Articles | Volume 21, issue 11
https://doi.org/10.5194/hess-21-5863-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-5863-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Nov 2017
Research article |
| 27 Nov 2017
Global change in streamflow extremes under climate change over the 21st century
Department of Earth and Environmental Science, University of Pennsylvania, Philadelphia, PA, USA
Nir Y. Krakauer
Civil Engineering Department and NOAA-CREST, The City College of New York, City University of New York, New York, USA
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Hydrol. Earth Syst. Sci., 19, 877–891, https://doi.org/10.5194/hess-19-877-2015, https://doi.org/10.5194/hess-19-877-2015, 2015
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We present a systematic comparison of changes in historical extreme precipitation in station observations (HadEX2) and 15 climate models from the CMIP5 (as the largest and most recent sets of available observational and modeled data sets), on global and continental scales for 1901-2010, using both parametric (linear regression) and non-parametric (the Mann-Kendall as well as Sen’s slope estimator) methods, taking care to sample observations and models spatially and temporally in comparable ways.
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We simulated effects of irrigation on climate with the NASA GISS global climate model. Present-day irrigation levels affected air pressures and temperatures even in non-irrigated land and ocean areas. The simulated effect was bigger and more widespread when ocean temperatures in the climate model could change, rather than being fixed. We suggest that expanding irrigation may affect global climate more than previously believed.
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Subject: Global hydrology | Techniques and Approaches: Uncertainty analysis
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H. Müller Schmied, S. Eisner, D. Franz, M. Wattenbach, F. T. Portmann, M. Flörke, and P. Döll
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P. Roudier, A. Ducharne, and L. Feyen
Hydrol. Earth Syst. Sci., 18, 2789–2801, https://doi.org/10.5194/hess-18-2789-2014, https://doi.org/10.5194/hess-18-2789-2014, 2014
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
A. Kauffeldt, S. Halldin, A. Rodhe, C.-Y. Xu, and I. K. Westerberg
Hydrol. Earth Syst. Sci., 17, 2845–2857, https://doi.org/10.5194/hess-17-2845-2013, https://doi.org/10.5194/hess-17-2845-2013, 2013
I. H. Taylor, E. Burke, L. McColl, P. D. Falloon, G. R. Harris, and D. McNeall
Hydrol. Earth Syst. Sci., 17, 2339–2358, https://doi.org/10.5194/hess-17-2339-2013, https://doi.org/10.5194/hess-17-2339-2013, 2013
H. Xie, L. Longuevergne, C. Ringler, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 16, 3083–3099, https://doi.org/10.5194/hess-16-3083-2012, https://doi.org/10.5194/hess-16-3083-2012, 2012
F. Sienz, O. Bothe, and K. Fraedrich
Hydrol. Earth Syst. Sci., 16, 2143–2157, https://doi.org/10.5194/hess-16-2143-2012, https://doi.org/10.5194/hess-16-2143-2012, 2012
D. González-Zeas, L. Garrote, A. Iglesias, and A. Sordo-Ward
Hydrol. Earth Syst. Sci., 16, 1709–1723, https://doi.org/10.5194/hess-16-1709-2012, https://doi.org/10.5194/hess-16-1709-2012, 2012
S. N. Gosling, R. G. Taylor, N. W. Arnell, and M. C. Todd
Hydrol. Earth Syst. Sci., 15, 279–294, https://doi.org/10.5194/hess-15-279-2011, https://doi.org/10.5194/hess-15-279-2011, 2011
W. A. Dorigo, K. Scipal, R. M. Parinussa, Y. Y. Liu, W. Wagner, R. A. M. de Jeu, and V. Naeimi
Hydrol. Earth Syst. Sci., 14, 2605–2616, https://doi.org/10.5194/hess-14-2605-2010, https://doi.org/10.5194/hess-14-2605-2010, 2010
G. Schumann, D. J. Lunt, P. J. Valdes, R. A. M. de Jeu, K. Scipal, and P. D. Bates
Hydrol. Earth Syst. Sci., 13, 1545–1553, https://doi.org/10.5194/hess-13-1545-2009, https://doi.org/10.5194/hess-13-1545-2009, 2009
Cited articles
Alexander, L. V., Zhang, X., Peterson, T. C., Caesar, J., Gleason, B., Klein Tank, A. M. G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., Tagipour, A., Rupa Kumar, K., Revadekar, J., Griffiths, G., Vincent, L., Stephenson, D. B., Burn, J., Aguilar, E., Brunet, M., Taylor, M., New, M., Zhai, P., Rusticucci, M., and Vazquez-Aguirre, J. L.: Global observed changes in daily climate extremes of temperature and precipitation, J. Geophys. Res., 111, D05109, https://doi.org/10.1029/2005JD006290, 2006.
