Incorporation of Multivariate Statistical Distribution of Magnitude-Distance and Monte-Carlo Simulation in Probabilistic Seismic Hazard Analysis

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Alireza Azarbakht
https://orcid.org/0000-0003-3627-652X
Mohamad Ali Ebrahimi
https://orcid.org/0000-0003-4947-180X

Abstract

The classical seismic hazard analysis is based on two independent simpli ed assumptions including the statistical distribution of mag- nitude (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 simpli ed assumptions. The Tehran metropolis is considered as the case study since it lo- cates 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 clas- sical 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.

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How to Cite
Azarbakht, A. and Ebrahimi, M. A. (2020) “Incorporation of Multivariate Statistical Distribution of Magnitude-Distance and Monte-Carlo Simulation in Probabilistic Seismic Hazard Analysis”, Annals of Geophysics, 62(5), p. SE570. doi: 10.4401/ag-7886.
Section
Seismology