Future water stress in China: Projections under socioeconomic and climate change scenarios.

Journal: Journal of environmental management
Published Date: Jul 7, 2025

Abstract

Estimating future water stress under socioeconomic and climate change is crucial for sustainable management. However, previous studies in China normally rely on assumptions, lack region-specific calibration, or apply inconsistent scenarios for water resources and demand. This study develops a new modelling framework integrating machine learning with a land surface model to evaluate Water Stress Index (WSI) by water demand and resources in China. After calibration and validation, the framework projects future WSI under two coupled climate-socioeconomic scenarios: SSP2-RCP4.5 and SSP5-RCP8.5. Results show that the framework accurately simulates surface water resources (R = 0.96) and sectoral water demand (mean R = 0.96). Nationally, WSI is expected to fluctuate between 0.20 and 0.31 from 2022 to 2100, showing no significant improvement or deterioration. Regionally, water stress varies widely, with severe stress projected to increase in the northwest and central regions, particularly under SSP5-RCP8.5, while some northern and northeastern provinces are expected to experience a decrease in water stress. These findings highlight the need for targeted, region-specific water management strategies. In areas where increased WSI is primarily driven by declining water resources alongside rising demand, such as north-central China, policies should focus on both demand management and inter-provincial water allocation strategies. In southeastern China, where water resources are projected to increase but could be offset by higher demand, water-use efficiency improvements and water-saving technologies should be prioritised. Temporal trends across the 2030s, 2060s, and 2090s offer a roadmap for phased policy responses, allowing policymakers to prioritise immediate concerns while planning for long-term challenges.

Authors

  • Danyang Gao
    Centre for Water Systems, University of Exeter, Exeter, EX4 4QF, UK. Electronic address: dg442@exeter.ac.uk.
  • Guangtao Fu
    College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.
  • Xi Wan
    Centre for Water Systems, Department of Engineering, University of Exeter, Exeter, Devon EX4 4QF, UK.
  • Fayyaz Ali Memon
    Centre for Water Systems, University of Exeter, Exeter, EX4 4QF, UK.

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