Dynamic Evaluation of Water Resources Management Performance in the Yangtze River Economic Belt

Fuhua Sun, Caiqin Miao, Shuqin Li (), Juqin Shen, Xin Huang and Shengnan Zhang
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Fuhua Sun: College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China
Caiqin Miao: Business School, Hohai University, Nanjing 210098, China
Shuqin Li: Business School, Hohai University, Nanjing 210098, China
Juqin Shen: College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China
Xin Huang: College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, China
Shengnan Zhang: College of Finance and Economics, Wan Jiang University of Technology, Ma’anshan 243031, China

Sustainability, 2024, vol. 16, issue 2, 1-22

Abstract: The evaluation of water resources management performance (WRMP) can provide guidance for water resources management. This paper constructs a scientific WRMP evaluation index system based on “water resources–water environment–water ecology”. Secondly, the game variable weight matter–element extension model is appropriately introduced to dynamically evaluate the WRMP level of the provinces (cities) in the YREB from 2012 to 2021, and Arcgis is used to analyze the spatial and temporal variations in the performance level of each sub-system. Lastly, a geographical detector model is used to explore the main factors influencing the WRMP in the Yangtze River Economic Balt (YREB). The main findings are as follows: (1) The overall provincial WRMP level in the YREB has been improving from 2012 to 2021, and the performance of water resource utilization (WRU) and water environment treatment (WET) are high in the east and low in the west, while the performance of water ecological protection (WEP) shows a trend of continuous improvement. (2) Compared with the model without variable weight modification, the game variable weight matter–element extension model can reflect the influence of the measured value of the index on the evaluation result as much as possible. (3) The top eight factors that have a greater impact on the WRMP level are the industrial water conservation rate, water resource development and utilization rate, water resource sustainability index, sewage diameter ratio, urban water penetration rate, industrial wastewater treatment completion rate, ecological construction and protection of the year to complete the investment in GDP, and the water ecological carrying capacity growth rate. The interaction types of each influence factor are nonlinear enhancement and two-factor enhancement.

Keywords: water resources management performance; game variable weight matter–element extension; space–time analysis; geographical detector; Yangtze River Economic Belt (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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