In current practice, most earthquake risk models adopt a “declustered” view of seismicity, i.e. they disregard foreshock, aftershock and triggered earthquakes and model seismicity as a series of independent mainshock events, whose occurrence (typically) conforms to a Poisson process. This practice is certainly disputable but has been justified by the false notion that earthquakes of smaller magnitude than the mainshock cannot induce further damage than what was caused by the latter. A companion paper makes use of the epidemic-type aftershock sequence (ETAS) model fitted to Central Italy seismicity data to describe the full earthquake occurrence process including “dependent” earthquakes. Herein, loss estimates for the region of Umbria in Central Italy are derived using stochastic event catalogues generated by means of the ETAS model and damage-dependent fragility functions to track damage accumulation. The results are then compared with estimates obtained with a conventional Poisson-based model. The potential gains of utilizing a model capable of capturing the spatiotemporal clustering features of seismicity are illustrated along with a discussion on the various details and challenges of such considerations.

Exploring probabilistic seismic risk assessment accounting for seismicity clustering and damage accumulation: Part II. Risk analysis

Papadopoulos A;Bazzurro P
2020

Abstract

In current practice, most earthquake risk models adopt a “declustered” view of seismicity, i.e. they disregard foreshock, aftershock and triggered earthquakes and model seismicity as a series of independent mainshock events, whose occurrence (typically) conforms to a Poisson process. This practice is certainly disputable but has been justified by the false notion that earthquakes of smaller magnitude than the mainshock cannot induce further damage than what was caused by the latter. A companion paper makes use of the epidemic-type aftershock sequence (ETAS) model fitted to Central Italy seismicity data to describe the full earthquake occurrence process including “dependent” earthquakes. Herein, loss estimates for the region of Umbria in Central Italy are derived using stochastic event catalogues generated by means of the ETAS model and damage-dependent fragility functions to track damage accumulation. The results are then compared with estimates obtained with a conventional Poisson-based model. The potential gains of utilizing a model capable of capturing the spatiotemporal clustering features of seismicity are illustrated along with a discussion on the various details and challenges of such considerations.
clustered seismiciy; seismic hazard and risk, DAMAGE ACCUMULATION
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12076/7362
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