Impact of future tsunamis from the Java trench on household welfare: Merging geophysics and economics through catastrophe modelling

Dimitra M. Salmanidou, Ayao Ehara, Rozana Himaz, Mohammad Heidarzadeh, Serge Guillas

Research output: Contribution to journalArticlepeer-review

13 Citations (SciVal)


This paper presents the first end-to-end example of a risk model for loss of assets in households due to possible future tsunamis. There is a significant need for Government to assess the generic risk to buildings, and the concrete impact on the full range of assets of households, including the ones that are key to livelihoods such as agricultural land, fishing boats, livestock and equipment. Our approach relies on the Oasis Loss Modelling Framework to integrate hazard and risk. We first generate 25 representative events of tsunamigenic earthquakes off the Southern coast of Java, Indonesia. We then create a new vulnerability function based upon the Indonesian household survey STAR1 of how much assets have been reduced in each household after the 2004 tsunami. We run a multinomial logit regression to precisely allocate the probabilistic impacts to bins that correspond with levels of financial reduction in assets. We focus on the town of Cilacap for which we build loss exceedance curves, which represent the financial losses that may be exceeded at a range of future timelines, using future tsunami inundations over a surveyed layout and value of assets over the city. Our loss calculations show that losses increase sharply, especially for events with return periods beyond 250 years. These series of computations will allow more accurate investigations of impacts on livelihoods and thus will help design mitigation strategies as well as policies to minimize suffering from tsunamis.

Original languageEnglish
Article number102291
Number of pages15
JournalInternational Journal of Disaster Risk Reduction
Early online date14 May 2021
Publication statusPublished - 1 Jul 2021

Bibliographical note

Funding Information:
*We acknowledge funding from the Lloyd's Tercentenary Research Foundation, the Lighthill Risk Network and the Lloyd's Register Foundation-Data Centric Engineering Programme of the Alan Turing Institute. We also acknowledge support from the Alan Turing Institute project “Uncertainty Quantification of multi-scale and multiphysics computer models: applications to hazard and climate models” as part of the grant EP/N510129/1 made to the Alan Turing Institute by EPSRC. MH was partly funded by the Royal Society, the United Kingdom, grant number CHL/R1/180173. We thank four anonymous reviewers for their thorough review and insightful comments.

Publisher Copyright:
© 2021 The Author(s)


  • Disaster risk finance
  • Indonesia
  • Insurance
  • Natural disasters
  • Risk modelling
  • Vulnerability

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Safety Research
  • Geology


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