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首页> 外文期刊>Journal of the American Water Resources Association >An Interval Two-Stage Classified-Allocation Model for Regional Water Management under Nonstationary Condition
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An Interval Two-Stage Classified-Allocation Model for Regional Water Management under Nonstationary Condition

机译：在非视野条件下区域水管理区间的间隔两阶段分配模型

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Due to climate change and human activities, the assumption of the stationarity of hydrologic features will no longer hold. Moreover, uncertainties, such as the apparent randomness of hydrologic elements, and complexities, such as the existence of various water users with different characteristics, also introduce huge challenges for water managers. To address nonstationarity, uncertainty, and complexity, a new approach is proposed for the optimal allocation of regional water resources. This objective was achieved via two steps: First, the generalized additive model was chosen to analyze the nonstationary probability distribution of the hydrologic dataset; then, an interval two-stage classified-allocation model is formulated by incorporating two-stage stochastic programming, interval parameter programming and classification thought. The model can not only address uncertainties, which were expressed as interval parameters and probability distributions, but can also handle complexities by classifying the water users into agricultural and nonagricultural users. The approach was applied to the Zhanghe Irrigation District to optimize available water allocation for municipality, industry, hydropower, and agriculture in two planning years (namely 2010 and 2015). The annual inflow of the Zhanghe Reservoir is found to be nonstationary and can be well fitted by Gamma distribution with one location parameter based on a nonlinear function of time. Moreover, the difference in output between the two years with different inflow probability distributions indicates the need for nonstationary analysis. Comparison to the inexact two-stage water management model that did not consider the variation of agricultural water requirement shows the meaning of classification. From the results, municipality and industry are more competitive than agriculture and then hydropower. For agriculture, winter rape and cotton have higher priority than rice. These solutions of the optimal targets and optimal water allocation for different water users can help managers to accurately develop allocation plans under uncertain and nonstationary conditions.
机译：由于气候变化和人类的活动，保护水文特征的实证性的假设将不再持有。此外，不确定性，例如水文元素的表观随机性，以及复杂性，例如具有不同特征的各种水用户的存在，也为水管理人员带来了巨大的挑战。为了解决非运动，不确定性和复杂性，提出了一种新方法，以实现区域水资源的最佳分配。通过两个步骤实现了该目的：首先，选择广义添加剂模型来分析水文数据集的非间断概率分布;然后，通过结合两级随机编程，间隔参数编程和分类思想来制定间隔两阶段分配模型。该模型不仅可以解决表示为间隔参数和概率分布的不确定性，而且还可以通过将水用户分类为农业和非农业用户来处理复杂性。该方法适用于张河灌溉区，优化两项规划年代市政，工业，水电和农业的可用水分配（即2010年和2015年）。发现张海水库的年流入是不间断的，可以通过基于时间的非线性函数的一个地点参数进行良好装配。此外，具有不同流入概率分布的两年之间的输出差异表明了对非标准分析的需求。与不考虑农业需求变化的不适的两级水管理模式相比表明了分类的含义。从结果，市政和行业比农业更具竞争力，然后水电更竞争。农业，冬季油菜和棉花的优先级高于米饭。这些解决方案的最佳目标和不同水位用户的最佳水分配可以帮助管理人员在不确定和非间平条件下准确地开发分配计划。

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