IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v104y2020i1d10.1007_s11069-020-04201-7.html
   My bibliography  Save this article

Exploring the impact of epistemic uncertainty on a regional probabilistic seismic risk assessment model

Author

Listed:
  • Petros Kalakonas

    (University School for Advanced Studies (IUSS))

  • Vitor Silva

    (Global Earthquake Model Foundation (GEM))

  • Amaryllis Mouyiannou

    (Partner Re)

  • Anirudh Rao

    (Global Earthquake Model Foundation (GEM))

Abstract

Probabilistic earthquake loss models are widely used in the (re)insurance industry to assess the seismic risk of portfolios of assets and to inform pricing mechanisms for (re)insurance contracts, as well as by international and national organizations with the remit to assess and reduce disaster risk. Such models include components characterizing the seismicity of the region, the ground motion intensity, the building inventory, and the vulnerability of the assets exposed to ground shaking. Each component is characterized by a large uncertainty, which can be classified as aleatory or epistemic. Modern seismic risk assessment models often neglect some sources of uncertainty, which can lead to biased loss estimates or to an underestimation of the existing uncertainty. This study focuses on exploring and quantifying the impact of a number of sources of uncertainties from each component of an earthquake loss model to the loss estimates. To this end, the residential exposure of Guatemala and Guatemala City were used as case studies. Moreover, a comparison of the predicted losses for an insured portfolio in the country between OpenQuake-engine and a vendor catastrophe platform was performed, assessing the potential application of OpenQuake in the (re)insurance industry. The findings from this study suggest that the uncertainty in the hazard component has the most significant effect on the loss estimates.

Suggested Citation

  • Petros Kalakonas & Vitor Silva & Amaryllis Mouyiannou & Anirudh Rao, 2020. "Exploring the impact of epistemic uncertainty on a regional probabilistic seismic risk assessment model," 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. 104(1), pages 997-1020, October.
    • Handle: RePEc:spr:nathaz:v:104:y:2020:i:1:d:10.1007_s11069-020-04201-7
    DOI: 10.1007/s11069-020-04201-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-04201-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-020-04201-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jamal Dabbeek & Vitor Silva, 2020. "Modeling the residential building stock in the Middle East for multi-hazard risk assessment," 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. 100(2), pages 781-810, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sreevalsa Kolathayar, 2021. "Recent seismicity in Delhi and population exposure to seismic hazard," 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. 109(3), pages 2621-2648, December.
    2. André Hartmann & Martin Behnisch & Robert Hecht & Gotthard Meinel, 2024. "Prediction of residential and non-residential building usage in Germany based on a novel nationwide reference data set," Environment and Planning B, , vol. 51(1), pages 216-233, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:104:y:2020:i:1:d:10.1007_s11069-020-04201-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.