Stochastic finite-fault ground motion simulation for the Mw 6.7 earthquake in Lushan, China

Abstract

The Ya’an, Sichuan Mw 6.7 earthquake occurred on April 20, 2013. In this article, the stochastic finite-fault method (EXSIM) based on dynamic corner frequency, proposed by Motazedian and Atkinson (Bull Seismol Soc Am 95(3):995–1010, 2005), is validated to be an intelligible and productive approach for the generation of high-frequency strong ground motion. The validated model parameters were considered for the simulation at 31 selected stations, which are less than 200 km away from the fault. The input parameters included site condition, source term, and path term. The calibration of the input parameters, such as the stress drop, was achieved by using misfit functions between the observed PSA (pseudo-acceleration response spectra) and simulated PSA in the time domain. Some of the other parameters, such as distance-dependent duration, high-frequency attenuation parameter kappa, and local amplification functions, were calibrated by considering the observed recordings. In this study, we attempted to employ two different slip models for strong ground motion simulation, so that the influence on the simulation results can be revealed. Our results depicted that although the method cannot combine well, the directivity effects and the soil conditions are not adequately represented at individual stations, the synthetics satisfactorily match with the seismic characteristics regarding peak ground acceleration (PGA), response spectra, Fourier spectrum, and time history, for both the time and frequency range considered. The results also demonstrated that there is a slight difference between the simulation results of the two slip models. Finally, we compared the effects of different distance-dependent duration models for the simulated PGA. It illustrates that it is difficult to find a balance between the ground motion duration and PGA at stations with fault distance less than 20 km, which makes the duration and PGA to coincide well with the observed recordings.