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A Case Study of Grassroots Water Conservancy Services Evaluation and Obstacle Factors Diagnosis Based on Gray Correlation-TOPSIS Model in Hunan Province, China

Author

Listed:
  • Jie Zhang

    (Hunan Institute of Water Resourses and Hydropower Research, Changsha 410011, China)

  • Zihao Tang

    (Hunan Institute of Water Resourses and Hydropower Research, Changsha 410011, China
    School of Hydraulic and Environmental Engineering, Changsha University of Science and Technology, Changsha 410114, China)

  • Bin Deng

    (School of Hydraulic and Environmental Engineering, Changsha University of Science and Technology, Changsha 410114, China
    Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province, Changsha 410114, China)

  • Siyan Liu

    (Hunan Institute of Water Resourses and Hydropower Research, Changsha 410011, China)

  • Yifei Xiang

    (College of Artificial Intelligence, Guangxi Minzu University, Nanning 530006, China)

Abstract

Based on the evaluation model of the gray correlation-TOPSIS method, this paper examines the index system of grass-roots water conservancy services in Hunan Province, China. This paper aims at the present situation of grassroots water conservancy in Hunan province, which assisted it in developing grassroots water conservancy services. The evaluation indicators include five criteria levels (institutional staffing, personnel quality, management level, public policy and service capacity) and twenty-four indicator levels. In this paper, the weight calculation method combined with an analytic hierarchy process and an entropy weight method, as well as quantitative and qualitative methods, was used to conduct an empirical study on the basic water conservancy service level of Hunan Province in 2020. The results classify grassroots water services in Hunan Province into three levels. By fitting the GDP of cities and prefectures with the comprehensive closeness, we conclude that there is considerable convergence between the grassroots water conservancy service level of Hunan Province and its local economic level. The more developed the economy, the higher the grassroots water conservancy service level. In addition, through obstacle factor analysis, the main constraints of grassroots water conservancy in various cities and prefectures are obtained. Therefore, the grassroots water conservancy service’s ability can be comprehensively improved from three aspects: serviceability, capital investment, and talent construction. This indicator system can promote the overall governance capacity of grassroots water conservancy in the future development of cities and prefectures, and it can also provide Hunan with experience and case examples for the implementation of rural revitalization.

Suggested Citation

  • Jie Zhang & Zihao Tang & Bin Deng & Siyan Liu & Yifei Xiang, 2022. "A Case Study of Grassroots Water Conservancy Services Evaluation and Obstacle Factors Diagnosis Based on Gray Correlation-TOPSIS Model in Hunan Province, China," IJERPH, MDPI, vol. 20(1), pages 1-18, December.
    • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:174-:d:1012011
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    1. Pawlak, Zdzisaw & Sowinski, Roman, 1994. "Rough set approach to multi-attribute decision analysis," European Journal of Operational Research, Elsevier, vol. 72(3), pages 443-459, February.
    2. Cai, Ximing & McKinney, Daene C. & Rosegrant, Mark W., 2003. "Sustainability analysis for irrigation water management in the Aral Sea region," Agricultural Systems, Elsevier, vol. 76(3), pages 1043-1066, June.
    3. Sun, Haoyang & Wang, Sufen & Hao, Xinmei, 2017. "An Improved Analytic Hierarchy Process Method for the evaluation of agricultural water management in irrigation districts of north China," Agricultural Water Management, Elsevier, vol. 179(C), pages 324-337.
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