CaltechAUTHORS
Published January 2025 | Version Published
Journal Article Open

Decoupling of surface water storage from precipitation in global drylands due to anthropogenic activity

Creators

  • 1. ROR icon Institute of Geographic Sciences and Natural Resources Research
  • 2. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA
  • 3. ROR icon Texas A&M University
  • 4. ROR icon Southwest University
  • 5. ROR icon University of Chinese Academy of Sciences
  • 6. ROR icon Bangor University
  • 7. ROR icon Stanford University

Abstract

The availability of surface water in global drylands is essential for both human society and ecosystems. However, the long-term drivers of change in surface water storage, particularly those related to anthropogenic activities, remain unclear. Here we use multi-mission remote sensing data to construct monthly time series of water storage changes from 1985 to 2020 for 105,400 lakes and reservoirs in global drylands. An increase of 2.20 km3 per year in surface water storage is found primarily due to the construction of new reservoirs. For lakes and old reservoirs (constructed before 1983), conversely, the trend in storage is minor when aggregated globally, but they dominate surface water storage trends in 91% of individual global dryland basins. Further analysis reveals that long-term storage changes in these water bodies are primarily linked to anthropogenic factors—including human-induced warming and water-management practices—rather than to precipitation changes, as previously thought. These findings reveal a decoupling of surface water storage from precipitation in global drylands, raising concerns about societal and ecosystem sustainability.

Copyright and License

© The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acknowledgement

G.Z. was supported by the Third Xinjiang Scientific Expedition Program (grant number 2021xjkk0803), the Chinese Academy of Sciences Pioneer Initiative Talents Program and the Carnegie Institution for Science. Q.T. was supported by the Third Xinjiang Scientific Expedition Program (grant number 2021xjkk0800) and the National Natural Science Foundation of China (U2243226). Y.L. is supported by the National Natural Science Foundation of China (42201349). A.M.M., J.M. and L.R. were supported by the Carnegie Institution for Science. R.I.W. was supported by the UK Research and Innovation (UKRI) Natural Environment Research Council (NERC) grant reference NE/T011246/1 and NE/X019071/1 (‘UK Earth Observation Climate Information Service (EOCIS)’). We have benefitted from the usage of the Google Earth Engine platform.

Data Availability

The shapefiles of HydroLAKES are available from https://www.hydrosheds.org/page/hydrolakes. The GOODD is available at https://www.globaldamwatch.org/goodd. The global dryland lake storage dataset59—containing monthly lake areas, surface elevation and storage changes for 105,400 lakes and reservoirs—is available via Figshare at https://doi.org/10.6084/m9.figshare.25609902.v1 (ref. 59).

Code Availability

The codes for the core algorithm are available via Github at https://github.com/gzhaowater/dryland.

Supplemental Material

Supplementary Figs. 1–19 and Tables 1–3.

Files

s44221-024-00367-7.pdf

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Additional details

Funding

Ministry of Science and Technology of the People's Republic of China
2021xjkk0803
Chinese Academy of Sciences
Pioneer Initiative Talents Program
Carnegie Institution for Science
Ministry of Science and Technology of the People's Republic of China
2021xjkk0800
National Natural Science Foundation of China
U2243226
National Natural Science Foundation of China
42201349
Natural Environment Research Council
NE/T011246/1
Natural Environment Research Council
NE/X019071/1

Dates

Available
2025-01-10
Published

Caltech Custom Metadata

Caltech groups
Division of Geological and Planetary Sciences (GPS)
Publication Status
Published