Comprehensive Evaluation of Water Resource Carrying Capacity in Hebei Province Based on a Combined Weighting–TOPSIS Model

Water scarcity severely restricts the sustainable development of water-stressed regions like Hebei Province. A scientific assessment of water resource carrying capacity (WRCC) is essential. However, single-weighting methods often lead to biased results. To address this limitation, we propose a combined weighting model that integrates the Entropy Weight Method (EWM), Projection Pursuit (PP), and CRITIC. To support this model, we developed a multi-dimensional, long-term WRCC evaluation dataset covering 11 prefecture-level cities in Hebei Province over 24 years (2000–2023). This approach simultaneously considers data dispersion, inter-indicator conflict, and structural features. It ensures that a more balanced weighting scheme is obtained. The traditional TOPSIS model was further improved through Grey Relational Analysis (GRA), which enhanced the discriminatory power and stability of WRCC assessment. The findings were as follows: (1) From 2000 to 2023, the WRCC in Hebei Province showed a fluctuating upward trend and a “high-north, low-south” spatial gradient. (2) Obstacle analysis revealed a vicious cycle of “resource scarcity–structural conflict–ecological deficit”. This cycle is caused by excessive exploitation of groundwater and low efficiency of industrial water use. The combined weighting–GRA–TOPSIS model offers a reliable WRCC diagnostic tool. The results indicate the core barriers to water use in Hebei and provide targeted policy ideas for sustainable development.

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Published
2025-09-10
DOI
https://doi.org/10.3390/data10090143
Primary Topic
Water Resources and Sustainability
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article
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Comprehensive Evaluation of Water Resource Carrying Capacity in Hebei Province Based on a Combined Weighting–TOPSIS Model

Ying Hong, Yong Chen, Qichao Zhao, Nianning Wang et al.
Data
Water Resources and Sustainability
article

Comprehensive Evaluation of Water Resource Carrying Capacity in Hebei Province Based on a Combined Weighting–TOPSIS Model

Ying Hong, Yong Chen, Qichao Zhao, Nianning Wang, Si-Jie Chen, Lihua Yuan
article en

Abstract

Water scarcity severely restricts the sustainable development of water-stressed regions like Hebei Province. A scientific assessment of water resource carrying capacity (WRCC) is essential. However, single-weighting methods often lead to biased results. To address this limitation, we propose a combined weighting model that integrates the Entropy Weight Method (EWM), Projection Pursuit (PP), and CRITIC. To support this model, we developed a multi-dimensional, long-term WRCC evaluation dataset covering 11 prefecture-level cities in Hebei Province over 24 years (2000–2023). This approach simultaneously considers data dispersion, inter-indicator conflict, and structural features. It ensures that a more balanced weighting scheme is obtained. The traditional TOPSIS model was further improved through Grey Relational Analysis (GRA), which enhanced the discriminatory power and stability of WRCC assessment. The findings were as follows: (1) From 2000 to 2023, the WRCC in Hebei Province showed a fluctuating upward trend and a “high-north, low-south” spatial gradient. (2) Obstacle analysis revealed a vicious cycle of “resource scarcity–structural conflict–ecological deficit”. This cycle is caused by excessive exploitation of groundwater and low efficiency of industrial water use. The combined weighting–GRA–TOPSIS model offers a reliable WRCC diagnostic tool. The results indicate the core barriers to water use in Hebei and provide targeted policy ideas for sustainable development.

DataVol. 10(9)
North China Institute of Aerospace Engineering (CN), Geological Exploration Technology Institute of Jiangsu Province (CN)
Openalex Percentile: Top 77%
Water Resources and Sustainability
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Comprehensive Evaluation of Water Resource Carrying Capacity in Hebei Province Based on a Combined Weighting–TOPSIS Model — Ying Hong, Yong Chen, et al. · Data (2025) | TGRS Research Map | TGRS