Uncertainty-Based Industrial Water Supply and Demand Balance Pattern Recognition: A Case Study in the Yellow River Basin of Gansu Province, China

Mingyue Ma, Junying Chu (), Zuhao Zhou, Zuohuai Tang, Yunfu Zhang, Tianhong Zhou, Xusheng Zhang and Ying Wang
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Mingyue Ma: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources & Hydropower Research, Beijing 100038, China
Junying Chu: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources & Hydropower Research, Beijing 100038, China
Zuhao Zhou: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources & Hydropower Research, Beijing 100038, China
Zuohuai Tang: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources & Hydropower Research, Beijing 100038, China
Yunfu Zhang: China Construction Eco-Environmental Group Co., Ltd., Beijing 100037, China
Tianhong Zhou: School of Environment and Municipal Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Xusheng Zhang: Gansu Water Resources and Hydropower Survey and Design Research Institute Co., Ltd., Lanzhou 730000, China
Ying Wang: China Construction Eco-Environmental Group Co., Ltd., Beijing 100037, China

Sustainability, 2025, vol. 17, issue 2, 1-16

Abstract: The balance between water supply and demand is essential for industrial growth, affecting economic, social, and environmental sustainability. Our research employs a Gaussian process regression for demand prediction. Additionally, it takes into account water limits and policy thresholds when determining the supply, thereby defining a range of uncertainty for both the industrial demand and the supply. A pattern recognition method matches this trade-off range, identifying three patterns to support water management. The study focuses on the analysis of industrial water supply and demand dynamics under uncertain conditions in nine cities (Baiyin, Dingxi, Gannan, Lanzhou, Linxia, Pingliang, Qingyang, Tianshui, and Wuwei) in Gansu Province of China’s Yellow River Basin in 2030. The results of the study show that industrial water use in Baiyin, Linxia, Dingxi, and Tianshui cities falls into Pattern I, providing water resources to support industrial development. Industrial water use in Wuwei, Pingliang, Qingyang, and Gannan cities represents Pattern II, which maintains a balance between supply and demand while allowing flexibility in water demand. Finally, the industrial water use in Lanzhou city is characterized by Pattern III, which requires optimization through structural, technological, and management improvements to mitigate the negative impacts of water scarcity on the sustainable development of the economy and society. The results of the research can be used as a reference for policy making in water resources planning and management in the basin.

Keywords: industrial water supply; industrial water demand; uncertainty analysis; pattern recognition; water resource management; Gaussian process regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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