Abstract
Seismogenic fault geometry, especially for a blind fault, is usually difficult to derive, based only on the distribution of aftershocks and interference fringes of Interferometric Synthetic Aperture Radar (InSAR). To better constrain the fault geometry of the 2017 Jiuzhaigou Mw 6.5 earthquake, we first carried out a nonlinear inversion for a single fault source using multi-peak particle swarm optimization (MPSO), Monte Carlo (MC), and Markov Chain Monte Carlo (MCMC) algorithms, respectively, with constraints of InSAR data in multiple SAR viewing geometries. The fault geometry models retrieved with different methods were highly consistent and mutually verifiable, showing that a blind faulting with a strike of ~154° and a dip angle of ~77° was responsible for the Jiuzhaigou earthquake. Based on the optimal fault geometry model, the fault slip distribution jointly inverted from the InSAR and Global Positioning System (GPS) data by the steepest descent method (SDM) and the MC method showed that the slip was mainly concentrated at the depth of 1–15 km, and only one slip center appeared at the depth of 5–9 km with a maximum slip of about 1.06 m, some different from previous studies. Taking the shear modulus of μ = 32 GPa, the seismic moment derived from the distributed slip model was about 7.85 × 1018 Nm, equivalent to Mw 6.54, which was slightly larger than that from the focal mechanism solutions. The fault spatial geometry and slip distribution could be further validated with the spatial patterns of the immediate aftershocks. Most of the off-fault aftershocks with the magnitude > M2 within one year after the mainshock occurred in the stress positive stress change area, which coincided with the stress triggering theory. The static Coulomb stress, triggered by the mainshock, significantly increased at the Tazang fault (northwest to the epicenter), and at the hidden North Huya fault, and partial segments of the Minjiang fault (west of the epicenter).
Highlights
On the 8 August 2017, an MW 6.5 earthquake struck Jiuzhaigou (103.82◦E, 33.20◦N) in Sichuan Province, China, with a focal depth of approximately 20 km
There were significant discrepancies among the focal mechanism solutions by several organizations, e.g., the Global Centroid Moment Tensor (GCMT), United States Geological Survey (USGS), and China Seismic Information (CSI), in terms of the fault geometric parameters, while these solutions showed that the rupture was dominated by strike-slip
The F1 and F2 are separately the uniform slip fault model retrieved by the multi-peak particle swarm optimization (MPSO)+Monte Carlo (MC) and the Markov Chain Monte Carlo (MCMC) method; the S1 are the distributed slip models derived by the steepest descent method (SDM)+MC method based on the extension of F1 with an optimize dip angle
Summary
On the 8 August 2017, an MW 6.5 earthquake struck Jiuzhaigou (103.82◦E, 33.20◦N) in Sichuan Province, China, with a focal depth of approximately 20 km (http://www.csi.ac.cn). There were significant discrepancies among the focal mechanism solutions by several organizations, e.g., the Global Centroid Moment Tensor (GCMT), United States Geological Survey (USGS), and China Seismic Information (CSI), in terms of the fault geometric parameters, while these solutions showed that the rupture was dominated by strike-slip. The near-field full seismic waveform inversion for the focal mechanism indicated that the Jiuzhaigou earthquake was mostly dominated by a left-lateral strike-slip [5], with a strike direction of 153◦. Constrained by the InSAR and GPS data, optimal dip angles of 80◦ and 81◦ for the Jiuzhaigou earthquake with the strike direction of 155◦ were reported [9,10], respectively. The results of three faulting segments, used to fit seismic waveforms and InSAR data, indicated that the Jiuzhaigou earthquake occurred on a young fault system [11]. TThhee IInnSSAARR ccoosseeiissmmiicc ddeeffoorrmmaattiioonn ffiieellddss.. ((aa––cc)) CCoorrrreessppoonnddiinngg ccoosseeiissmmiicc ddeeffoorrmmaattiioonn ffiieellddss ooff tthhee iinntteerrffeerrooggrraamm ppaaiirrss ooff SS11AA,, SS11DD aanndd RR22AA,, rreessppeeccttiivveellyy
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