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Optimal and Fair Distribution of Water Under Water Scarcity Scenarios at a Macroscopic Level
International Journal of Environmental Research ( IF 3.2 ) Pub Date : 2020-11-12 , DOI: 10.1007/s41742-020-00297-8
Rogelio Ochoa-Barragán , Fabricio Nápoles-Rivera , José María Ponce-Ortega

This paper presents an optimization approach for designing water allocation systems at macroscopic level under water scarcity conditions. The proposed approach accounts for the proper water distribution of the available sources (dams, deep wells, lakes, rivers, etc.) and the incorporation of artificial sources (rainwater harvesting systems, and recycled water) to satisfy domestic and agricultural demands in a specific region at the maximum revenue. The proposed mathematical model incorporates fair distribution schemes (Social Welfare, Rawls and Nash Schemes), which allow determining fair water distribution options under water scarcity conditions. A case study for the city of Morelia in Mexico is presented to show the applicability of the proposed optimization approach. Results show that it is possible to obtain fair solutions for the water allocation for all the users under different water scarcity conditions. A mathematical model is developed for optimal water management at macroscopic level. Fair distribution schemes are proposed under water scarcity scenarios. Harvested rainwater and reclaimed water give flexibility to the water network. Results show balanced distribution under water scarcity conditions. A mathematical model is developed for optimal water management at macroscopic level. Fair distribution schemes are proposed under water scarcity scenarios. Harvested rainwater and reclaimed water give flexibility to the water network. Results show balanced distribution under water scarcity conditions.

中文翻译:

宏观层面缺水情景下水资源的最优公平分配

本文提出了一种在缺水条件下宏观层面设计水分配系统的优化方法。提议的方法考虑了可用水源(水坝、深井、湖泊、河流等)的适当水分配,并结合人工水源(雨水收集系统和循环水)以满足特定地区的家庭和农业需求。收入最高的地区。提议的数学模型结合了公平分配方案(社会福利、罗尔斯和纳什方案),允许在缺水条件下确定公平的水分配方案。介绍了墨西哥莫雷利亚市的案例研究,以展示所提出的优化方法的适用性。结果表明,在不同的缺水条件下,可以为所有用户获得公平的水资源分配解决方案。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。结果显示在缺水条件下分布均衡。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。结果显示在缺水条件下分布均衡。开发了一个数学模型,用于宏观层面的最佳水资源管理。在缺水情景下提出了公平分配方案。收集的雨水和再生水为供水网络提供了灵活性。结果显示在缺水条件下分布均衡。
更新日期:2020-11-12
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