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Empirical tsunami fragility modelling for hierarchical damage levels

Jalayer, F; Ebrahimian, H; Trevlopoulos, K; Bradley, B; (2023) Empirical tsunami fragility modelling for hierarchical damage levels. Natural Hazards and Earth System Sciences , 23 (2) pp. 909-931. 10.5194/nhess-23-909-2023. Green open access

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Abstract

The present work proposes a simulation-based Bayesian method for parameter estimation and fragility model selection for mutually exclusive and collectively exhaustive (MECE) damage states. This method uses an adaptive Markov chain Monte Carlo simulation (MCMC) based on likelihood estimation using point-wise intensity values. It identifies the simplest model that fits the data best, among the set of viable fragility models considered. The proposed methodology is demonstrated for empirical fragility assessments for two different tsunami events and different classes of buildings with varying numbers of observed damage and flow depth data pairs. As case studies, observed pairs of data for flow depth and the corresponding damage level from the South Pacific tsunami on 29 September 2009 and the Sulawesi-Palu tsunami on 28 September 2018 are used. Damage data related to a total of five different building classes are analysed. It is shown that the proposed methodology is stable and efficient for data sets with a very low number of damage versus intensity data pairs and cases in which observed data are missing for some of the damage levels.

Type: Article
Title: Empirical tsunami fragility modelling for hierarchical damage levels
Open access status: An open access version is available from UCL Discovery
DOI: 10.5194/nhess-23-909-2023
Publisher version: https://doi.org/10.5194/nhess-23-909-2023
Language: English
Additional information: © Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Inst for Risk and Disaster Reduction
URI: https://discovery.ucl.ac.uk/id/eprint/10166984
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