Climatic Change

, Volume 117, Issue 4, pp 783–794 | Cite as

The effects of adaptation and mitigation on coastal flood impacts during the 21st century. An application of the DIVA and IMAGE models

  • Jochen Hinkel
  • Detlef P. van Vuuren
  • Robert J. Nicholls
  • Richard J. T. Klein


This paper studies the effects of mitigation and adaptation on coastal flood impacts. We focus on a scenario that stabilizes concentrations at 450 ppm-CO2-eq leading to 42 cm of global mean sea-level rise in 1995–2100 (GMSLR) and an unmitigated one leading to 63 cm of GMSLR. We also consider sensitivity scenarios reflecting increased tropical cyclone activity and a GMSLR of 126 cm. The only adaptation considered is upgrading and maintaining dikes. Under the unmitigated scenario and without adaptation, the number of people flooded reaches 168 million per year in 2100. Mitigation reduces this number by factor 1.4, adaptation by factor 461 and both options together by factor 540. The global annual flood cost (including dike upgrade cost, maintenance cost and residual damage cost) reaches US$ 210 billion per year in 2100 under the unmitigated scenario without adaptation. Mitigation reduces this number by factor 1.3, adaptation by factor 5.2 and both options together by factor 7.8. When assuming adaptation, the global annual flood cost relative to GDP falls throughout the century from about 0.06 % to 0.01–0.03 % under all scenarios including the sensitivity ones. From this perspective, adaptation to coastal flood impacts is meaningful to be widely applied irrespective of the level of mitigation. From the perspective of a some less-wealthy and small island countries, however, annual flood cost can amount to several percent of national GDP and mitigation can lower these costs significantly. We conclude that adaptation and mitigation are complimentary policies in coastal areas.


Tropical Cyclone Shuttle Radar Topography Mission Coastal Flood Mitigation Cost Small Island Develop States 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work has been supported by the ADAM project funded by the European Commission’s Directorate-General Research from March 2006 to July 2009 (project reference: 18476). We thank Richard Tol, Lars Exner, Andries Hof, Morna Isaac as well as two anonymous reviewers for their support and very helpful comments on earlier versions of this paper.


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Jochen Hinkel
    • 1
    • 2
  • Detlef P. van Vuuren
    • 3
    • 4
  • Robert J. Nicholls
    • 5
  • Richard J. T. Klein
    • 6
    • 7
  1. 1.Global Climate Forum (GCF)BerlinGermany
  2. 2.Potsdam Institute for Climate Impact ResearchPotsdamGermany
  3. 3.Department of GeosciencesNetherlands Environmental Assessment Agency (PBL)BilthovenThe Netherlands
  4. 4.Utrecht UniversityUtrechtThe Netherlands
  5. 5.Faculty of Engineering and the Environment and Tyndall Centre for Climate Change ResearchUniversity of SouthamptonSouthamptonUK
  6. 6.Stockholm Environment InstituteStockholmSweden
  7. 7.Centre for Climate Science and Policy Research and Department of Thematic StudiesLinköping UniversityLinköpingSweden

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