Incorporation of multivariate statistical distribution of magnitude-distance and Monte-Carlo simulation in probabilistic seismic hazard analysis

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Azarbakht, Alireza and Ebrahimi, Mohammad Ali (2019) Incorporation of multivariate statistical distribution of magnitude-distance and Monte-Carlo simulation in probabilistic seismic hazard analysis. Annals of Geophysics, 62. SE570. ISSN 1593-5213 (https://doi.org/10.4401/ag-7886)

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Abstract

The classical seismic hazard analysis is based on two independent simplified assumptions including the statistical distribution of magnitude (usually Gutenberg-Richter 1958) and the distance distribution (equal probability in each point of a given source). However, the interaction between the two distributions is rarely discussed in past researches. Therefore, a joint M-R distribution has been implemented in this paper in order to shed light into these simplified assumptions. The Tehran metropolis is considered as the case study since it locates in a highly active seismic region. Three seismological datasets were used in this study, i.e. the observed dataset, the simulated dataset based on the Han and Choi 2008 methodology, and the simulated dataset based on the EqHaz software platform. Then, the classical seismic hazard analysis results are compared with the results obtained based on the joint M-R distribution. The results show that the classical seismic hazard analysis is always conservative when compared with the results based on the simulated data.

ORCID iDs

Azarbakht, Alireza ORCID logoORCID: https://orcid.org/0000-0003-3627-652X and Ebrahimi, Mohammad Ali;
CORE (COnnecting REpositories)