Multimodel Assessment of Water Scarcity Under Climate Change
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Multimodel assessment of water scarcity under SPECIAL FEATURE climate change Jacob Schewea,1, Jens Heinkea,b, Dieter Gertena, Ingjerd Haddelandc, Nigel W. Arnelld, Douglas B. Clarke, Rutger Dankersf, Stephanie Eisnerg, Balázs M. Feketeh, Felipe J. Colón-Gonzálezi, Simon N. Goslingj, Hyungjun Kimk, Xingcai Liul, Yoshimitsu Masakim, Felix T. Portmannn,o, Yusuke Satohp, Tobias Stackeq, Qiuhong Tangl, Yoshihide Wadar, Dominik Wissers, Torsten Albrechta, Katja Frielera, Franziska Pionteka, Lila Warszawskia, and Pavel Kabatt,u aPotsdam Institute for Climate Impact Research, 14412 Potsdam, Germany; bInternational Livestock Research Institute, Nairobi, Kenya; cNorwegian Water Resources and Energy Directorate, N-0301 Oslo, Norway; dWalker Institute for Climate System Research, University of Reading, Reading RG6 6AR, United Kingdom; eCentre for Ecology and Hydrology, Wallingford OX10 8BB, United Kingdom; fMet Office Hadley Centre, Exeter EX1 3PB, United Kingdom; gCenter for Environmental Systems Research, University of Kassel, 34109 Kassel, Germany; hCivil Engineering Department, The City College of New York, New York, NY 10031; iAbdus Salam International Centre for Theoretical Physics, I-34151Trieste, Italy; jSchool of Geography, University of Nottingham, Nottingham NG7 2RD, United Kingdom; kInstitute of Industrial Science , The University of Tokyo, 4-6-1 Komaba, Meguro, Tokyo 153-8505, Japan; pDepartment of Civil Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8654, Japan; lInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; mCenter for Global Environmental Research, National Institute for Environmental Studies, Tsukuba 305-8506, Japan; nLOEWE Biodiversity and Climate Research Centre and Senckenberg Research Institute and Natural History Museum, 60325 Frankfurt am Main, Germany; oInstitute of Physical Geography, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany; qMax Planck Institute for Meteorology, 20146 Hamburg, Germany; rDepartment of Physical Geography, Utrecht University, 3584 CS Utrecht, The Netherlands; sCenter for Development Research, University of Bonn, 53113 Bonn, Germany; tInternational Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria; and uWageningen University and Research Centre, 6708, Wageningen, The Netherlands Edited by Hans Joachim Schellnhuber, Potsdam Institute for Climate Impact Research, Potsdam, Germany, and approved August 13, 2013 (received for review January 31, 2013) Water scarcity severely impairs food security and economic pros- resources already constrains development and societal well-being perity in many countries today. Expected future population changes in many countries (4, 5), the expected growth of global population SCIENCE will, in many countries as well as globally, increase the pressure on over the coming decades, together with growing economic pros- SUSTAINABILITY available water resources. On the supply side, renewable water perity, will increase water demand and thus aggravate these resources will be affected by projected changes in precipitation problems (6–8). patterns, temperature, and other climate variables. Here we use Climate change poses an additional threat to water security a large ensemble of global hydrological models (GHMs) forced by because changes in precipitation and other climatic variables five global climate models and the latest greenhouse-gas concen- may lead to significant changes in water supply in many regions tration scenarios (Representative Concentration Pathways) to syn- (6–11). The effect of climate change on water resources is, thesize the current knowledge about climate change impacts on however, uncertain for a number of reasons. Climate model water resources. We show that climate change is likely to exacer- projections, although rather consistent in terms of global average bate regional and global water scarcity considerably. In particular, changes, disagree on the magnitude, and in many cases even the the ensemble average projects that a global warming of 2 °C above sign, of change at a regional scale, in particular when it comes to present (approximately 2.7 °C above preindustrial) will confront an precipitation patterns (12). In addition, the way in which pre- additional approximate 15% of the global population with a severe cipitation changes translate into changes in hydrological varia- decrease in water resources and will increase the number of people bles such as surface or subsurface runoff and river discharge (i.e., living under absolute water scarcity (<500 m3 per capita per year) by runoff accumulated along the river network), and thus in re- another 40% (according to some models, more than 