Abstract:
The near source strong ground motions of the 2013
MS7.0 Lushan, China, earthquake were simulated using empirical Green’s function (EGF) method. At first, we estimated the amount and location of strong motion gene-ration areas (SMGAs) based on the characteristics of both slip distributions from far-field seismic inversion and the envelopes of recorded acceleration from the main shock, and determined the amount of subfaults on SMGAs referring to the scaling law of asperity area
versus seismic moment introduced by Somerville
et al. Then, we implemented the genetic algorithm searching for the optimized value of above two and other source parameters. Based on the source models, we synthetized the waveforms for the 30 selected stations near the source region. The comparison of the synthetic waveforms with the observed records indicated that they agreed very well with each other, especially for the part of high-frequency larger than 1 Hz. We found that there were two obvious SMGAs on the fault, which take the position that the asperities from far-field seismic inversion take. The combined SMGAs we obtained were smaller than those predicted by extension of the scaling law by Somerville
et al.