Inversion of time-varying gravity field before and after the 2013 Lushan MS7.0 earthquake

Abstract

The 2013 MS7.0 Lushan earthquake, Sichuan, China, occurs on a blind thrust fault in the southern Longmenshan fault belt. The terrestrial hybrid gravity observations enable us to investigate how the deep mass changes before and after the earthquake. Based on the gravity measurement data, we find a transient increase in the gravity field about 2 years before the earthquake and a drop after the mainshock. To find out the cause, a Bayesian inversion method with spatiotemporal smoothness prior is employed to extract apparent density changes. We hypothesize that the significant increase of apparent density over the region on the south of the focal zone might be related to mass transfer in the deep crust. Therefore, we introduce a disc-shaped equivalent source model with a homogeneous density to address this hypothesis. Based on Markov Chain Monte Carlo simulations, we also estimate that the disc-shaped model has a radius of about 96 km, with a thickness of about 1.2 km and a depth of about 14 km. As a fluid diffusion footprint is indicated by seismicity migration in this region, with a fitted diffusion rate of 10 m2/s, we conclude that such deep crustal mass transfer may be caused by fluid diffusion.

Crustal Apparent Density Variations in the Middle Segment of the North Tianshan Mountains and Their Tectonic Significance

“…The source term is discretized into hexahedral grids in a spherical domain [45], and spatiotemporal constraints are introduced. Then, the "equivalent source" inversion model is optimized and solved following Akaike Information Criterion and Bayesian Information Criterion (ABIC) [46].…”

“…As we aimed to conduct equivalent source inversion for crustal apparent density, we only tested the resolution in the horizontal directions. We assigned alternatively distributed sources of positive and negative anomalies of the same size in the study area, measured the theoretical gravity anomalies at the surface monitoring stations by forward gravity modeling, and then used the inversion method to solve the source parameters and compare the results with the designed values to evaluate the differences in spatial resolution caused by the uneven distribution of the existing monitoring stations [50]. We designed discretized source bodies with a size of 0.5 • × 0.5 • , a burial depth of 10 km, an apparent density of ±1.0 kg/m 3 , and a thickness of 1 km to examine the resolution capacity of the gravity monitoring network in the middle segment of the North Tianshan Mountains with the hypothetical equivalent source model [51].…”