The Spatiotemporal Evolution Characteristics of the Water Use Structure in Shandong Province, Northern China, Based on the Gini Coefficient

The spatiotemporal evolution of the regional water use structure holds significant theoretical value for optimizing regional water resource allocation, adjusting industrial structures, and achieving sustainable water resource development. Shandong Province, located at the lowest reach of the Yellow River Basin in China, is a major economic, agricultural, and populous province, as well as a region with one of the most prominent water supply–demand imbalances in the country. As a result, exploring how water use patterns change over time and space in this region has become crucial. Using analytical methods like the Lorenz curve, Gini coefficient, cluster analysis, and spatial statistics, we examine shifts in Shandong’s water use structure from 2001 to 2023. We find that while agriculture remained the largest water consumer over this period, industrial, household, and ecological water use steadily increased, signaling a move toward more balanced resource distribution. Across Shandong’s 16 regions (cities), the water use patterns varied considerably, particularly in terms of agriculture, industry, and ecological needs. Among these, agricultural, industrial, and domestic water use were distributed relatively evenly, whereas ecological water use showed greater regional disparities. These results may have the potential to guide policymakers in refining water allocation strategies, improving industrial planning, and boosting the water use efficiency in Shandong and the country ore broadly.

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Publication Details

Journal
Water
Published
2025-08-04
DOI
https://doi.org/10.3390/w17152315
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

The Spatiotemporal Evolution Characteristics of the Water Use Structure in Shandong Province, Northern China, Based on the Gini Coefficient

Haijiao Liu, Yongfeng Yang, Kairan Wang, Caihong Liu et al.
Water
Water resources management and optimization
article

The Spatiotemporal Evolution Characteristics of the Water Use Structure in Shandong Province, Northern China, Based on the Gini Coefficient

Haijiao Liu, Yongfeng Yang, Kairan Wang, Caihong Liu, Mingyuan Fan
article en

Abstract

The spatiotemporal evolution of the regional water use structure holds significant theoretical value for optimizing regional water resource allocation, adjusting industrial structures, and achieving sustainable water resource development. Shandong Province, located at the lowest reach of the Yellow River Basin in China, is a major economic, agricultural, and populous province, as well as a region with one of the most prominent water supply–demand imbalances in the country. As a result, exploring how water use patterns change over time and space in this region has become crucial. Using analytical methods like the Lorenz curve, Gini coefficient, cluster analysis, and spatial statistics, we examine shifts in Shandong’s water use structure from 2001 to 2023. We find that while agriculture remained the largest water consumer over this period, industrial, household, and ecological water use steadily increased, signaling a move toward more balanced resource distribution. Across Shandong’s 16 regions (cities), the water use patterns varied considerably, particularly in terms of agriculture, industry, and ecological needs. Among these, agricultural, industrial, and domestic water use were distributed relatively evenly, whereas ecological water use showed greater regional disparities. These results may have the potential to guide policymakers in refining water allocation strategies, improving industrial planning, and boosting the water use efficiency in Shandong and the country ore broadly.

WaterVol. 17(15)
Shandong Provincial Water Resources Research Institute (CN), Shandong Jianzhu University (CN)
Natural Science Foundation of Shandong Province, Postdoctoral Innovation Project of Shandong Province, Water Resources Research Institute, North Carolina State University
Openalex Percentile: Top 77%
Water resources management and optimization
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