Strong motion PGA prediction for southwestern China from small earthquake records

Abstract

Abstract. For regions without enough strong ground motion records, a seismology-based method is adopted to predict motion PGA (peak ground acceleration) values on rock sites with parameters from small earthquake data, recorded by regional broadband digital monitoring networks. Sichuan and Yunnan regions in southwestern China are selected for this case study. Five regional parameters of source spectrum and attenuation are acquired from a joint inversion by the micro-genetic algorithm. PGAs are predicted for earthquakes with moment magnitude (M w ) 5.0, 6.0, and 7.0 respectively and a series of distances. The result is compared with limited regional strong motion data in the corresponding interval M w ± 0.5. Most of the results ideally pass through the data clusters, except the case of M w 7.0 in the Sichuan region, which shows an obvious slow attenuation due to a lack of observed data from larger earthquakes (M w ≥ 7.0). For further application, the parameters are adopted in strong motion synthesis at two near-fault stations during the great Wenchuan Earthquake M8.0 in 2008.

Characterized source model of the 2013 Lushan earthquake (Mw 6.6) by the empirical Green’s function method

“…We employed the S-wave portion with a length of 40.96 s of the mainshock and EGF event to calculate the observed Fourier spectra. We followed the method of Miyake et al (1999) to adopt the hypocenter distance for the mainshock and EGF events to remove the path effect (Q s (f) = 155f 0.6804 , Tao et al 2016) from the Fourier spectra to obtain the observed source spectra. The average source spectral ratios and standard deviations for the target stations are shown with thick gray and dashed curves in Fig.…”

Preliminary Evaluation of Crustal Medium Parameters in Western China

“…In the regions with abundant strong earthquake records, some researchers have tried to directly establish the regional attenuation relationship by statistical regression of regional earthquake data, but some results are limited by insufficient data and have low reliability. We provided the seismology-based ground motion prediction models [29]- [30] , in which the regional parameters were inversed by small earthquake data of the broadband seismological network. In this paper, we attempt to use limited strong motion data in the inversion.…”