Alfieri, L., Burek, P., Feyen, L., and Forzieri, G.: Global warming increases the frequency of river floods in Europe, Hydrol. Earth Syst. Sci., 19, 2247–2260, https://doi.org/10.5194/hess-19-2247-2015, 2015.
Alfieri, L., Bisselink, B., Dottori, F., Naumann, G., Wyser, K., Feyen, L., and De Roo, A.: Global projections of river flood risk in a warmer world, Earth's Futur, 5, 171–182, https://doi.org/10.1002/2016EF000485, 2017.
Allan, R. P. and Soden, B. J.: Atmospheric warming and the amplification of precipitation extremes, Science, 321, 1481–484, https://doi.org/10.1126/science.1160787, 2008.
Allen, M. R. and Ingram, W. J.: Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 224–232, https://doi.org/10.1038/nature01092, 2002.
Arnell, N. W.: Climate change and global water resources: SRES emissions and socio-economic scenarios, Glob. Environ. Chang., 14, 31–52, https://doi.org/10.1016/j.gloenvcha.2003.10.006, 2004.
Asadieh, B. and Krakauer, N. Y.: Global trends in extreme precipitation: climate models versus observations, Hydrol. Earth Syst. Sci., 19, 877–891, https://doi.org/10.5194/hess-19-877-2015, 2015.
Asadieh, B. and Krakauer, N. Y.: Impacts of changes in precipitation amount and distribution on water resources studied using a model rainwater harvesting system, J. Am. Water Resour. Assoc., 52, 1450–1471, https://doi.org/10.1111/1752-1688.12472, 2016.
Asadieh, B., Krakauer, N. Y., and Fekete, B. M.: Historical trends in mean and extreme runoff and streamflow based on observations and climate models, Water, 8, 189, https://doi.org/10.3390/w8050189, 2016.
Brekke, L. D., Maurer, E. P., Anderson, J. D., Dettinger, M. D., Townsley, E. S., Harrison, A., and Pruitt, T.: Assessing reservoir operations risk under climate change, Water Resour. Res., 45, 1–16, https://doi.org/10.1029/2008WR006941, 2009.
Carmack, E. C., Yamamoto-Kawai, M., Haine, T. W. N., Bacon, S., Bluhm, B. A., Lique, C., Melling, H., Polyakov, I. V., Straneo, F., Timmermans, M. L., and Williams, W. J.: Freshwater and its role in the Arctic Marine System: Sources, disposition, storage, export, and physical and biogeochemical consequences in the Arctic and global oceans, J. Geophys. Res.-Biogeosciences, 121, 675–717, https://doi.org/10.1002/2015JG003140, 2016.
Dai, A.: Drought under global warming: A review, Wiley Interdiscip. Rev. Clim. Chang., 2, 45–65, https://doi.org/10.1002/wcc.81, 2011.
Dankers, R., Arnell, N. W., Clark, D. B., Falloon, P. D., Fekete, B. M., Gosling, S. N., Heinke, J., Kim, H., Masaki, Y., Satoh, Y., Stacke, T., Wada, Y., and Wisser, D.: First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble, P. Natl. Acad. Sci. USA, 111, 3257–3261, https://doi.org/10.1073/pnas.1302078110, 2013.
