Letter | Published:

Global flood risk under climate change

Nature Climate Change volume 3, pages 816821 (2013) | Download Citation


A warmer climate would increase the risk of floods1. So far, only a few studies2,3 have projected changes in floods on a global scale. None of these studies relied on multiple climate models. A few global studies4,5 have started to estimate the exposure to flooding (population in potential inundation areas) as a proxy of risk, but none of them has estimated it in a warmer future climate. Here we present global flood risk for the end of this century based on the outputs of 11 climate models. A state-of-the-art global river routing model with an inundation scheme6 was employed to compute river discharge and inundation area. An ensemble of projections under a new high-concentration scenario7 demonstrates a large increase in flood frequency in Southeast Asia, Peninsular India, eastern Africa and the northern half of the Andes, with small uncertainty in the direction of change. In certain areas of the world, however, flood frequency is projected to decrease. Another larger ensemble of projections under four new concentration scenarios7 reveals that the global exposure to floods would increase depending on the degree of warming, but interannual variability of the exposure may imply the necessity of adaptation before significant warming.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    IPCC Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (eds Field, C. B. et al.) (Cambridge Univ. Press, 2012).

  2. 2.

    , , & Increasing risk of great floods in a changing climate. Nature 415, 514–517 (2002).

  3. 3.

    , , , & Global projections of changing risks of floods and droughts in a changing climate. Hydrol. Sci. J. 53, 754–772 (2008).

  4. 4.

    , & Global exposure to river and coastal flooding: Long term trends and changes. Glob. Environ. Change 22, 823–835 (2012).

  5. 5.

    , , & Assessing global exposure and vulnerability towards natural hazards: The Disaster Risk Index. Nat. Hazards Earth Syst. Sci. 9, 1149–1159 (2009).

  6. 6.

    , , & A physically based description of floodplain inundation dynamics in a global river routing model. Wat. Resour. Res. 47, W04501 (2011).

  7. 7.

    et al. The representative concentration pathways: an overview. Climatic Change 109, 5–31 (2011).

  8. 8.

    et al. in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (eds Field, C. B. et al.) 109–230 (Cambridge Univ. Press, 2012).

  9. 9.

    et al. The WCRP CMIP3 multimodel dataset: A new era in climate change research. Bull. Am. Meteorol. Soc. 88, 1383–1394 (2007).

  10. 10.

    , & An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2011).

  11. 11.

    et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

  12. 12.

    & Climate change impact on flood hazard in Europe: An assessment based on high-resolution climate simulations. J. Geophys. Res. 113, D19105 (2008).

  13. 13.

    , , & Role of rivers in the seasonal variations of terrestrial water storage over global basins. Geophys. Res. Lett. 36, L17402 (2009).

  14. 14.

    , , , & Estimating the impact of global change on flood and drought risks in Europe: A continental, integrated analysis. Climatic Change 75, 273–299 (2006).

  15. 15.

    & First estimate of the future global population at risk of flooding. Hydrol. Res. Lett. 3, 6–9 (2009).

  16. 16.

    UN Population Division World Population Prospects: The 2011 Revision (United Nations, 2011).

  17. 17.

    & A variable velocity flow routing algorithm for GCMs. J. Geophys. Res. 104, 30965–30979 (1999).

  18. 18.

    et al. Analysis of the water level dynamics simulated by a global river model: A case study in the Amazon River. Wat. Resour. Res. 48 (in the press, 2012).

  19. 19.

    The return period of flood flows. Ann. Math. Stat. 12, 163–190 (1941).

  20. 20.

    & Regional Frequency Analysis: An Approach Based on L-moments (Cambridge Univ. Press, 1997).

  21. 21.

    The probability plot correlation coefficient test for the normal, lognormal and Gumbel distributional hypotheses. Wat. Resour. Res. 22, 587–590 (1986).

Download references


This paper was financially supported by the Funding Program for Next-Generation World-Leading Researchers, Japan Society for the Promotion of Science, CREST of Japan Science and Technology Agency, and the Environmental Research and Technology Development Fund (S-10, ICA-RUS) of the Ministry of the Environment, Japan. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Author information


  1. Institute of Engineering Innovation, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-8656, Japan

    • Yukiko Hirabayashi
    • , Roobavannan Mahendran
    • , Sujan Koirala
    • , Lisako Konoshima
    •  & Satoshi Watanabe
  2. School of Geographical Sciences, University of Bristol, University Road, Clifton, Bristol BS8 1SS, UK

    • Dai Yamazaki
  3. Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan

    • Hyungjun Kim
  4. Department of Civil Engineering, Tokyo Institute of Technology, 2-12-1 O-okayama, Meguro-ku, Tokyo 152-8552, Japan

    • Shinjiro Kanae


  1. Search for Yukiko Hirabayashi in:

  2. Search for Roobavannan Mahendran in:

  3. Search for Sujan Koirala in:

  4. Search for Lisako Konoshima in:

  5. Search for Dai Yamazaki in:

  6. Search for Satoshi Watanabe in:

  7. Search for Hyungjun Kim in:

  8. Search for Shinjiro Kanae in:


R.M., S. Koirala, D.Y. and H.K. carried out the simulation and analysis. L.K. and S. Koirala carried out the exposure estimation. S.W. contributed to the data archive. Y.H. and S. Kanae designed the research. Y.H., S. Koirala and S. Kanae co-wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Yukiko Hirabayashi or Shinjiro Kanae.

Supplementary information

About this article

Publication history






Further reading