Frequency-dependent site amplification functions for key geological units in Iceland from a Bayesian hierarchical model for earthquake strong-motions

Abstract

A fundamental modeling assumption in engineering seismology is that seismic ground motion is affected by source, propagation path and site effects. Contrary to the first two, comprehensive studies on site effects, the localized amplification effects on seismic ground motion due to the uppermost geological structure, have been limited in Iceland. As a result, site amplification has been modeled in ground motion models in a simplistic and qualitative way. In this study, we address this limitation by using the new Bayesian hybrid GMM proposed by Kowsari et al. (2020) to model the recorded ground motions at regional strong-motion stations in southwest Iceland, specifically the peak ground acceleration and pseudo-acceleration response spectra as a function of oscillator period (i.e., PGA and PSA at T=0.01-3.0 s), earthquake magnitude, distance and hypocentral depth, and at first, we omit a site-term. Then, we incorporate the GMM in a Bayesian Hierarchical Model (BHM) that allows prior distributions of model parameters to be used and we partition the model residuals into various terms associated with the source, propagation path and station terms. Through Bayesian inference of the model parameters the results show that the station term residuals reveal a frequency-dependent site amplification at the recording sites. By inspecting this systematic behaviour, we propose four groups of station terms by their characteristics. We then carefully inspect the station locations in terms of their associated geological unit and observe that the geological units and station term groups are qualitatively correlated. By combining the two, we propose the first frequency-dependent average site amplification functions associated with key geological units in Iceland based on age and formation. Provisionally we refer to them as hard rock, rock, (Holocene) lava rock, and (unspecified) soil site classes, respectively. We then update the GMM by incorporating these amplification functions so that it now enables the prediction of PGA and PSA at these four site classes. As a result, the new model standard deviations are considerably lower, with those associated with the event term being τ = 0.05, station terms φS2S = 0.10, intra-event φ = 0.17 and total σ = 0.18 in common logarithm units for PGA. The new site class-specific GMM now enables the site-specific ground motion for separate geological units which in turn improves site-specific seismic hazard assessment and informed site-specific engineering decision making in Iceland.