刘凌,陈浩,周戎星,等. 动态差异度系数在淮北平原水资源承载力评价中的应用[J]. 水利水运工程学报,2024.. doi: 10.12170/20230519002
引用本文: 刘凌,陈浩,周戎星,等. 动态差异度系数在淮北平原水资源承载力评价中的应用[J]. 水利水运工程学报,2024.. doi: 10.12170/20230519002
(LIU Ling, CHEN Hao, ZHOU Rongxing, et al. Utilizing dynamic difference coefficient in the evaluation of water resources carrying capacity in the Huaibei plain of Anhui province[J]. Hydro-Science and Engineering, 2024(in Chinese)). doi: 10.12170/20230519002
Citation: (LIU Ling, CHEN Hao, ZHOU Rongxing, et al. Utilizing dynamic difference coefficient in the evaluation of water resources carrying capacity in the Huaibei plain of Anhui province[J]. Hydro-Science and Engineering, 2024(in Chinese)). doi: 10.12170/20230519002

动态差异度系数在淮北平原水资源承载力评价中的应用

Utilizing dynamic difference coefficient in the evaluation of water resources carrying capacity in the Huaibei plain of Anhui province

  • 摘要: 为科学有效地评价区域水资源承载力,基于现有动态差异度系数的相关研究,充分挖掘评价样本与等级标准之间的不确定性信息,推导出随样本值变化而变化的差异度系数计算式,构建了基于动态差异度系数的四元联系数值法的区域水资源承载力定量评价方法。该方法在安徽省淮北平原的应用结果表明:2015—2019年安徽省淮北平原六市水资源承载状况均处于2级临界可载与3级临界超载之间,说明水资源承载状况较差;联系数值法得出的评价结果与级别特征值法、四元减法集对势基本相同,联系数值法较其他两种方法更客观,灵敏度更高;联系数值法可准确判断集对系统的发展趋势,为解决水资源、水环境等领域类似评价提供参考。

     

    Abstract: In order to assess the water resources carrying capacity in the Huaibei plain of Anhui province in a scientific and effective manner, this study utilizes the dynamic difference coefficient. By leveraging uncertainty information between evaluation samples and grade standards, the study fully explores the potential of the dynamic difference coefficient formula, which adjusts according to the sample values. A quantitative evaluation method for regional water resources carrying capacity is then established based on this dynamic difference coefficient. The application of this method in the Huaibei plain of Anhui province reveals that the water resources carrying status of the six cities in the region ranged between level 2 (critical load) and level 3 (critical overload) during the period of 2015-2019, suggesting a poor water resources carrying capacity. The evaluation results obtained through the associative numerical method align closely with those obtained using the hierarchical eigenvalue method and the quaternion subtraction method. However, the associative numerical method proves to be more objective and sensitive compared to the other two methods. The relational numerical method accurately predicts the development trends of the set pair system, providing valuable insights for addressing similar evaluation issues related to water resources and the water environment.

     

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