Exacerbated global surface water stress under climate change

Abstract

Water stress is expected to intensify due to escalating atmospheric and surface dryness under global warming. Despite extensive research indicate that intensified dryness exacerbates water constraints on ecosystems, the dynamics and underlying mechanisms of surface water stress (SWS) under climate change remain poorly understood. In this study, we use annual evaporative stress as the surface water stress index (WSI) and provide a comprehensive analysis of historical and projected global terrestrial SWS, covering its characteristic changes, driving factors, and impacts on vegetation. Our results show a significant declining trend in WSI during 1982–2014 (-0.0033/decade, p < 0.01), indicating the enhancement of SWS concurrent with a rapid expansion of water stress intensified areas at a rate of 1.85 %/decade (p < 0.01). Using the Budyko-Penman budget framework, we found that the intensification of SWS was primarily driven by an increase in vapor pressure deficit (VPD) and a decrease in precipitation. Furthermore, the intensification of SWS contributed to a decline in vegetation growth, with the extent of areas experiencing increased vegetation water deficit expanding rapidly at a rate of 1.38 % per decade (p < 0.01). In the future, SWS is projected to escalate, with the proportion of areas experiencing intensified SWS increasing from 6.3 % to 24.3 % by the end of the century under the SSP5–8.5. Our study provides a comprehensive analysis of the drivers of SWS under climate change and its impacts on ecosystems, offering valuable scientific insights for the effective management of water resources.

Keywords

Surface water stress / Vapor pressure deficit / Vegetation growth

Data availability

The meteorological and climatological dataset are available from GLDAS2.0: https://disc.gsfc.nasa.gov/datasets/GLDAS_NOAH025_M_2.0/summary?keywords, from ERA5-land: https://cds.climate.copernicus.eu/datasets/, and from TerraClimate: https://www.climatologylab.org/terraclimate.html. The 20 CMIP6 models datasets are available at: https://esgf-node.llnl.gov/search/cmip6/. The Normalized Difference Vegetation Index (NDVI) is available at: https://daac.ornl.gov/VEGETATION/guides/Global_Veg_Greenness_GIMMS_3G.html.

CRediT authorship contribution statement

Ming Peng: Writing – original draft, Visualization, Methodology, Investigation, Data curation, Conceptualization. Haipeng Yu: Writing – review & editing, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization. Jianping Huang: Writing – review & editing, Supervision, Methodology, Funding acquisition. Yu Ren: Writing – review & editing, Investigation, Data curation. Li Fu: Writing – review & editing, Investigation, Data curation.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was jointly supported by the National Natural Science Foundation of China (Grant No. U2442207), the Youth Innovation Promotion Association of Chinese Academy of Sciences (Grant No. 2021427), the West Light Foundation (Grant No. xbzg-zdsys-202409) of the Chinese Academy of Sciences, Key Talent Project in Gansu and Central Guidance Fund for Local Science and Technology Development Projects in Gansu (Grant No. 24ZYQA031). The authors acknowledge European Centre for Medium-Range Weather Forecasts (ECMWF), the Goddard Earth Sciences Data and Information Services Center (GES DISC) of NASA, and University of Idaho for providing the Meteorological and climatological datasets. We also acknowledge the World Climate Research Programme’s (WCRP) Working Group on Coupled Modelling (WGCM), the Global Organization for Earth System Science Portals (GO-ESSP) for producing the CMIP6 model simulations and making them available for analysis. Finally, we acknowledge the Computing Center in Xi’an for providing the computing resource.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2025.100361.

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