Dilley, M., Chen, R. S., Deichmann, U., Lerner-Lam, A. L., and Arnold, M.: Natural disaster hotspots: a global risk analysis, World Bank Publications, Washington D.C. USA, 5, 2005.
Doxsey-Whitfield, E., MacManus, K., Adamo, S. B., Pistolesi, L., Squires, J., Borkovska, O., and Baptista, S. R.: Taking advantage of the improved availability of census data: a first look at the gridded population of the world, version 4 (GPWv4), Pap. Appl. Geogr., 1, 226–234, https://doi.org/10.1080/23754931.2015.1014272, 2015.
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, https://doi.org/10.5194/hess-16-3391-2012, 2012.
Ehsani, N., Vörösmarty, C. J., Fekete, B. M., and Stakhiv, E. Z.: Reservoir Operations Under Climate Change: Storage Capacity Options to Mitigate Risk, J. Hydrol., 555, 435–446, https://doi.org/10.1016/j.jhydrol.2017.09.008, 2017.
Ellis, A. W., Goodrich, G. B., and Garfin, G. M.: A hydroclimatic index for examining patterns of drought in the Colorado River Basin, Int. J. Climatol., 30, 236–255, https://doi.org/10.1002/joc.1882, 2010.
Field, C. B.: Managing the risks of extreme events and disasters to advance climate change adaptation: special report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, UK, 2012.
Giuntoli, I., Vidal, J.-P., Prudhomme, C., and Hannah, D. M.: Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models, Earth Syst. Dynam., 6, 267–285, https://doi.org/10.5194/esd-6-267-2015, 2015.
Haddeland, I., Clark, D. B., Franssen, W., Ludwig, F., Voß, 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.: Multimodel estimate of the global terrestrial water balance: setup and first results, J. Hydrometeorol., 12, 869–884, https://doi.org/10.1175/2011JHM1324.1, 2011.
Hagemann, S., Chen, C., Haerter, J. O., Heinke, J., Gerten, D., 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, https://doi.org/10.1175/2011JHM1336.1, 2011.
Hagemann, S., Chen, C., Clark, D. B., Folwell, S., Gosling, S. N., Haddeland, I., Hanasaki, N., Heinke, J., Ludwig, F., Voss, F., and Wiltshire, A. J.: Climate change impact on available water resources obtained using multiple global climate and hydrology models, Earth Syst. Dynam., 4, 129–144, https://doi.org/10.5194/esd-4-129-2013, 2013.
Haine, T. W. N., Curry, B., Gerdes, R., Hansen, E., Karcher, M., Lee, C., Rudels, B., Spreen, G., de Steur, L., Stewart, K. D., and Woodgate, R.: Arctic freshwater export: Status, mechanisms, and prospects, Glob. Planet. Change, 125, 13–35, https://doi.org/10.1016/j.gloplacha.2014.11.013, 2015.
Held, I. M. and Soden, B. J.: Robust responses of the hydrological cycle to global warming, J. Climate, 19, 5686–5699, https://doi.org/10.1175/JCLI3990.1, 2006.
Hempel, S., Frieler, K., Warszawski, L., Schewe, J., and Piontek, F.: A trend-preserving bias correction – the ISI-MIP approach, Earth Syst. Dynam., 4, 219–236, https://doi.org/10.5194/esd-4-219-2013, 2013.
Hirabayashi, Y., Kanae, S., Emori, S., Oki, T., and Kimoto, M.: Global projections of changing risks of floods and droughts in a changing climate, Hydrol. Sci. J., 53, 754–772, https://doi.org/10.1623/hysj.53.4.754, 2008.
Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D., Watanabe, S., Kim, H., and Kanae, S.: Global flood risk under climate change, Nat. Clim. Chang., 3, 816–821, https://doi.org/10.1038/nclimate1911, 2013.