100%) com- newable water resources, depends on many biophysical charac- pared with the effect of population growth alone. For some indica- teristics of the affected region (e.g., orography, vegetation, and tors of moderate impacts, the steepest increase is seen between the soil properties) and is the subject of hydrological models, which present day and 2 °C, whereas indicators of very severe impacts in- represent a second level of uncertainty (11, 13). crease unabated beyond 2 °C. At the same time, the study highlights In the framework of the Inter-Sectoral Impact Model In- large uncertainties associated with these estimates, with both global tercomparison Project [ISI-MIP; Warszawski et al. (14) in this climate models and GHMs contributing to the spread. GHM uncer- issue of PNAS] a set of nine global hydrological models, one tainty is particularly dominant in many regions affected by declining global land-surface model, and one dynamic global vegetation water resources, suggesting a high potential for improved water model [here summarized as global hydrological models (GHMs); resource projections through hydrological model development. Materials and Methods] has been applied using bias-corrected forcing from five different global climate models (GCMs) under climate impacts | hydrological modeling | Inter-Sectoral Impact Model the newly developed Representative Concentration Pathways Intercomparison Project (RCPs). The purpose is to explore the associated uncertainties and to synthesize the current state of knowledge about the reshwater is one of the most vital natural resources of the impact of climate change on renewable water resources at Fplanet. The quantities that humans need for drinking and the global scale. In this paper we investigate the multimodel sanitation are relatively small, and the fact that these basic needs are not satisfied for many people today is primarily a matter of access to, and quality of, available water resources (1). Much Author contributions: J.S., K.F., F.P., L.W., and P.K. designed research; J.S., J.H., D.G., I.H., N.A., D.B.C., R.D., S.E., B.M.F., F.J.C.-G., S.N.G., H.K., X.L., Y.M., F.T.P., Y.S., T.S., Q.T., Y.W., larger quantities of water are required for many other purposes, and D.W. performed research; J.S. and T.A. analyzed data; and J.S. wrote the paper. most importantly irrigated agriculture, but also for industrial use, The authors declare no conflict of interest. in particular for hydropower and the cooling of thermoelectric This article is a PNAS Direct Submission. fi power plants (2, 3). These activities critically depend on a suf - 1To whom correspondence should be addressed. E-mail: [email protected]. cient amount of freshwater that can be withdrawn from rivers, This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. lakes, and groundwater aquifers. Whereas scarcity of freshwater 1073/pnas.1222460110/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1222460110 PNAS | March 4, 2014 | vol. 111 | no. 9 | 3245–3250 Downloaded by guest on September 28, 2021 ensemble projections and the associated spread for changes in a relatively high level of agreement across the multimodel en- annual discharge—taken here as a first-order measure of the semble on the sign of change indicates high confidence. Most of water resources available to humans. We then reconcile these these patterns are consistent with previous studies (8, 11, 17, 18), hydrological changes with global population patterns to estimate but there are also some differences. For example, ensemble pro- how many people will be living in areas affected by a given jections using the previous generation of GCMs and climate sce- change in water resources. Finally, we apply a commonly used narios found a robust runoff increase in southeastern South measure of water scarcity to estimate the percentage of the America (19, 20), where we find no clear trend, or partly even world’s population living in water-scarce countries and to a drying trend. Whereas those latter studies used larger GCM quantify the contributions of both climate change and population ensembles, we apply an unprecedented number of GHMs as well as change to the change in water scarcity. Results are presented as the new RCP climate forcing. At 3 °C of global mean warming, the a function of global mean warming above the present day to ac- pattern of change is similar to that at 2 °C, although the changes are count for the relative independence of regional temperature, enhanced in many regions, and new robust trends emerge in some precipitation, and runoff changes of the rate of warming (15, 16) regions (most notably a strong negative trend in Mesoamerica; SI and to allow for systematic comparison of climate change impacts Appendix,Fig.S1). across scenarios