Influence of Elevation Data Resolution on Tsunami Loss Estimation and Insurance Rate-Making

Jie Song, Katsuichiro Goda*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

21 Citations (Scopus)
151 Downloads (Pure)

Abstract

Tsunamis triggered by large offshore earthquakes are devastating, and buildings located near the coast experience damage and loss due to such extreme events. In evaluating regional tsunami impact via numerical tsunami simulations, it is important to pay close attention to local geographical features represented by a digital elevation model (DEM), because tsunami loss estimation is sensitive to its quality and resolution. This study investigates the influence of elevation data resolution on tsunami loss estimation at different scales by comparing tsunami risk results using DEMs of four resolutions (i.e., 10-m, 50-m, 150-m, and 450-m). Using stochastic tsunami modeling, a case study is carried out by focusing on the Tohoku region in Japan to investigate the influence of DEM resolution on tsunami loss estimation considering the effect of location attributes (i.e., coastal topography, distance from the coast, and land elevation) for two building portfolios on plain coast and ria coast. The results indicate the significance of DEM resolution for local tsunami loss estimations at different locations. The local tsunami risk is closely related to the building location, and the increase of distance from the coast and/or land elevation dramatically reduces the local tsunami risk. The investigations extend discussions regarding the calculations of pure insurance premium rate for tsunami loss coverage depending upon structural attributes and location attributes.

Original languageEnglish
Article number246
Number of pages19
JournalFrontiers in Earth Science
Volume7
DOIs
Publication statusPublished - 18 Sept 2019

Keywords

  • elevation data resolution
  • insurance rate-making
  • probabilistic tsunami loss estimation
  • rate differentiation
  • stochastic tsunami simulation

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