CyberShake Earthquake Fault Rupture Modeling and Ground Motion Simulations for the Southwest Iceland Transform Zone

TL;DR

This study applies CyberShake, a high-performance seismic hazard assessment workflow, to simulate ground motions in Southwest Iceland, validating its effectiveness and generating data for regions with limited empirical seismic records.

Contribution

It adapts and validates the CyberShake physics-based seismic hazard modeling approach for the Southwest Iceland transform zone using synthetic fault rupture simulations.

Findings

Synthetic GM results agree well with Icelandic strong-motion data.

Most simulations fall within one standard deviation of GMPE predictions.

CS dataset can inform future seismic hazard assessments in data-scarce regions.

Abstract

CyberShake (CS) is a high-performance computing workflow for Probabilistic Seismic Hazard Assessment (PSHA) developed by the Statewide California Earthquake Center. Here, we employ CS to generate a set of 2103 fault ruptures and simulate the corresponding two horizontal velocity components time histories of ground motion (GM) on a 5-km grid of 625 stations in Southwest Iceland (SI). The ruptures were defined on a new synthetic time-independent 500-year catalog consisting of 223 hypothetical finite-fault sources of 5-7, generated using a new physics-based bookshelf fault system model in the SI transform zone. This fault system model and rupture realizations enable the CS time-independent physics-based approach to PSHA in the region. The study aims to migrate CS to SI and validate its kinematic fault rupture, anelastic wave propagation and ground motion simulations. Toward this goal, we use CS to generate multiple finite-fault rupture variations for each hypothetical fault. CS exploits seismic reciprocity for wave propagation by computing Strain Green Tensors along fault planes, which in turn are convolved with rupture models to generate GM seismograms. For each GM recording station, every adjoint simulation uses a 0-1 Hz Gaussian point source polarized along one horizontal grid direction. Comparison of the results in the form of rotation-invariant synthetic pseudo-acceleration spectral response values at 2, 3 and 5 sec periods are in very good agreement with the Icelandic strong-motion dataset, and a suite of new empirical Bayesian ground motion prediction equations (GMPEs). The vast majority of the CS results fall within one standard deviation of the mean GMPE predictions, previously estimated for the area. Importantly, at large magnitudes for which no data exists in Iceland, the CS dataset may play an important role in constraining the GMPEs for future applications.