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

Abstract

Probabilistic seismic hazard analysis (PSHA), as a tool to assess the probability that ground motion of a given intensity or larger is experienced at a given site and time span, has historically comprised the basis of both building design codes in earthquake-prone regions and seismic risk models. The PSHA traditionally refers solely to mainshock events and typically employs a homogeneous Poisson process to model their occurrence. Nevertheless, recent disasters, such as the 2010–2011 Christchurch sequence or the 2016 Central Italy earthquakes, to name a few, have highlighted the potential pitfalls of neglecting the occurrence of foreshocks, aftershocks, and other triggered events, and pinpointed the need to revisit the current practice. Herein, we employ the epidemic-type aftershock sequence (ETAS) model to describe seismicity in Central Italy, investigate the model’s capability to reproduce salient features of observed seismicity, and compare ETAS-derived one-year hazard estimates with ones obtained with a standard mainshock-only Poisson-based hazard model. A companion paper uses the hazard models derived herein to compare and contrast loss estimates for the residential exposure of Umbria in Central Italy.

The new Italian seismic hazard model (MPS19)

“…In MPS19 we use GK74 declustering technique, because it is the most efficient procedure to get a mainshocks distribution similar to Poisson distribution (see Section 3). No matter of the declustering method used, this operation implies that strong ground shaking caused by aftershocks and foreshocks is not considered in classical PSHA [Boyd, 2012;Iervolino et al, 2012;Marzocchi and Taroni, 2014] and risk [Papadopoulos et al, 2020]. For this reason, we build a version of MPS19 which includes the effects of earthquake clustering (hereafter MPS19_cluster) and allows us to quantify its impact in terms of seismic hazard.…”

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

“…As already pointed out, the seismic hazard component employed here is modeled through the space–time ETAS model. As explained in Papadopoulos et al (in press) but reported here for convenience, the latter is a self-exciting point process (Hawkes, 1971) essentially based on the principle that each earthquake can trigger its own offspring. The conditional intensity, that is, the infinitesimal expected occurrence rate at a specific point in space and time, according to the ETAS model can generally be formulated as follows:…”

“…As discussed in the companion paper (Papadopoulos et al, in press), fixing the parameter α equal to β in the ETAS model (as done for the second, fourth, fifth, and sixth ETAS parameterizations in Table 1) compensates for some sources of bias but may occasionally result in unrealistic sequence realizations. Within the context of operational earthquake forecasting, where the ETAS model has been heavily used, this might not be important, given that the main product is daily predictions of the number of earthquakes, typically given as a mean/median point estimate along with a confidence interval (both of which are not overly affected by the extreme tails of the distribution).…”

“…Herein, an investigation of the effects of seismicity clustering on regional loss estimates is carried out by means of employing a representation of seismicity based on the ETAS model that goes beyond the limitations of its Poissonian counterpart. As a case study, the region of Umbria in Central Italy is selected and loss estimates are obtained for its residential building stock through ETAS- and Poisson-based seismic hazard components, developed based on a local seismicity catalog and described in a companion paper (Papadopoulos et al, in press). Furthermore, an attempt to incorporate the effects of damage accumulation is made by developing and employing a set of damage-dependent fragility functions derived through equivalent single degree-of-freedom (ESDOF) systems representative of prominent classes within the testbed region of Umbria.…”

Modelling and quantifying tomorrow's risks from natural hazards

“…A comprehensive review of these methods is provided in Iacoletti et al (2021). Short-term time-dependent seismic hazard assessments account for the spatial and temporal clustering of aftershock events that follow the occurrence of a J o u r n a l P r e -p r o o f Journal Pre-proof mainshock earthquake (e.g., Papadopoulos et al, 2020).…”