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Cost-effectiveness analysis of different watershed management scenarios developed by simulation–optimization model

机译:仿真优化模型开发的不同流域管理场景的成本效益分析

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>The effort to control sediment yield at watershed scale is an ongoing challenge that needs to take into account trade-offs between two conflicting objective functions, i.e. economic and hydrologic criteria. Therefore, researchers have coupled hydrologic and multi-objective optimization models to find Pareto-optimal solutions. However, very limited studies have been conducted to analyse the cost-effectiveness (C/E) of scenarios obtained in the Pareto-front optimal. This could provide new information leading to effective watershed management. Therefore, in the present study, the Soil and Water Assessment Tool (SWAT) was used to simulate sediment yield under different combinations of best management practices (BMPs) and was coupled with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The model attends to providing the Pareto-optimal solutions by minimizing the costs of BMPs and maximizing sediment reduction. The results of the application of the cost-effective optimization model in Mehran watershed, Iran, showed that the solutions in the Pareto-optimal front reduce sediment yield between 2% and 40.5% from baseline at costs of between $6,500 and $72,100, respectively. Finally, comparison of four sediment reduction solutions (i.e. 10%, 20%, 30%, and 40%) showed that the total cost and C/E ratio of solutions increased as the sediment reduction criteria increased.
机译:>在流域规模控制沉积物产量的努力是一个持续的挑战,需要考虑两个相互矛盾的客观职能之间的权衡,即经济和水文标准。因此,研究人员已经耦合了水文和多目标优化模型,以找到帕累托最佳解决方案。然而,已经进行了非常有限的研究,以分析帕累托 - 前面最佳中获得的场景的成本效益(C / e)。这可以提供导致有效分水岭管理的新信息。因此,在本研究中,土壤和水评估工具(SWAT)用于在最佳管理实践(BMPS)的不同组合下模拟沉积物产量,并与非主导的分选遗传算法(NSGA-II)偶联。该模型通过最小化BMP的成本和最大化沉积物减少来提供帕累托最佳解决方案。在伊朗梅兰流域的经济高效优化模型中申请的结果表明,帕累托 - 最佳前线的溶液将沉积物产量降低2%至40.5%的基线,分别为6,500美元至72,100美元。最后,四种沉积物还原溶液的比较(即10%,20%,30%和40%)表明,随着沉积物减少标准的增加,溶液的总成本和C / E比增加。

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