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Estimating probable maximum loss from a Cascadia tsunami

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  • Dale Dominey-Howes
  • Paula Dunbar
  • Jesse Varner
  • Maria Papathoma-Köhle

Abstract

The Cascadia margin is capable of generating large magnitude seismic-tsunami. We use a 1:500 year tsunami hazard flood layer produced during a probabilistic tsunami hazard assessment as the input to a pilot study of the vulnerability of residential and commercial buildings in Seaside, OR, USA. We map building exposure, apply the Papathoma Tsunami Vulnerability Assessment Model to calculate building vulnerability and estimate probable maximum loss (PML) associated with a 1:500 year tsunami flood. Almost US$0.5 billion worth of buildings would be inundated, 95% of single story residential and 23% of commercial buildings would be destroyed with PML’s exceeding US$116 million. These figures only represent a tiny fraction of the total values of exposed assets and loss that would be associated with a Cascadia tsunami impacting the NW Pacific coast. Not withstanding the various issues associated with our approach, this study represents the first time that PML’s have ever been calculated for a Cascadia type tsunami, and these results have serious implications for tsunami disaster risk management in the region. This method has the potential to be rolled out across the United States and elsewhere for estimating building vulnerability and loss to tsunami. Copyright Springer Science+Business Media B.V. 2010

Suggested Citation

  • Dale Dominey-Howes & Paula Dunbar & Jesse Varner & Maria Papathoma-Köhle, 2010. "Estimating probable maximum loss from a Cascadia tsunami," 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. 53(1), pages 43-61, April.
  • Handle: RePEc:spr:nathaz:v:53:y:2010:i:1:p:43-61
    DOI: 10.1007/s11069-009-9409-9
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    References listed on IDEAS

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    1. H. Matsutomi & N. Shuto & F. Imamura & T. Takahashi, 2001. "Field Survey of the 1996 Irian Jaya Earthquake Tsunami in Biak Island," 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. 24(3), pages 199-212, November.
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    Cited by:

    1. Duygu Tufekci & Mehmet Lutfi Suzen & Ahmet Cevdet Yalciner & Andrey Zaytsev, 2018. "Revised MeTHuVA method for assessment of tsunami human vulnerability of Bakirkoy district, Istanbul," 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. 90(2), pages 943-974, January.
    2. Anawat Suppasri & Erick Mas & Ingrid Charvet & Rashmin Gunasekera & Kentaro Imai & Yo Fukutani & Yoshi Abe & Fumihiko Imamura, 2013. "Building damage characteristics based on surveyed data and fragility curves of the 2011 Great East Japan tsunami," 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. 66(2), pages 319-341, March.
    3. Teresa Vera San Martín & Gary Rodriguez Rosado & Patricia Arreaga Vargas & Leonardo Gutierrez, 2018. "Population and building vulnerability assessment by possible worst-case tsunami scenarios in Salinas, Ecuador," 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. 93(1), pages 275-297, August.
    4. Shima Madani & Saeedeh Khaleghi & Mahmood Reza Akbarpour Jannat, 2017. "Assessing building vulnerability to tsunami using the PTVA-3 model: A case study of Chabahar Bay, Iran," 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. 85(1), pages 349-359, January.
    5. Dane Wiebe & Daniel Cox, 2014. "Application of fragility curves to estimate building damage and economic loss at a community scale: a case study of Seaside, Oregon," 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. 71(3), pages 2043-2061, April.
    6. Chih-peng Wang & Ban-jwu Shih & Min-cheng Tu, 2022. "Study on the improvement of disaster resistance against tsunamis at Taiwan’s Keelung Port," 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. 110(3), pages 1507-1526, February.
    7. Aaron Opdyke & Desmond Chiang & Anthony Tsang & Jacob Smyth, 2022. "Benchmarking household storm surge risk perceptions to scientific models in the Philippines," 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. 114(2), pages 1285-1305, November.

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