High spatial-resolution loss estimation using dense array strong-motion near-fault records. Case study for Hveragerði and the Mw6.3 Ölfus earthquake, South Iceland

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Abstract

The most recent and costliest damaging earthquake in Iceland is the M w6.3 29-May-2008 Ölfus earthquake to date. In particular, Hveragerði town located in the extreme near-fault region, suffered intense horizontal peak ground accelerations (PGA) of ∼ 40–90%g and large amplitude and long-period near-fault pulses, recorded on a dense urban strong-motion array in the town. In this study we collated a high-spatial resolution exposure database (building-by-building) complete with actual reported losses and classified the buildings by building materials and construction year according to the code design requirements in place at the time. We took advantage of the array data and evaluated a set of well-known ground motion intensity measures (IM), including PGA, pseudo-acceleration response spectra at short-to-long periods, Arias Intensity and Cumulative Absolute Velocity. We applied empirical Bayesian kriging geostatistical analyses to generate high-resolution shakemaps and provide IM estimates for each building. The shakemaps showed a significant and systematic variation of the IMs across the small study area, with the lowest ground motions observed centrally and highest values in the outskirts. Furthermore, correlation analysis was carried out for the damage ratio and the exposure data IMs, but only low-to-moderate correlations were observed. A key reason is the incurred losses were primarily due to damage to non-structural components, to which the code design requirements do not apply. We carried out a seismic loss assessment in Hveragerði for the earthquake scenario of the Ölfus earthquake both on building-by-building, and municipality levels of spatial resolution. We applied both local and global fragility models associated with detail building typologies identified based on the SERA taxonomy scheme. The results show that the global fragility functions severely underestimate the seismic performance of the building stock, except for one-story reinforced concrete buildings, while overall the masonry buildings were associated with the most predicted and observed losses. On the other hand, the local models predicted losses that conformed well with the observed damages to timber and concrete buildings. The high-spatial-resolution predictions of losses gave results that better correlated with the observed losses in most typologies.

Original languageEnglish
Article number102894
JournalInternational Journal of Disaster Risk Reduction
Volume73
DOIs
Publication statusPublished - 15 Apr 2022

Bibliographical note

Funding Information:
This study was funded by the TURNkey H2020 European project (Towards more Earthquake-Resilient Urban Societies through a Multi-Sensor-Based Information System enabling Earthquake Forecasting, Early Warning and Rapid Response Actions) [ www.earthquake-turnkey.eu ] under grant agreement No 821046 . This work was facilitated by an Erasmus+ staff mobility grant No. IS-TS2020-87850 for the lead author to the University of Alicante, Spain . This work was also partly supported by a Postdoctoral fellowship (No. 218255-051 ) and grant of excellence (No. 218149-051 ) from the Icelandic Research Fund of the Icelandic Centre for Research , and the University of Iceland Research Fund . The authors thank the Natural Catastrophe Insurance of Iceland ( http://www.nti.is/en/ ) for providing the building damage database for the 2008 earthquake. Furthermore, we are grateful to the Registers Iceland ( https://www.skra.is/english/ ) for making the building properties database of Hveragerði available to the University of Iceland for the purposes of this research. The authors would like to acknowledge the anonymous reviewers who have contributed significantly to improving and enriching the paper.

Funding Information:
This study was funded by the TURNkey H2020 European project (Towards more Earthquake-Resilient Urban Societies through a Multi-Sensor-Based Information System enabling Earthquake Forecasting, Early Warning and Rapid Response Actions) [www.earthquake-turnkey.eu] under grant agreement No 821046. This work was facilitated by an Erasmus+ staff mobility grant No. IS-TS2020-87850 for the lead author to the University of Alicante, Spain. This work was also partly supported by a Postdoctoral fellowship (No. 218255-051) and grant of excellence (No. 218149-051) from the Icelandic Research Fund of the Icelandic Centre for Research, and the University of Iceland Research Fund. The authors thank the Natural Catastrophe Insurance of Iceland (http://www.nti.is/en/) for providing the building damage database for the 2008 earthquake. Furthermore, we are grateful to the Registers Iceland (https://www.skra.is/english/) for making the building properties database of Hverager?i available to the University of Iceland for the purposes of this research. The authors would like to acknowledge the anonymous reviewers who have contributed significantly to improving and enriching the paper.

Publisher Copyright:
© 2022 The Authors

Other keywords

  • Empirical Bayesian Kriging
  • Geostatistical analyses
  • Intensity measure variability
  • Loss estimation
  • Seismic risk assessment
  • South Iceland

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