IFRC: World disaster report, focus on reducing risk, edited by: Walter, J., International Federation of Red Cross and Red Crescent Societies, Geneva, Switzerland, available at: http://www.ifrc.org/Global/Publications/disasters/WDR/32600-WDR2002.pdf (last access: 21 November 2017), 2002.
Jian, X., Wolock, D. M., Lins, H. F., and Brady, S.: Streamflow of 2015 – Water year national summary, U.S. Geological Survey Fact Sheet 2016–3055, 6 p., https://doi.org/10.3133/fs20163055, available at: https://waterwatch.usgs.gov/2015summary/ (last access: 21 November 2017), 2015.
Kharin, V. V., Zwiers, F. W., Zhang, X., and Wehner, M.: Changes in temperature and precipitation extremes in the CMIP5 ensemble, Clim. Change, 119, 345–357, https://doi.org/10.1007/s10584-013-0705-8, 2013.
Koirala, S., Hirabayashi, Y., Mahendran, R., and Kanae, S.: Global assessment of agreement among streamflow projections using CMIP5 model outputs, Environ. Res. Lett., 9, 64017, https://doi.org/10.1088/1748-9326/9/6/064017, 2014.
Krakauer, N. Y. and Fekete, B. M.: Are climate model simulations useful for forecasting precipitation trends? Hindcast and synthetic-data experiments, Environ. Res. Lett., 9, 24009, https://doi.org/10.1088/1748-9326/9/2/024009, 2014.
Lambert, F. H., Stine, A. R., Krakauer, N. Y., and Chiang, J. C. H.: How much will precipitation increase with global warming?, Eos, Trans. Am. Geophys. Union, 89, 193–194, https://doi.org/10.1029/2008EO210001, 2008.
Lique, C., Holland, M. M., Dibike, Y. B., Lawrence, D. M., and Screen, J. A.: Modeling the Arctic freshwater system and its integration in the global system: Lessons learned and future challenges, J. Geophys. Res.-Biogeosciences, 121, 540–566, https://doi.org/10.1002/2015JG003120, 2016.
Min, S.-K., Zhang, X., Zwiers, F. W., and Hegerl, G. C.: Human contribution to more-intense precipitation extremes, Nature, 470, 378–81, https://doi.org/10.1038/nature09763, 2011.
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next generation of scenarios for climate change research and assessment, Nature, 463, 747–756, https://doi.org/10.1038/nature08823, 2010.
O'Gorman, P. A. and Schneider, T.: The physical basis for increases in precipitation extremes in simulations of 21st-century climate change, P. Natl. Acad. Sci. USA, 106, 14773–14777, https://doi.org/10.1073/pnas.0907610106, 2009.
Oki, T. and Kanae, S.: Global hydrological cycles and world water resources, Science., 313, 1068–1072, https://doi.org/10.1126/science.1128845, 2006.
Pall, P., Allen, M. R., and Stone, D. A.: Testing the Clausius–Clapeyron constraint on changes in extreme precipitation under CO2 warming, Clim. Dynam., 28, 351–363, https://doi.org/10.1007/s00382-006-0180-2, 2006.
Peterson, B. J., Holmes, R. M., McClelland, J. W., Vörösmarty, C. J., Lammers, R. B., Shiklomanov, A. I., Shiklomanov, I. A., and Rahmstorf, S.: Increasing river discharge to the Arctic Ocean, Science, 298, 2171–2173, https://doi.org/10.1126/science.1077445, 2002.
Rawlins, M. A., Steele, M., Holland, M. M., Adam, J. C., Cherry, J. E., Francis, J. A., Groisman, P. Y., Hinzman, L. D., Huntington, T. G., Kane, D. L., Kimball, J. S., Kwok, R., Lammers, R. B., Lee, C. M., Lettenmaier, D. P., Mcdonald, K. C., Podest, E., Pundsack, J. W., Rudels, B., Serreze, M. C., Shiklomanov, A., Skagseth, O., Troy, T. J., Vorosmarty, C. J., Wensnahan, M., Wood, E. F., Woodgate, R., Yang, D., Zhang, K., and Zhang, T.: Analysis of the Arctic system for freshwater cycle intensification: Observations and expectations, J. Climate, 23, 5715–5737, https://doi.org/10.1175/2010JCLI3421.1, 2010.
