥沙产量和养分浓度以及总运营/实施成本，同时最大化农业开发的水质和生产效益。所提出的优化策略还考虑了土地所有者的偏好。径流模型 AnnAGNPS（由 USDA 开发）和河道网络模型 CCHE1D（由 NCCHE 开发）被链接在一起，根据任何指定的土地利用组合，模拟流域尺度上的泥沙/污染物输移过程。贪婪随机自适应禁忌搜索启发式用于翻转土地利用选项，以找到土地利用分配的最佳组合。该方法通过将其应用于涉及美国农业部古德温溪实验流域的示范案例研究来证明，该流域位于密西西比州北部。结果表明，在实施拟议的最优土地利用规划后，流域的效益和成本之间的权衡得到了改善。
