Climatic Change

, Volume 113, Issue 3–4, pp 919–931 | Cite as

Simplified method for scenario-based risk assessment adaptation planning in the coastal zone

  • Paul KirshenEmail author
  • Samuel Merrill
  • Peter Slovinsky
  • Norman Richardson


The development of successful coastal adaptation strategies for both the built and natural environments requires combining scenarios of climate change and socio-economic conditions, and risk assessment. Such planning needs to consider the adaptation costs and residual damages over time that may occur given a range of possible storm conditions for any given sea level rise scenario. Using the metric of the expected value of annual adaptation costs and residual damages, or another metric that can be related to the elevation of flooding, a simplified method to carry this out is presented. The approach relies upon developing damage-flooding depth probability exceedance curves for various scenarios over a given planning period and determining the areas under the curves. While the approach does have limitations, it is less complex to implement than using Monte Carlo simulation approaches and may be more intuitive to decision makers. A case study in Maine, USA is carried out to illustrate the method.


Storm Surge Climate Change Scenario Adaptation Option Coastal Flooding Beach Nourishment 
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.



We have enjoyed working on the application of this methodology with James Neumann, John Herter, and Caroleen Verly of Industrial Economics, Inc., and also appreciate the use of their tools in data analysis. Gary Lamb of Old Orchard Beach and J.T. Lockman of the Southern Maine Regional Planning Commission are acknowledged for their preliminary review of this methodology. The first author also acknowledges the opportunity to explore risk analysis while UCOWR Visiting Scholar at the US Army Corps of Engineers Institute for Water Resources. The paper has been improved by the comments of the anonymous reviewers.

Research described in this paper has been funded by the US Environmental Protection Agency in grant funding provided to the Environmental Finance Center at the University of Southern Maine; however this paper has not been subjected to the Agency’s required peer and policy review and therefore does not necessarily reflect views of the Agency and no official endorsement should be inferred.


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Paul Kirshen
    • 1
    Email author
  • Samuel Merrill
    • 2
  • Peter Slovinsky
    • 3
  • Norman Richardson
    • 4
  1. 1.University of New HampshireDurhamUSA
  2. 2.US EPA Region 1 Environmental Finance Center at the Muskie School of Public ServiceUniversity of Southern MainePortlandUSA
  3. 3.Department of ConservationMaine Geological SurveyAugustaUSA
  4. 4.Battelle Memorial InstituteLexingtonUSA

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