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., and Kabat, P.: Multimodel assessment of water scarcity under climate change, P. Natl. Acad. Sci. USA, 111, 3245–3250, https://doi.org/10.1073/pnas.1222460110, 2013.
Snedecor, G. W. and Cochran, W. G.: Statistical methods, 8th Edn, Iowa State University Press, Iowa, 1989.
Sprague, L. A.: Drought Effects on Water Quality in the South Platte River Basin, Colorado, J. Am. Water Resour. Assoc., 41, 11–24, https://doi.org/10.1111/j.1752-1688.2005.tb03713.x, 2005.
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M. M. B., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M.: Climate change 2013: The physical science basis. Working group I contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 2013.
Tang, Q. and Lettenmaier, D. P.: 21st century runoff sensitivities of major global river basins, Geophys. Res. Lett., 39, L06403, https://doi.org/10.1029/2011GL050834, 2012.
Toreti, A., Naveau, P., Zampieri, M., Schindler, A., Scoccimarro, E., Xoplaki, E., Dijkstra, H. A., Gualdi, S., and Luterbacher, J.: Projections of global changes in precipitation extremes from Coupled Model Intercomparison Project Phase 5 models, Geophys. Res. Lett., 40, 4887–4892, https://doi.org/10.1002/grl.50940, 2013.
Trenberth, K. E.: Changes in precipitation with climate change, Clim. Res., 47, 123–138, https://doi.org/10.3354/cr00953, 2011.
UNFCCC: Adoption of the Paris Agreement (FCCC/CP/2015/L.9/Rev.1), available at: http://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf (last access: 21 November 2017), 2015.
Vörösmarty, C. J., Green, P., Salisbury, J., and Lammers, R. B.: Global water resources: vulnerability from climate change and population growth, Science, 289, 284–288, https://doi.org/10.1126/science.289.5477.284, 2000.
Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., and Schewe, J.: The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): Project framework, P. Natl. Acad. Sci. USA, 111, 1–5, https://doi.org/10.1073/pnas.1312330110, 2013.
Wentz, F. J., Ricciardulli, L., Hilburn, K., and Mears, C.: How much more rain will global warming bring?, Science, 317, 233–235, https://doi.org/10.1126/science.1140746, 2007.
Westra, S., Alexander, L. V., and Zwiers, F. W.: Global increasing trends in annual maximum daily precipitation, J. Climate, 26, 3904–3918, https://doi.org/10.1175/JCLI-D-12-00502.1, 2013.
Wu, H., Adler, R. F., Hong, Y., Tian, Y., and Policelli, F.: Evaluation of Global Flood Detection Using Satellite-Based Rainfall and a Hydrologic Model, J. Hydrometeorol., 13, 1268–1284, https://doi.org/10.1175/JHM-D-11-087.1, 2012.
Wu, H., Adler, R. F., Tian, Y., Huffman, G. J., Li, H., and Wang, J.: Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model, Water Resour. Res., 50, 2693–2717, https://doi.org/10.1002/2013WR014710, 2014.
Short summary
Multi-model analysis of global streamflow extremes for the 20th and 21st centuries under two warming scenarios is performed. About 37 and 43 % of global land areas show potential for increases in flood and drought events. Nearly 10 % of global land areas, holding around 30 % of world’s population, reflect a potentially worsening hazard of flood and drought. A significant increase in streamflow of the regions near and above the Arctic Circle, and decrease in subtropical arid areas, is projected.
Multi-model analysis of global streamflow extremes for the 20th and 21st centuries under two...
