Group A, Poster #165, Fault and Rupture Mechanics (FARM)
Constraining On- and Off-Fault Nonlinear Dynamic Rupture Parameters via Hierarchical Bayesian Inversion of GNSS and Satellite Data for the 2019 Mw 7.1 Ridgecrest Earthquake
Poster Image:

Poster Presentation
2025 SCEC Annual Meeting, Poster #165, SCEC Contribution #14774 VIEW PDF
resent the first Bayesian inversion of complex 3D dynamic rupture simulations with off-fault plasticity, jointly resolving on- and off-fault nonlinear parameters, constrained by fault-parallel surface offsets from satellite imagery, high-rate GNSS time series, and static GNSS displacements. We employ a multilevel delayed acceptance (MLDA) algorithm, reducing the number of costly simulations needed for uncertainty quantification by combining fast approximate models with fewer fully resolved simulations.
Off-fault plasticity critically influences seismic hazard by affecting rupture dynamics and ground motions. Our inversion quantifies uncertainties and correlations among on- and off-fault dynamic rupture parameters for the 2019 Mw 7.1 Ridgecrest earthquake, using multidisciplinary surface deformation data and over four million CPU hours of simulations. We identify a strong correlation between on-fault frictional weakening and off-fault plasticity, showing increased inelastic deformation can compensate for stronger velocity-weakening frictional behavior.
Preferred rupture models feature spatially varying friction parameters (a-b), increasing from northwest to southeast, reducing velocity-weakening effects, and improving agreement with observed surface offsets. This variation aligns with along-strike changes in fault maturity. Lower off-fault plastic cohesion further enhances the match to observed surface deformation, consistent with geophysically imaged shallow damage zones.
We infer a shallow slip deficit (SSD) of 13.1% ±5.1%, aligning with previous kinematic inversion estimates. Our results highlight the feasibility of integrating 3D dynamic rupture simulations and multilevel Bayesian inversion to rigorously characterize earthquake sources and quantify uncertainties.
SHOW MORE
Off-fault plasticity critically influences seismic hazard by affecting rupture dynamics and ground motions. Our inversion quantifies uncertainties and correlations among on- and off-fault dynamic rupture parameters for the 2019 Mw 7.1 Ridgecrest earthquake, using multidisciplinary surface deformation data and over four million CPU hours of simulations. We identify a strong correlation between on-fault frictional weakening and off-fault plasticity, showing increased inelastic deformation can compensate for stronger velocity-weakening frictional behavior.
Preferred rupture models feature spatially varying friction parameters (a-b), increasing from northwest to southeast, reducing velocity-weakening effects, and improving agreement with observed surface offsets. This variation aligns with along-strike changes in fault maturity. Lower off-fault plastic cohesion further enhances the match to observed surface deformation, consistent with geophysically imaged shallow damage zones.
We infer a shallow slip deficit (SSD) of 13.1% ±5.1%, aligning with previous kinematic inversion estimates. Our results highlight the feasibility of integrating 3D dynamic rupture simulations and multilevel Bayesian inversion to rigorously characterize earthquake sources and quantify uncertainties.
SHOW MORE