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An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition

机译:不确定和非间平条件下区域间和季节性水域管理的间隔多级分类模型

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In regional water management, various uncertainties such as randomness, non-stationarities, dynamics and complexities, lead to difficulties for water managers. To deal with the above problems, a new methodology is proposed by introducing two methods nonstationary analysis, where the generalized additive model is selected to analyze and fit the distribution of water inflow; and model optimization, where an interval multistage water classified-allocation model (IMWCA) is formulated to optimally allocate the available water. By incorporating multistage stochastic programming, interval parameter programming and classification thought, the IMWCA model can tackle both stochastic and imprecise uncertainties, realize inter-seasonal dynamic allocation, and address the complexity of various water users. The methodology is applied to the Zhanghe Irrigation District to optimize water allocation for municipality, industry, hydropower and agriculture among winter, spring, summer and autumn. The Zhanghe Reservoir seasonal inflow is found to be nonstationary for all the seasons and can be well fitted by the corresponding distributions, showing the sense of nonstationary analysis. Additionally, the comparison with the other model demonstrates the need for classification. From the results, municipality and industry are more competitive than hydropower. The Dongbao, Dangyang and Zhanghe districts have a higher priority than the Jingzhou and Shayang districts for irrigation water. Water requirements are more likely to be satisfied in autumn. These solutions of optimal targets and optimal water allocation are valuable for optimizing inter- and intra-seasonal water resource allocation under uncertainty. (C) 2017 Elsevier B.V. All rights reserved.
机译:在区域水管理中,各种不确定性,如随机,非公平性,动态和复杂性,导致水管理人员困难。为了应对上述问题,通过引入两种方法不间断的分析来提出一种新方法,其中选择广义添加剂模型分析和适应水流入的分布;和模型优化,配制间隔多级水分分配模型(IMWCA)以最佳地分配可用水。通过结合多级随机编程,间隔参数编程和分类思想,IMWCA模型可以解决随机和不精确的不确定性,实现季节性动态分配,并解决各种水用户的复杂性。该方法适用于张海灌溉区,优化冬季,春季,夏季和秋季的市政,工业,水电和农业水分分配。张河水库季节性流入被发现为所有季节是非营养的,并且可以通过相应的分布良好地拟合,显示出非子体分析的感觉。此外,与其他模型的比较表明了对分类的需求。从结果,市政和行业比水电更竞争。东宝,当唐和张海区的优先级高于荆州和少凉区进行灌溉水。秋季的水需求更有可能满足。这些最佳目标和最佳水分配的解决方案对于优化不确定性下的季节性和季节性水资源分配有价值。 (c)2017 Elsevier B.v.保留所有权利。

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