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基于集对分析和改进熵权法的水资源承载能力评价与诊断

Water Resources Carrying Capacity Evaluation and Diagnosis Based on Set Pair Analysis and Improved the Entropy Weight Method.

作者信息

Cui Yi, Feng Ping, Jin Juliang, Liu Li

机构信息

Stage Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China.

School of Civil Engineering, Hefei University of Technology, Hefei 230009, China.

出版信息

Entropy (Basel). 2018 May 11;20(5):359. doi: 10.3390/e20050359.

Abstract

To quantitatively evaluate and diagnose the carrying capacity of regional water resources under uncertain conditions, an index system and corresponding grade criteria were constructed from the perspective of carrying subsystem. Meanwhile, an improved entropy weight method was used to determine the objective weight of the index. Then, an evaluation model was built by applying set pair analysis, and a set pair potential based on subtraction was proposed to identify the carrying vulnerability factors. Finally, an empirical study was carried out in Anhui Province. The results showed that the consistency among objective weights of each index was considered, and the uncertainty between the index and grade criterion was reasonably dealt with. Furthermore, although the carrying situation in Anhui was severe, the development tended to be improved. The status in Southern Anhui was superior to that in the middle area, and that in the northern part was relatively grim. In addition, for Northern Anhui, the fewer water resources chiefly caused its long-term overloaded status. The improvement of capacity in the middle area was mainly hindered by its deficient ecological water consumption and limited water-saving irrigation area. Moreover, the long-term loadable condition in the southern part was due largely to its relatively abundant water resources and small population size. This evaluation and diagnosis method can be widely applied to carrying issues in other resources and environment fields.

摘要

为定量评估和诊断不确定条件下区域水资源承载能力,从承载子系统角度构建了指标体系及相应等级标准。同时,采用改进熵权法确定指标的客观权重。然后,应用集对分析建立评价模型,并提出基于减法的集对势来识别承载脆弱性因素。最后,在安徽省进行了实证研究。结果表明,该方法考虑了各指标客观权重间的一致性,合理处理了指标与等级标准间的不确定性。此外,虽然安徽的承载状况严峻,但发展趋势趋于改善。皖南的状况优于中部地区,北部相对严峻。另外,皖北水资源较少导致其长期处于超载状态。中部地区承载能力提升主要受生态用水量不足和节水灌溉面积有限的阻碍。而且,南部长期可承载状况主要得益于其相对丰富的水资源和较小的人口规模。这种评价和诊断方法可广泛应用于其他资源与环境领域的承载问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92fc/7512877/8e75371cb194/entropy-20-00359-g001.jpg

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