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Risk analysis of rich-poor rainfall encounter in inter-basin water transfer projects based on Bayesian networks

机译:基于贝叶斯网络的跨流域调水工程富雨降水风险分析

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摘要

An inter-basin water transfer project is one of the effective ways to resolve the problem of an uneven distribution of water resources. Temporal and spatial variations in rainfall in different basins greatly affect water supply and demand in inter-basin water transfer projects, leading to risks to the operation of the water transfer projects. This paper applies a Bayesian network model to analyze this risk and studies the rich-poor rainfall encounter risk between a water source area and water receiving areas in the middle route of the South-to-North Water Transfer Project in China. Real time scenario simulations with the input of new observations were also studied. The results show that the rich-poor rainfall encounter risk is high for the Tangbai River receiving area in the fourth quarter, for the Huai River and South of Hai River receiving area in the second quarter, and for the North of the Hai River receiving area in the fourth and first quarters. The scenario simulations reflect risk change in the operation of water transfer projects, providing scientific decision support for the management of the water resource distribution in the inter-basin water transfer projects.
机译:跨流域调水工程是解决水资源分配不均问题的有效途径之一。流域间降雨的时空变化极大地影响了跨流域调水工程的供需,给调水工程的运行带来风险。本文运用贝叶斯网络模型对这一风险进行了分析,并研究了南水北调中线中水源区与受水区之间降雨富集的风险。还研究了具有新观测值输入的实时情景模拟。结果表明,唐白河入库区第四季度,淮河和海河以南地区第二季度,海河以北地区的富贫雨遭遇风险较高。在第四和第一季度。情景模拟反映了调水项目运行中的风险变化,为流域间调水项目中的水资源分配管理提供了科学决策支持。

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