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Allowances for evolving coastal flood risk under uncertain local sea-level rise

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Listed:
  • Maya K. Buchanan

    (Princeton University)

  • Robert E. Kopp

    (Rutgers University)

  • Michael Oppenheimer

    (Princeton University
    Princeton University)

  • Claudia Tebaldi

    (National Center for Atmospheric Research (NCAR))

Abstract

Estimates of future flood hazards made under the assumption of stationary mean sea level are biased low due to sea-level rise (SLR). However, adjustments to flood return levels made assuming fixed increases of sea level are also inadequate when applied to sea level that is rising over time at an uncertain rate. SLR allowances—the height adjustment from historic flood levels that maintain under uncertainty the annual expected probability of flooding—are typically estimated independently of individual decision-makers’ preferences, such as time horizon, risk tolerance, and confidence in SLR projections. We provide a framework of SLR allowances that employs complete probability distributions of local SLR and a range of user-defined flood risk management preferences. Given non-stationary and uncertain sea-level rise, these metrics provide estimates of flood protection heights and offsets for different planning horizons in coastal areas. We illustrate the calculation of various allowance types for a set of long-duration tide gauges along U.S. coastlines.

Suggested Citation

  • Maya K. Buchanan & Robert E. Kopp & Michael Oppenheimer & Claudia Tebaldi, 2016. "Allowances for evolving coastal flood risk under uncertain local sea-level rise," Climatic Change, Springer, vol. 137(3), pages 347-362, August.
    • Handle: RePEc:spr:climat:v:137:y:2016:i:3:d:10.1007_s10584-016-1664-7
    DOI: 10.1007/s10584-016-1664-7
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    Cited by:

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    3. J. P. Palutikof & D. Rissik & S. Webb & Fahim N. Tonmoy & S. L. Boulter & Anne M. Leitch & A. C. Perez Vidaurre & M. J. Campbell, 2019. "CoastAdapt: an adaptation decision support framework for Australia’s coastal managers," Climatic Change, Springer, vol. 153(4), pages 491-507, April.
    4. Shao Sun & Zunya Wang & Chuanye Hu & Ge Gao, 2021. "Understanding Climate Hazard Patterns and Urban Adaptation Measures in China," Sustainability, MDPI, vol. 13(24), pages 1-12, December.
    5. Mohamed A. Abdelhafez & Hussam N. Mahmoud & Bruce R. Ellingwood, 2024. "Adjusting to the reality of sea level rise: reshaping coastal communities through resilience-informed adaptation," Climatic Change, Springer, vol. 177(7), pages 1-20, July.
    6. Ryan L Sriver & Robert J Lempert & Per Wikman-Svahn & Klaus Keller, 2018. "Characterizing uncertain sea-level rise projections to support investment decisions," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-35, February.
    7. D. J. Rasmussen & Scott Kulp & Robert E. Kopp & Michael Oppenheimer & Benjamin H. Strauss, 2022. "Popular extreme sea level metrics can better communicate impacts," Climatic Change, Springer, vol. 170(3), pages 1-17, February.
    8. Robert L. Ceres & Chris E. Forest & Klaus Keller, 2017. "Understanding the detectability of potential changes to the 100-year peak storm surge," Climatic Change, Springer, vol. 145(1), pages 221-235, November.
    9. Thomas David Pol & Jochen Hinkel, 2019. "Uncertainty representations of mean sea-level change: a telephone game?," Climatic Change, Springer, vol. 152(3), pages 393-411, March.
    10. Jesse M. Keenan & Jacob T. Bradt, 2020. "Underwaterwriting: from theory to empiricism in regional mortgage markets in the U.S," Climatic Change, Springer, vol. 162(4), pages 2043-2067, October.
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    12. Scott Kulp & Benjamin H. Strauss, 2017. "Rapid escalation of coastal flood exposure in US municipalities from sea level rise," Climatic Change, Springer, vol. 142(3), pages 477-489, June.

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