ESD Earth System Dynamics ESD Earth Syst. Dynam. 2190-4987 Copernicus Publications Göttingen, Germany 10.5194/esd-4-129-2013 Climate change impact on available water resources obtained using multiple global climate and hydrology models Hagemann S. 1 Chen C. 1 Clark D. B. https://orcid.org/0000-0003-1348-7922 2 Folwell S. 2 Gosling S. N. https://orcid.org/0000-0001-5973-6862 3 Haddeland I. 4 Hanasaki N. https://orcid.org/0000-0002-5092-7563 5 Heinke J. https://orcid.org/0000-0001-5256-0024 6 Ludwig F. 7 Voss F. 8 Wiltshire A. J. 9 Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany Centre for Ecology and Hydrology, Wallingford, UK School of Geography, University of Nottingham, Nottingham, UK Norwegian Water Resources and Energy Directorate, Oslo, Norway National Institute for Environmental Studies, Tsukuba, Japan Potsdam Institute for Climate Impact Research, Potsdam, Germany Wageningen University and Research Centre, Wageningen, the Netherlands Center for Environmental Systems Research, University of Kassel, Kassel, Germany Met Office Hadley Centre, Exeter, UK 07 05 2013 4 1 129 144 Copyright: © 2013 S. Hagemann et al. 2013 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://esd.copernicus.org/articles/4/129/2013/esd-4-129-2013.html The full text article is available as a PDF file from https://esd.copernicus.org/articles/4/129/2013/esd-4-129-2013.pdf

Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.

 References Arora, V.: The use of the aridity index to assess climate change effect on annual runoff, J. Hydrol., 265, 164–177, 2002. Berg, P., Haerter, J. O., Thejll, P., Piani, C., Hagemann, S., and Christensen, J. H.: Seasonal characteristics of the relationship between daily precipitation intensity and surface temperature, J. Geophys. Res., 114, D18102, <a href="http://dx.doi.org/10.1029/2009JD012008">https://doi.org/10.1029/2009JD012008</a>, 2009. Betts, R. A., Boucher, O., Collins, M., Cox, P. M., Falloon, P. D., Gedney, N., Hemming, D. L., Huntingford, C., Jones, C. D., Sexton, D. M., and Webb, M. J.: Projected increase in continental runoff due to plant responses to increasing carbon dioxide, Nature, 448, 1037–1041, 2007. Brutsaert, W. and Parlange, M. B.: Hydrologic cycle explains the evaporation paradox, Nature, 396, 30, <a href="http://dx.doi.org/10.1038/23845">https://doi.org/10.1038/23845</a>, 1998. Döll, P., Kaspar, F., and Lehner, B.: A global hydrological model for deriving water availability indicators: model tuning and validation, J. Hydrol., 270, 105–134, 2003. Dosio, A. and Paruolo, P.: Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate, J. Geophys. Res., 116, D16106, <a href="http://dx.doi.org/10.1029/2011JD015934">https://doi.org/10.1029/2011JD015934</a>, 2011. Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J.: HESS Opinions "Should we apply bias correction to global and regional climate model data?", Hydrol. Earth Syst. Sci., 16, 3391–3404, <a href="http://dx.doi.org/10.5194/hess-16-3391-2012">https://doi.org/10.5194/hess-16-3391-2012</a>, 2012. Falloon, P., Betts, R., Wiltshire, A., Dankers, R., Mathison, C., McNeall, D., Bates, P., and Trigg, M.: Validation of river flows in HadGEM1 and HadCM3 with the TRIP river flow model, J. Hydrometeorol., 12, 1157–1180, 2011. Gosling, S. N. and Arnell, N. W.: Simulating current global river runoff with a global hydrological model: model revisions, validation, and sensitivity analysis, Hydrol. Process., 25, 1129–1145, 2011. Gosling, S. N., Taylor, R. G., Arnell, N. W., and Todd, M. C.: A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models, Hydrol. Earth Syst. Sci., 15, 279–294, <a href="http://dx.doi.org/10.5194/hess-15-279-2011">https://doi.org/10.5194/hess-15-279-2011</a>, 2011. Gosling, S. N., McGregor, G. R., and Lowe, J. A.: The benefits of quantifying climate model uncertainty in climate change impacts assessment: an example with heat-related mortality change estimates, Climatic Change, 112, 217–231, <a href="http://dx.doi.org/10.1007/s10584-011-0211-9">https://doi.org/10.1007/s10584-011-0211-9</a>, 2012. Haddeland, I., Clark, D. B., Franssen, W., Ludwig, F., Vo{ß}, F., Arnell, N. W., Bertrand, N., Best, M., Folwell, S., Gerten, D., Gomes, S., Gosling, S. N., Hagemann, S., Hanasaki, N., Harding, R., Heinke, J., Kabat, P., Koirala, S., Oki, T., Polcher, J., Stacke, T., Viterbo, P., Weedon, G. P., and Yeh, P.: Multi-model estimate of the global terrestrial water balance: setup and first results, J. Hydrometeorol. 