南水北调中线工程河南段供用水特征及驱动因素

    Characteristics and driving factors of water supply and consumption in Henan section of Middle Route Project of South-to-North Water Diversion

    • 摘要: 供用水结构可以反映区域水资源开发利用、经济社会发展与生态文明建设的协调程度,研究南水北调中线工程河南段受水区供用水特征和驱动因素对受水区水资源合理配置具有重要意义。基于南水北调中线工程河南段受水区12个城市2003~2022年的供用水数据,采用M-K检验法、信息熵原理和灰色关联理论,分析了研究区供用水结构变化趋势、用水结构均衡度及其驱动因素。结果表明:①在95%置信水平下,受水区地表水源、地下水源以及其他水源供水分别呈现显著上升、显著下降以及显著上升趋势;农业、工业用水均呈不显著下降趋势,而城乡生活环境综合用水则呈显著上升趋势。② 12个城市中用水结构信息熵值均值最大的是许昌市和漯河市,均达1.06,用水结构最为均衡;信息熵值增长最快的是鹤壁市,增幅16.4%,减小最快的是郑州市,降幅达34.4%。③在16个用水结构驱动因子中,粮食产量、年降水量、规模以上企业个数3个指标与对应部门用水量的灰色关联度均增大到0.65~1之间,达到高度相关。

       

      Abstract: The water supply and consumption structure reflects the coordination degree between regional water resources utilization, socio-economic development, and ecological civilization construction.Investigating the characteristics and driving factors of water supply and consumption in the Henan section of the Middle Route Project of the South-to-North Water Diversion is crucial for rational water resource allocation in receiving areas.Based on water supply and consumption data from 12 cities in the receiving areas of Henan section from 2003 to 2022, this study utilized Mann-Kendall test, information entropy principle, and grey correlation theory to analyze the changing trends of water supply and consumption structure, equilibrium degree of water use structure, and driving factors.The results indicated: ① at a 95% confidence level, surface water supply, groundwater supply, and other water sources in the receiving areas showed significant upward, significant downward, and significant upward trends, respectively; agricultural and industrial water use displayed insignificant downward trends, while comprehensive urban-rural living environment water use showed a significant upward trend.② Among the 12 cities, Xuchang City and Luohe City had the highest mean information entropy values (both 1.06), indicating the most balanced water use structure.Hebi City experienced the fastest entropy growth (16.4% increment), while Zhengzhou City showed the most substantial decrease (34.4% reduction).③ Among the 16 driving factors of water use structure, three indicators, namely grain yield, annual precipitation, and the number of enterprises above designated size, demonstrated significantly increased grey correlation degrees with water consumption in corresponding sectors, rising to a range of 0.65~1.0 and reaching high correlation levels.

       

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