A Bayesian Methodology Applied to the Estimation of Earthquake Recurrence Parameters for Seismic Hazard Assessment

Seismic hazard curves provide the rate (or probability) of exceedance of different levels of a ground motion parameter (e.g., the peak ground acceleration, PGA) in a given geographical point and for a given time frame. Hence, to evaluate seismic hazard curves, one needs an occurrence model of earthquakes and an attenuation law of the ground motion with the distance. Generally, the input data needed to define the occurrence model consists in values of the magnitude, experimentally observed or, in the case of ancient earthquakes, indirectly inferred based on historically recorded damages. In this paper, we sketch a full Bayesian methodology for estimating the parameters characterizing the seismic activity in pre‐determined seismotectonical zones, given such a catalog of recorded magnitudes. The statistical model, following the peak over threshold formalism, consists in the distribution of the annual number of earthquakes exceeding a given magnitude, coupled with the probability density of the magnitudes, given that they exceed the threshold. Then, as an example of the possible applications of the proposed methodology, the PGA is evaluated in several sites of interest, while taking into account the uncertainty tainting the parameters of the magnitudes' distribution in several seismotectonical zones and the attenuation law. Finally, some perspectives are sketched.