12, 869–884, <a href="http://dx.doi.org/10.1175/2011JHM1324.1">https://doi.org/10.1175/2011JHM1324.1</a>, 2011. Haddeland, I., Heinke, J., Vo{ß}, F., Eisner, S., Chen, C., Hagemann, S., and Ludwig, F.: Effects of climate model radiation, humidity and wind estimates on hydrological simulations, Hydrol. Earth Syst. Sci., 16, 305–318, <a href="http://dx.doi.org/10.5194/hess-16-305-2012">https://doi.org/10.5194/hess-16-305-2012</a>, 2012. Haddeland, I., Biemans, H., Eisner, S., Fekete, B., Flörke, M., Hanasaki, N., Heinke, J., Ludwig, F., Schewe, J., Stacke, T., Wada, Y., and Wisser, D.: A global multi-model view on water balance alterations caused by human interventions versus climate change, P. Natl. Acad. Sci., submitted, 2013. Haerter, J. O., Hagemann, S., Moseley, C., and Piani, C.: Climate model bias correction and the role of timescales, Hydrol. Earth Syst. Sci., 15, 1065–1079, <a href="http://dx.doi.org/10.5194/hess-15-1065-2011">https://doi.org/10.5194/hess-15-1065-2011</a>, 2011. Hagemann, S., Berg, P., Christensen, J. H., and Haerter, J. O.: Analysis of existing climate model results over Europe, WATCH Technical Rep.&nbsp;7, <a href="http://www.eu-watch.org/publications/technical-reports">http://www.eu-watch.org/publications/technical-reports</a> (last access:&nbsp;2&nbsp;May&nbsp;2013), 2008. Hagemann, S., Göttel, H., Jacob, D., Lorenz, P., and Roeckner, E.: Improved regional scale processes reflected in projected hydrological changes over large European catchments, Clim. Dynam., 32, 767–781, <a href="http://dx.doi.org/10.1007/s00382-008-0403-9">https://doi.org/10.1007/s00382-008-0403-9</a>, 2009. Hagemann, S., Chen, C., Haerter, J. O., Gerten, D., Heinke, J., and Piani, C.: Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models, J. Hydrometeorol., 12, 556–578, <a href="http://dx.doi.org/10.1175/2011JHM1336.1">https://doi.org/10.1175/2011JHM1336.1</a>, 2011. Hansen, J. W., Challinor, A., Ines, A., Wheeler, T., and Moronet, V.: Translating forecasts into agricultural terms: advances and challenges, Climate Res., 33, 27–41, 2006. Koster, R. D. and Milly, P. C. D.: The interplay between transpiration and runoff formulations in land surface schemes used with atmospheric models, J. Climate, 10, 1578–1591, 1997. Masson, D. and Knutti, R.: Climate model genealogy, Geophys. Res. Lett., 38, L08703, <a href="http://dx.doi.org/10.1029/2011GL046864">https://doi.org/10.1029/2011GL046864</a>, 2011. Meehl, G. A., Boer, G. J., Covey, C., Latif, M., and Stouffer, R. J.: The Coupled Model Intercomparison Project (CMIP), B. Am. Meteorol. Soc., 81, 313–318, 2000. Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J. F. B., Stouffer, R. J., and Taylor, K. E.: The WCRP&nbsp;CMIP3 multi-model dataset: A new era in climate change research, B. Am. Meteorol. Soc., 88, 1383–1394, 2007. Nakicenovic, N., Alcamo, J., Davis, G., de Vries, B., Fenhann, J., Gaffin, S., Gregory, K., Grübler, A., Jung, T. Y., Kram, T., La Rovere, E. L., Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H., Price, L., Raihi, K., Roehrl, A., Rogner, H.-H., Sankovski, A., Schlesinger, M., Shukla, P., Smith, S., Swart, R., van Rooijen, S., Victor, N., and Dadi, Z.: IPCC Special Report on Emissions Scenarios, Cambridge University Press, Cambridge, UK and New York, NY, USA., 2000. Nijssen, B., O'Donnell, G. M., Hamlet, A. F., and Lettenmaier, D. P.: Hydrologic sensitivity of global rivers to climatic change, Climatic Change, 50, 143–175, 2001. Oki, T., Agata, Y., Kanae, S., SaruhashiI, T., and Musiake, K.: Global water resources assessment under climatic change in 2050 using TRIP, Water Resources Systems – Water availability and global change, Proceedings of symposium HS02a held during IUGG2003 at Sapporo, July&nbsp;2003, IAHS Publ., 280, 124–133, 2003. Osborne, T., Rose, G. and Wheeler, T.: Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation, Agr. Forest Meteorol., 170, 183–194. <a href="http://dx.doi.org/10.1016/j.agrformet.2012.07.006">https://doi.org/10.1016/j.agrformet.2012.07.006</a>, 2013. Piani, C. and Haerter, J. O.: Two