Dynamic Updating of Building Loss Predictions Using Regional Risk Models and Conventional Post-Earthquake Data Sources
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Date
2021-09
Publication Type
Conference Paper
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yes
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Abstract
Earthquakes can cause widespread damage to the built environment, disrupt the function of many residential buildings to provide safe housing capacities and thus, potentially induce severe long-term societal consequences. Rapid recovery significantly improves the short-term resilience of communities after an earthquake. However, time pressure and scarce information on the severity and the spatial distribution of damage complicate the decision-making. Therefore, early damage estimates are produced using regional earthquake risk models with rapid earthquake intensity data and typological building vulnerability functions. While the precision of the former depends, amongst other issues, on the density of seismic network stations and the region-specific geological knowledge, the typological classification of buildings often involves attribution models correlating exposure data, such as building height and age, with typological seismic vulnerability classes. Typological attribution models are approximate and locally add to the uncertainties resulting from the average representation of buildings forming one building class. Employing probabilistic machine-learning tools, the continuous inspection data inflow is leveraged to dynamically update initial regional earthquake risk predictions by updating simultaneously the functions that govern typological attribution and building damage. Hence, while completing inspection of all affected buildings may take several weeks, the limited information becoming available in the first days following an earthquake helps constraining underlying uncertainties. This leads to more reliable rapid estimates of losses of building functions and their respective spatial distribution. The framework is demonstrated on a region in Switzerland subjected to a fictitious earthquake scenario.
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Publication status
published
Book title
Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)
Journal / series
Volume
Pages / Article No.
1411 - 1418
Publisher
Research Publishing Services
Event
31st European Safety and Reliability Conference (ESREL 2021)
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Methods
Software
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Date collected
Date created
Subject
Rapid loss assessment; Earthquake recovery; Spatial damage distribution; Typological building classification; Community resilience; Gaussian process
Organisational unit
03930 - Stojadinovic, Bozidar / Stojadinovic, Bozidar
03890 - Chatzi, Eleni / Chatzi, Eleni
Notes
Funding
821115 - Real-time Earthquake Risk Reduction for Europe (EC)