PGA and PGV Spatial Correlation Models Based on European Multievent Datasets

Abstract

Spatial modeling of ground motion intensity measures (IMs) is required for risk assessment of spatially distributed engineering systems. For example, when a lifeline system is of concern, classical site-specific hazard tools, which treat IMs at different locations independently, may not be adequate to accurately assess the seismic risk. In fact, in this case, modeling of ground motion as a random field is required; it basically consists of assigning a correlation structure to the IM of interest. This work focuses on semiempirical estimation of the correlation coefficient, as a function of intersite separation distance, between residuals with respect to ground motion prediction equations (GMPEs) of horizontal peak ground acceleration (PGA) and peak ground velocity (PGV). In particular, subsets of the European Strong-Motion Database (ESD) and the Italian Accelerometric Archive (ITACA) were employed to evaluate the intraevent residual correlation based on multiple earthquakes, considering different GMPEs fitted to the same records. The analyses were carried out through geostatistical tools, which enabled results to be found that are generally consistent between the two datasets. Correlation for PGV appears to attenuate more gradually with respect to PGA. In order to better understand the dependency of the results on the adopted estimation approach and dataset, some aspects related to the working hypotheses are critically discussed. Finally, estimated correlation models are used to develop illustrative applications of regional probabilistic seismic-hazard analysis.

Systemic Vulnerability and Risk Assessment of Transportation Systems Under Natural Hazards Towards More Resilient and Robust Infrastructures

“…The ground motion prediction equation (GMPE) introduced by Akkar and Bommer (2010) is applied for the estimation of the ground motion parameters on rock. The spatial variability for PGA is modeled using the correlation models provided by Jayaram and Baker (2009) as adapted for European events consistently with the selected GMPE (Esposito and Iervolino, 2011). The primary IM is then retrieved at vulnerable sites by distance-based interpolation and finally the local IM is sampled conditionally on primary IM.…”

Earthquake Risk Assessment: Present Shortcomings and Future Directions

“…Many researchers (e.g. Wang and Takada 2005;Goda and Hong 2008;Jayaram and Baker 2009;Esposito and Iervolino 2011) have shown that the intra-event residuals at two different sites for a given event are correlated, as a function of their separation distance -the greater the distance, the lower the correlation between the residuals. Hence, when modelling distributed ground motions for a future potential scenario earthquake, a sample of the interevent residual/epsilon for the event should be made and then this should be combined (through SRSS) with the intra-event residual/epsilon at each site, which should be obtained by employing a model of spatial correlation of the intra-event residuals (see e.g.…”

Seismic vulnerability analysis of a complex interconnected civil infrastructure

“…Both simulation of PGA and the conditional simulation of PGV are carried out using the GMPE by Akkar and Bommer (2010), recently developed for the European context. Spatial correlation with correlation parameter (range) is estimated based on European records by Esposito et al (2010). For within-site cross-IM correlation ρ PGA,PGV = 0.754 is used.…”