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首页> 外文期刊>The Science of the Total Environment >Optimizing water resources allocation and soil salinity control for supporting agricultural and environmental sustainable development in Central Asia
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Optimizing water resources allocation and soil salinity control for supporting agricultural and environmental sustainable development in Central Asia

机译:优化水资源配置和土壤盐度控制,以支持中亚农业环境可持续发展

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In this study, a stochastic-fuzzy-based fractional programming (SFFP) method is advanced for optimizing water-resources allocation and soil-salinity control under uncertainty. The developed method can address ratio objective optimization problems of complex system in association with stochastic and fuzzy uncertainties, which can help gain in-depth analysis of the interrelationships between marginal effectiveness and system reliability. Then, SFFP is applied to an irrigation region in the lower reach of Amu Darya River basin, where linear crop yield-salinity functions and salt-leaching functions are introduced into the modeling formulation for reflecting the complicated interactions among water resources, soil salinity, arable land, and electricity supply. Solutions under 96 scenarios related to different irrigation efficiencies, water availabilities, and electricity supplies have been obtained. Our findings are: i) increased water availability, electricity supply, and irrigation efficiency result in high marginal benefit; ii) irrigation efficiency is the key factor influencing water allocation patterns for crop irrigation and salt-leaching, promotion of which can facilitate mitigating economic and environmental losses in the water-deficit and soil-salinized region; iii) leaching water allocation patterns for soil-salinity washing is related to salinity characters of crops and regions, and boosting drought- and salt-tolerance crop can be effective in adaption to risks of water scarcity and land salinization. Compared to the conventional approaches, SFFP can generate more flexible alternatives and achieve higher marginal effectiveness. These findings can provide effective decision support to identify desired water management strategies under multiple uncertainties for supporting agricultural sustainability in arid regions.
机译:在本研究中,基于随机模糊的分数编程(SFFP)方法是为了在不确定性下优化水资源配置和土壤 - 盐度控制。开发方法可以解决与随机和模糊不确定性相关的复杂系统的比率客观优化问题,这有助于深入分析边际有效性和系统可靠性之间的相互关系。然后,SFFP应用于AMU Darya河流域下游的灌溉区,其中线性作物产量 - 盐度函数和盐浸出功能被引入模拟配方中,以反映水资源,土壤盐度,耕种的复杂相互作用土地和电力供应。已经获得了与不同灌溉效率,水可用性和电力相关的96个方案的解决方案。我们的研究结果是:i)增加水供应,电力供应和灌溉效率,导致高边缘效益; ii)灌溉效率是影响作物灌溉和盐浸出的水分配模式的关键因素,推广,可以促进水资源 - 赤字和土壤盐渍地区的经济和环境损失; III)用于土壤 - 盐度洗涤的浸出水分配模式与作物和地区的盐度特征有关,促进干旱和耐盐性作物可有效适应水资源稀缺和陆地盐渍化的风险。与传统方法相比,SFFP可以产生更灵活的替代方案并实现更高的边际效果。这些发现可以提供有效的决策支持,以确定在干旱地区的农业可持续性的多种不确定性下确定所需的水管理策略。

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