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Emerging trends in global freshwater availability

Naturevolume 557pages651659 (2018) | Download Citation

Abstract

Freshwater availability is changing worldwide. Here we quantify 34 trends in terrestrial water storage observed by the Gravity Recovery and Climate Experiment (GRACE) satellites during 2002–2016 and categorize their drivers as natural interannual variability, unsustainable groundwater consumption, climate change or combinations thereof. Several of these trends had been lacking thorough investigation and attribution, including massive changes in northwestern China and the Okavango Delta. Others are consistent with climate model predictions. This observation-based assessment of how the world’s water landscape is responding to human impacts and climate variations provides a blueprint for evaluating and predicting emerging threats to water and food security.

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Acknowledgements

We thank the German Space Operations Center of the German Aerospace Center (DLR) for providing nearly 100% of the raw telemetry data of the twin GRACE satellites. Landsat is an interagency programme managed by NASA and the US Geological Survey. Lake products are courtesy of the USDA/NASA G-REALM programme (available at http://www.pecad.fas.usda.gov/cropexplorer/global_reservoir/). V. Khan of the Hydrometeorological Research Center of the Russian Federation assisted with the Volga River discharge analysis. Graphics were produced by A. K. Moran, Global Science & Technology, Inc. This research was funded by NASA’s GRACE Science Team and NASA’s Energy and Water Cycle Study (NEWS) Team; the University of California Office of the President, Multicampus Research Programs and Initiatives; the NASA Earth and Space Science Fellowship programme; the Jet Propulsion Laboratory; and the Ministry of Science and Technology, Taiwan. Portions of this research were conducted at the Jet Propulsion Laboratory, which is operated for NASA under contract with the California Institute of Technology.

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Author notes

    • J. S. Famiglietti

    Present address: Global Institute for Water Security, School of Environment and Sustainability, and Department of Geography and Planning, University of Saskatchewan, Saskatoon, Canada

Affiliations

  1. Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA

    • M. Rodell
    •  & H. K. Beaudoing
  2. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

    • J. S. Famiglietti
    • , D. N. Wiese
    • , J. T. Reager
    •  & F. W. Landerer
  3. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA

    • H. K. Beaudoing
  4. Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan

    • M.-H. Lo

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Contributions

M.R. and J.S.F. performed background research and designed the study with input from J.T.R. and M.-H.L. D.N.W. and J.T.R. led the GRACE data and error analysis with assistance from F.W.L. M.R. and F.W.L. designed the figures with additional data prepared by H.K.B. M.R. and J.S.F. wrote the manuscript. All authors discussed the results and commented on the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to M. Rodell.

Extended data figures and tables

  1. Extended Data Fig. 1 Non-seasonal TWS anomalies—global regions.

    af, Time series of monthly TWS anomalies (departures from the period mean) from GRACE, after removing the mean seasonal cycle, averaged over each of study regions 1–6, expressed as equivalent heights of liquid water (in centimetres). We note that the y axes vary among panels. Source Data

  2. Extended Data Fig. 2 Non-seasonal TWS anomalies—Eurasia.

    al, As in Extended Data Fig. 1, for regions 7–18.Source Data.

  3. Extended Data Fig. 3 Non-seasonal TWS anomalies—North and South America.

    ah, As in Extended Data Fig. 1, for regions 19–26.Source Data.

  4. Extended Data Fig. 4 Non-seasonal TWS anomalies—Africa and Australia.

    ah, As in Extended Data Fig. 1, for regions 27–34.Source Data.

  5. Extended Data Fig. 5 Annual precipitation totals—global regions.

    af, Time series of annual precipitation totals (in millimetres) averaged over each of study regions 1–6, based on GPCP v.2.3. We note that the y axes vary among panels.Source Data.

  6. Extended Data Fig. 6 Annual precipitation totals—Eurasia.

    an, As in Extended Data Fig. 5, for regions 7–18 and the full drainage basins of the Aral and Caspian seas.Source Data.

  7. Extended Data Fig. 7 Annual precipitation totals—North and South America.

    ah, As in Extended Data Fig. 5, for regions 19–26.Source Data.

  8. Extended Data Fig. 8 Annual precipitation totals—Africa and Australia.

    ah, As in Extended Data Fig. 5, for regions 27–34.Source Data.

  9. Extended Data Fig. 9 Comparison of TWS trends (in centimetres per year) over India (January 2003 – March 2016) from three GRACE mascon solutions.

    ad, JPL-M 3° (a), CSR-M 1° (b), GSFC-M 1° (c) and JPL-M smoothed with a 200-km-radius Gaussian filter and plotted at 1° (d). We note the similarity between bd, whose regional trend amplitudes have all been dampened by smoothing.Source Data.

  10. Extended Data Fig. 10 Comparison of normalized anomalies of Caspian Sea level changes and three primary drivers.

    Normalized anomalies of changes in annual mean Caspian Sea level (black), Volga River discharge (blue), Russian total crop weight (yellow) and Caspian Sea evaporation (red). Precipitation (Extended Data Fig. 6) is the other primary driver. Sea-level change is positively correlated with Volga River discharge and negatively correlated with Russian crop weight and evaporation.Source Data.

Source Data

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DOI

https://doi.org/10.1038/s41586-018-0123-1

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