Satellites reveal widespread decline in global lake water storage
Editor’s summary
The amount of water stored in large lakes has decreased over the past three decades due to both human and climatic drivers. Yao et al. used satellite observations, climate models, and hydrologic models to show that more than 50% of both large natural lakes and reservoirs experienced volume loss over this time (see the Perspective by Cooley). Their findings underscore the importance of better water management to protect essential ecosystem services such as freshwater storage, food supply, waterbird habitat, cycling of pollutants and nutrients, and recreation. —H. Jesse Smith
Abstract
Climate change and human activities increasingly threaten lakes that store 87% of Earth’s liquid surface fresh water. Yet, recent trends and drivers of lake volume change remain largely unknown globally. Here, we analyze the 1972 largest global lakes using three decades of satellite observations, climate data, and hydrologic models, finding statistically significant storage declines for 53% of these water bodies over the period 1992–2020. The net volume loss in natural lakes is largely attributable to climate warming, increasing evaporative demand, and human water consumption, whereas sedimentation dominates storage losses in reservoirs. We estimate that roughly one-quarter of the world’s population resides in a basin of a drying lake, underscoring the necessity of incorporating climate change and sedimentation impacts into sustainable water resources management.
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Volume 380 | Issue 6646
19 May 2023
19 May 2023
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Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
This is an article distributed under the terms of the Science Journals Default License.
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Submission history
Received: 11 March 2022
Accepted: 31 March 2023
Published in print: 19 May 2023
Acknowledgments
We thank A. Temme, C. Martin, S. Nerem, and J. Rosentreter for comments on the results and K. Yang and K. Bogan for suggestions and assistance on the visualizations. We thank P. Lin for sharing the latest version of the GRADES data and H. Beck for sharing the latest version of the MSWEP data for our analyses. Assistance for processing climate and human water use datasets was provided by K. Yang. We also thank L. Patterson for help with downloading the in situ data of reservoirs and L. Pitcher and E. Knight for proofreading our manuscript. We thank C. Schwatke, C. Birkett, and S. Cooley for making the altimetry-derived water level data publicly available.
Funding: This study was supported by NOAA Cooperative Agreement with CIRES (NA17OAR4320101) to F.Y., NASA NIP grant (80NSSC18K0951) to B.L., and the “Climate Change Initiative Grant (4000125030/18/I-NB) to J.-F.C. and M.B.-N.â€
Author contributions: F.Y. conceptualized the project. F.Y., J.W., J.-F.C., and M.B.-N. estimated and analyzed the water storage variability and trends. F.Y., B.R., and B.L. developed the statistical models. F.Y. and B.R. estimated the sedimentation-induced storage loss in reservoirs. F.Y. evaluated the potential impacts of drying lakes on population with inputs from B.L., B.R., and Y.W. F.Y. conducted the validation. F.Y. performed the visualization with inputs from B.L., J.W., and Y.W. F.Y. wrote the manuscript with inputs from B.L., B.R., and J.W. All authors read and commented on drafts of this paper.
Competing interests: The authors declare no competing interests.
