Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models
- In seismic risk assessment, the sources of uncertainty associated with building exposure modelling have not received as much attention as other components related to hazard and vulnerability. Conventional practices such as assuming absolute portfolio compositions (i.e., proportions per building class) from expert-based assumptions over aggregated data crudely disregard the contribution of uncertainty of the exposure upon earthquake loss models. In this work, we introduce the concept that the degree of knowledge of a building stock can be described within a Bayesian probabilistic approach that integrates both expert-based prior distributions and data collection on individual buildings. We investigate the impact of the epistemic uncertainty in the portfolio composition on scenario-based earthquake loss models through an exposure-oriented logic tree arrangement based on synthetic building portfolios. For illustrative purposes, we consider the residential building stock of Valparaiso (Chile) subjected to seismic ground-shaking from oneIn seismic risk assessment, the sources of uncertainty associated with building exposure modelling have not received as much attention as other components related to hazard and vulnerability. Conventional practices such as assuming absolute portfolio compositions (i.e., proportions per building class) from expert-based assumptions over aggregated data crudely disregard the contribution of uncertainty of the exposure upon earthquake loss models. In this work, we introduce the concept that the degree of knowledge of a building stock can be described within a Bayesian probabilistic approach that integrates both expert-based prior distributions and data collection on individual buildings. We investigate the impact of the epistemic uncertainty in the portfolio composition on scenario-based earthquake loss models through an exposure-oriented logic tree arrangement based on synthetic building portfolios. For illustrative purposes, we consider the residential building stock of Valparaiso (Chile) subjected to seismic ground-shaking from one subduction earthquake. We have found that building class reconnaissance, either from prior assumptions by desktop studies with aggregated data (top-down approach), or from building-by-building data collection (bottom-up approach), plays a fundamental role in the statistical modelling of exposure. To model the vulnerability of such a heterogeneous building stock, we require that their associated set of structural fragility functions handle multiple spectral periods. Thereby, we also discuss the relevance and specific uncertainty upon generating either uncorrelated or spatially cross-correlated ground motion fields within this framework. We successively show how various epistemic uncertainties embedded within these probabilistic exposure models are differently propagated throughout the computed direct financial losses. This work calls for further efforts to redesign desktop exposure studies, while also highlighting the importance of exposure data collection with standardized and iterative approaches.…
Author details: | Juan Camilo Gomez-ZapataORCiDGND, Massimiliano PittoreORCiD, Fabrice CottonORCiDGND, Henning LilienkampORCiDGND, Simantini Shinde, Paula Aguirre, Hernan Santa Maria |
---|---|
DOI: | https://doi.org/10.1007/s10518-021-01312-9 |
ISSN: | 1570-761X |
ISSN: | 1573-1456 |
Title of parent work (English): | Bulletin of Earthquake Engineering |
Publisher: | Springer |
Place of publishing: | Dordrecht |
Publication type: | Article |
Language: | English |
Date of first publication: | 2022/01/20 |
Publication year: | 2022 |
Release date: | 2024/05/29 |
Tag: | Data collection; Earthquake loss modelling; Earthquake scenario; Epistemic uncertainty; Faceted taxonomy; Probabilistic exposure modelling; Scheme; Sensitivity analysis; Spatially cross-correlated ground motion; fields |
Volume: | 20 |
Issue: | 5 |
Number of pages: | 38 |
First page: | 2401 |
Last Page: | 2438 |
Remarks: | Update notice Correction to: Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models (Bulletin of Earthquake Engineering, (2022), 20, 5, (2401-2438), https://doi.org/10.1007/s10518-021-01312-9) Bulletin of Earthquake Engineering, Volume 20, Issue 5, Pages 2439, March 2022, https://doi.org/10.1007/s10518-022-01340-z |
Funding institution: | Projekt DEAL; German Federal Ministry of Education and Research (BMBF); [03G0876A-J, 03G0905A-H]; Helmholtz Einstein International Berlin; Research School in Data Science (HEIBRiDS); Research Center for; Integrated Disaster Risk Management (CIGIDEN) [ANID/FONDAP/15110017,; ANID-FONDECYT 1191543] |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |
Publishing method: | Open Access / Hybrid Open-Access |
License (German): | CC-BY - Namensnennung 4.0 International |
External remark: | Correction to: https://link.springer.com/article/10.1007/s10518-022-01340-z |