Capabilities of the Bayesian Probabilistic Networks Approach for Earthquake Risk Management

Authors

Yahya Y. Bayraktarli, Ufuk Yazgan, Alessandro Dazio and Michael H. Faber

Abstract

The present paper considers large-scale risk based decision making in regard to management of earthquake hazards. First an outline is given on existing methodologies on management of earthquake hazards in terms of capabilities and shortcomings. Thereafter a recently developed generic risk assessment framework is introduced which takes basis in a system representation through exposures, direct and indirect consequences as well as vulnerability and robustness. The framework is fully generic in the sense that the characteristics of the system are formulated in terms of risk indicators which may be specified in accordance with the available information concerning a given system. Furthermore, the framework is fully Bayesian such that probabilistic models and consequently also the risk assessments can be updated based on new information of relevance for the decision making. This in turns allows for considering the different decision situations, before, during and after an earthquake takes place, subject to the available information in the different situations. The basic properties of Bayesian Probabilistic Networks (BPN) are shortly introduced. Taking basis in previously developed BPN based risk assessment tools for vulnerability analysis of structures and soil, the presented framework is then illustrated through an example where a risk based decision analysis on possible retrofitting or rebuilding of building structures in a larger part of a city is performed for the two different situations - before and after an earthquake.

Published by/in

First European Conference on Earthquake Engineering and Seismology (a joint event of the 13th ECEE & 30th General Assembly of the ESC) Geneva, Switzerland, 3-8 September 2006, Paper Number: 1458