Data and materials availability: The Landsat images, including Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper-plus, and Landsat 8 Operational Land Imager, are available from the US Geological Survey at http://earthexplorer.usgs.gov and the Google Earth Engine platform at https://earthengine.google.com. ICESat and ICESat-2 data are available from the National Snow and Ice Data Center (NSIDC) at https://nsidc.org/data. Water levels derived from ICESat-2 are available at https://doi.org/10.5281/zenodo.4489056. Water level products from radar altimeters can be downloaded from the Hydroweb at http://hydroweb.theia-land.fr, the Database for Hydrological Time Series of Inland Waters (DAHITI) at https://dahiti.dgfi.tum.de/en, and the USDA Global Reservoir and Lake Monitor database at https://ipad.fas.usda.gov/cropexplorer/global_reservoir. The CryoSat-2 data are available from the European Space Agency (ESA) at https://earth.esa.int/eogateway/catalog/cryosat-products. The Global Reservoir Bathymetry Dataset can be downloaded from https://dataverse.tdl.org/dataset.xhtml?persistentId=doi:10.18738/T8/TO5HJG. The Global Surface Water (GSW) dataset is available from https://global-surface-water.appspot.com/ and the Google Earth Engine platform at https://earthengine.google.com. Reservoir sedimentation survey data from the US Army Corps can be accessed at https://water.usace.army.mil/ and https://nicholasinstitute.duke.edu/reservoir-national-trends/sediment/. USGS gauge data can be downloaded from https://waterdata.usgs.gov/nwis/, US Army Corps gauge data can be downloaded from https://water.usace.army.mil/ and https://nicholasinstitute.duke.edu/reservoir-data/, California Department of Water Resources gauge data can be downloaded from https://cdec.water.ca.gov/, gauge data from Texas Water Development Board can be downloaded from https://waterdatafortexas.org/reservoirs/statewide, gauge data from Spain can be downloaded from https://ceh.cedex.es/anuarioaforos/afo/embalse-nombre.asp, and gauge data from Bureau of Meteorology in Australia can be downloaded from http://www.bom.gov.au/waterdata/. The HydroLAKES database can be downloaded from https://www.hydrosheds.org/page/hydrolakes. The Georeferenced global Dams And Reservoir dataset (GeoDAR) can be downloaded from https://doi.org/10.5281/zenodo.6163413. The database of Roller-Compacted Concrete (RCC) dams can be accessed at http://www.rccdams.co.uk/. The Global Lake area, Climate, and Population (GLCP) dataset can be downloaded at https://portal.edirepository.org/nis/mapbrowse?packageid=edi.394.4. The HydroSHEDS dataset can be downloaded from https://hydrosheds.org/page/overview. The Climatic Research Unit (CRU) data are available from https://crudata.uea.ac.uk/cru/data/hrg/. ECMWF Reanalysis v5 (ERA5) data are available from https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) are available from https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/. Multi-Source Weighted-Ensemble Precipitation (MSWEP) are available from https://www.gloh2o.org/mswep/. Global Historical Climatology Network data are available from https://www.ncei.noaa.gov/products/land-based-station/global-historical-climatology-network-monthly. Global Land Evaporation Amsterdam Model (GLEAM) data are available from https://www.gleam.eu/. Global Reach-scale A priori Discharge Estimates for SWOT (GRADES) dataset can be downloaded from https://www.reachhydro.org/home/records/grades. The reconstructed human water use data derived from four global hydrologic models can be downloaded from https://zenodo.org/record/1209296#.YZPcr2DMKM8. The water body masks delineated from the GSW dataset, lake volume time series derived from Landsat images and satellite altimeters, lake volume trend estimates, attribution, and all validation analyses are available on the Zenodo data repository at https://zenodo.org/record/7946043. Water storage trends and drivers of studied large lakes are available in the interactive map at https://cires.colorado.edu/globallakes.
Code availability: R scripts that were used to process hydroclimate and human water use data, to derive water levels from ICESat and ICESat-2, to construct lake water storage time series, to estimate the mean rate of sedimentation in reservoirs, to estimate trends in lake water storage and basin aridity, to conduct validation, to construct regression model ensemble, and to estimate affected population are available on CodeOcean at https://codeocean.com/capsule/0322198/tree/v1. JavaScript scripts for mapping water areas from Landsat images and IDL Scripts for processing CyoSat-2 data are available in the supplementary materials.
License information: Copyright © 2023 the authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original US government works. https://www.sciencemag.org/about/science-licenses-journal-article-reuse
Authors
Funding Information
National Aeronautics and Space Administration: 80NSSC20K1143
National Oceanic and Atmospheric Administration: NA17OAR4320101
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- Fangfang Yao
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- Global loss of lake water storage, Science, 380, 6646, (693-693), (2023)./doi/10.1126/science.adi0992
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