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Multimodel assessment of water scarcity under climate change

Open access
Schewe, Jacob, Heinke, Jens, Gerten, Dieter, Haddeland, Ingjerd, Arnell, Nigel W., Clark, Douglas B., Dankers, Rutger, Eisner, Stephanie, Fekete, Balázs M., Colón-González, Felipe J., Gosling, Simon N., Kim, Hyungjun, Liu, Xingcai, Masaki, Yoshimitsu, Portmann, Felix T., Satoh, Yusuke, Stacke, Tobias, Tang, Qiuhong, Wada, Yoshihide, Wisser, Dominik, Albrecht, Torsten, Frieler, Katja, Piontek, Franziska, Warszawski, Lila, Kabat, Pavel·2014·Proceedings of the National Academy of Sciences

Abstract

Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (<500 m 3 per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 °C, whereas indicators of very severe impacts increase unabated beyond 2 °C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

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Metadata

Authors
Schewe, J., Heinke, J., Gerten, D., Haddeland, I., Arnell, N. W., Clark, D. B., Dankers, R., Eisner, S., Fekete, B. M., Colón-González, F. J., Gosling, S. N., Kim, H., Liu, X., Masaki, Y., Portmann, F. T., Satoh, Y., Stacke, T., Tang, Q., Wada, Y., Wisser, D., Albrecht, T., Frieler, K., Piontek, F., Warszawski, L., & Kabat, P.
Venue
Proceedings of the National Academy of Sciences
Published
2013-12-16
Volume
111
Issue
9
Pages
3245-3250
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2148345493
Cited by
1,833
References
4
FWCI
135.39
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Multimodel assessment of water scarcity under climate change. https://app.cochat.ai/papers/10.1073/pnas.1222460110
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Schewe, J., Heinke, J., Gerten, D., Haddeland, I., Arnell, N. W., Clark, D. B., Dankers, R., Eisner, S., Fekete, B. M., Colón-González, F. J., Gosling, S. N., Kim, H., Liu, X., Masaki, Y., Portmann, F. T., Satoh, Y., Stacke, T., Tang, Q., Wada, Y., . . . Kabat, P. (2014). Multimodel assessment of water scarcity under climate change. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1222460110

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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