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Incorporating uncertainty of future sea-level rise estimates into vulnerability assessment: A case study in Kahului, Maui

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  • Hannah Cooper
  • Qi Chen

Abstract

Accurate sea-level rise (SLR) vulnerability assessments are essential in developing effective management strategies for coastal systems at risk. In this study, we evaluate the effect of combining vertical uncertainties in Light Detection and Ranging (LiDAR) elevation data, datum transformation and future SLR estimates on estimating potential land area and land cover loss, and whether including uncertainty in future SLR estimates has implications for adaptation decisions in Kahului, Maui. Monte Carlo simulation is used to propagate probability distributions through our inundation model, and the output probability surfaces are generalized as areas of high and low probability of inundation. Our results show that considering uncertainty in just LiDAR and transformation overestimates vulnerable land area by about 3 % for the high probability threshold, resulting in conservative adaptation decisions, and underestimates vulnerable land area by about 14 % for the low probability threshold, resulting in less reliable adaptation decisions for Kahului. Not considering uncertainty in future SLR estimates in addition to LiDAR and transformation has variable effect on SLR adaptation decisions depending on the land cover category and how the high and low probability thresholds are defined. Monte Carlo simulation is a valuable approach to SLR vulnerability assessments because errors are not required to follow a Gaussian distribution. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Hannah Cooper & Qi Chen, 2013. "Incorporating uncertainty of future sea-level rise estimates into vulnerability assessment: A case study in Kahului, Maui," Climatic Change, Springer, vol. 121(4), pages 635-647, December.
    • Handle: RePEc:spr:climat:v:121:y:2013:i:4:p:635-647
    DOI: 10.1007/s10584-013-0987-x
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    References listed on IDEAS

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    1. Keqi Zhang & Yuepeng Li & Huiqing Liu & Hongzhou Xu & Jian Shen, 2013. "Comparison of three methods for estimating the sea level rise effect on storm surge flooding," Climatic Change, Springer, vol. 118(2), pages 487-500, May.
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    Cited by:

    1. Hannah Cooper & Caiyun Zhang & Donna Selch, 2015. "Incorporating uncertainty of groundwater modeling in sea-level rise assessment: a case study in South Florida," Climatic Change, Springer, vol. 129(1), pages 281-294, March.
    2. Haunani Kane & Charles Fletcher & L. Frazer & Tiffany Anderson & Matthew Barbee, 2015. "Modeling sea-level rise vulnerability of coastal environments using ranked management concerns," Climatic Change, Springer, vol. 131(2), pages 349-361, July.
    3. Javier X Leon & Gerard B M Heuvelink & Stuart R Phinn, 2014. "Incorporating DEM Uncertainty in Coastal Inundation Mapping," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-12, September.
    4. Pablo Fraile-Jurado & José I. Álvarez-Francoso & Emilia Guisado-Pintado & Noela Sánchez-Carnero & José Ojeda-Zújar & Stephen P. Leatherman, 2017. "Mapping inundation probability due to increasing sea level rise along El Puerto de Santa María (SW Spain)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 581-598, June.

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