dimensional bias correction of temperature and precipitation copulas in climate models, Geophys. Res. Lett., <a href="http://dx.doi.org/10.1029/2012GL053839">https://doi.org/10.1029/2012GL053839</a>, in press, 2012. Piani, C., Haerter, J. O., and Coppola, E.: Statistical bias correction for daily precipitation in regional climate models over Europe, Theor. Appl. Climatol., 99, 187–192, 2010a. Piani, C., Weedon, G. P., Best, M., Gomes, S., Viterbo, P., Hagemann, S., and Haerter, J. O.: Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models, J. Hydrol., 395, 199–215, 2010b. Prudhomme, C., Giuntoli, I., Robinson, E. L., Clark, D. B., Arnell, N. W., Dankers, R., Fekete, B., Franssen, W., Gerten, D., Gosling, S. N., Hagemann, S., Hannah, D. M., Kim, H., Masaki, Y., Satoh, Y., Stacke, T., Wada, Y., and Wisser, D.: Drought in the 21st&nbsp;century: a multi-model ensemble experiment to assess global change, quantify uncertainty and identify "hotspots", P. Natl. Acad. Sci., submitted, 2013. Randall, D. A., Wood, R. A., Bony, S., Colman, R., Fichefet, T., Fyfe, J., Kattsov, V., Pitman, A., Shukla, J., Srinivasan, J., Stouffer, R. J., Sumi, A., and Taylor, K. E.: Climate Models and Their Evaluation. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2007. Renner, M. and Bernhofer, C.: Applying simple water-energy balance frameworks to predict the climate sensitivity of streamflow over the continental United States, Hydrol. Earth Syst. Sci., 16, 2531–2546, <a href="http://dx.doi.org/10.5194/hess-16-2531-2012">https://doi.org/10.5194/hess-16-2531-2012</a>, 2012. Roderick, M. and Farquhar, G.: A simple framework for relating variations in runoff to variations in climatic conditions and catchment properties, Water Resour. Res., 47, W00G07, <a href="http://dx.doi.org/10.1029/2010WR009826">https://doi.org/10.1029/2010WR009826</a>, 2011. Rojas, R., Feyen, L., Dosio, A., and Bavera, D.: Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations, Hydrol. Earth Syst. Sci., 15, 2599–2620, <a href="http://dx.doi.org/10.5194/hess-15-2599-2011">https://doi.org/10.5194/hess-15-2599-2011</a>, 2011. Scanlon, T. S., Caylor, K. K., Levin, S. A., and Rodriguez-Iturbe, I.: Positive feedbacks promote power-law clustering of Kalahari vegetation, Nature, 449, 209–212, 2007. Schewe, J., Heinke, J., Gerten, D., Haddeland, I., Arnell, N. W., Clark, D., Dankers, R., Eisner, S., Fekete, B., Colón-González, F. J., Gosling, S., 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., and Kabat, P. :Multi-model assessment of water scarcity under climate change, P. Natl. Acad. Sci., submitted, 2013. Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture–climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, <a href="http://dx.doi.org/10.1016/j.earscirev.2010.02.004">https://doi.org/10.1016/j.earscirev.2010.02.004</a>, 2010. Sharma, D., Das Gupta, A., and Babel, M. S.: Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand, Hydrol. Earth Syst. Sci., 11, 1373–1390, <a href="http://dx.doi.org/10.5194/hess-11-1373-2007">https://doi.org/10.5194/hess-11-1373-2007</a>, 2007. Smakhtin, V., Revenga, C., and Döll, P.: A Pilot Global assessment of environmental water requirements and scarcity, Water Int., 29, 307–317, 2004. Solomon, S., Qin, D., Manning, M., Marquis, M., Averyt, K., Tignor, M. M. B., Miller Jr., H. L., and Chen, Z.&nbsp;(Eds.): Climate Change&nbsp;2007: The Physical Science Basis, Cambridge University Press, Cambridge, 996 pp., 2007. Sperna Weiland, F. C., van Beek, L. P. H., Kwadijk, J. C. J., and Bierkens, M. F. P.: Global patterns of change in discharge regimes for 2100, Hydrol. Earth Syst. Sci., 16, 1047–1062, <a href="http://dx.doi.org/10.5194/hess-16-1047-2012">https://doi.org/10.5194/hess-16-1047-2012</a>, 2012. Weedon, G. P., Gomes, S., Viterbo, P., Shuttleworth, W. J., Blyth, E., Österle, H., Adam, J. C., Bellouin, N., Boucher, O., and Best, M.: Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century, J. Hydrometeorol., 823–848, 12, <a href="http://dx.doi.org/10.1175/2011JHM1369.1">https://doi.org/10.1175/2011JHM1369.1</a>, 2011. Wood, A. W., Leung, L. R., Shridhar, V., and Lettenmaier, D. P.: Hydrologic implications of dynamical and statistical approaches to downscaling climate outputs, Climatic Change, 62, 189–216, 2004.