Source Scaling, Spatially Variable Path Attenuation, and Site-Effect Parameters via a Generalized Inversion Technique for Strong-Motion Data from Sichuan, China

Abstract

ABSTRACT Quantifying the source, propagation path, and site characteristics accurately is pivotal for evaluating regional earthquake hazards. The nonparametric generalized inversion technique of strong-motion records offers an effective approach for analyzing these three fundamental elements. However, this technique might overlook the spatial variation of regional attenuation and the inherent uncertainty of reference stations. To enhance the understanding of strong ground motion characteristics in the Sichuan area, this study employs an improved nonparametric inversion scheme to analyze 3338 sets of strong-motion data from 397 earthquakes (Ms 3–6.5) that occurred in the Sichuan region between 2007 and 2020. In terms of regional source characteristics, the setting of low-frequency cutoffs in strong-motion records may lead to the overestimation of corner frequency and stress drop for earthquakes with higher magnitudes. Conversely, for events with moment magnitudes less than 5, the regional stress drop levels tend to stabilize as the magnitude increases. Furthermore, stress drop is independent of depth and fault type. Regarding path attenuation, considering the influence of Moho reflection, the geometric attenuation is limited to R−1 within a hypocentral distance of 75 km. The nonparametric results from 75 to 300 km show that as the hypocentral distance increases, the geometric attenuation in this region first decreases and then stabilizes. Furthermore, the mean level of the inelastic attenuation factor Qs is 199.5f0.98. Pertaining to site effects, we observe that at the edge of the Sichuan basin, the amplification of sites in the long-period part is clearly characterized and tends to stabilize with increasing frequency. In addition, the site amplification factor of 33 logarithmically spaced frequency points between 0.5 and 20 Hz has a linear relationship with the soil layer parameter VS30 or VS20. The correlation coefficients of both show moderate correlation, among which VS30 is slightly better than VS20.