High-resolution finite fault slip inversion of the 2019 Ridgecrest earthquake...

Barba-Sevilla, M., M. Glasscoe, J. Parker, G. A. Lyzenga, M. J. Willis, and K. Tiampo (2022), High-resolution finite fault slip inversion of the 2019 Ridgecrest earthquake using 3D finite element modeling, J. Geophys. Res., 127, e2022JB024404, doi:10.1029/2022JB024404.

The 2019 Ridgecrest earthquake sequence manifested as one of the most complex fault surface
ruptures observed in California in modern times. The M6.4 foreshock and M7.1 mainshock occurred on an
intricate network of orthogonal and sub-parallel faults resulting in observable surface displacement and surface
rupture captured by geodetic data. Here we present the application of a high-resolution 3D finite element model
(FEM) approach to invert for the detailed fault slip of the entire sequence using complex rheology and fused
coseismic Global Navigation Satellite System (GNSS) data with Sentinel-1 differential interferometric synthetic
aperture radar and pixel offset data. The heterogeneous FEM and the fused geodetic data set of pixel offsets,
interferograms, and GNSS data results in our optimal inversion solution. This preferred solution is a complex,
high-resolution non-planar slip model of both the M6.4 and M7.1 events that features three main regions of
large slip (6.9+ m), with depths ranging from 2 to 10 km. The regions of slip are bounded by the mainshock
hypocenter and the mainshock aftershocks and appear to be related to spatially varying rheological properties.
We successfully reproduce a localized region of observed subsidence in the northern portion of the primary
fault through the inclusion of a curved fault strand with a significant dip-slip component. The curved fault
strand is the site of our maximum slip of 7.4 m at a depth of 4.2 km. The results demonstrate a robust fit from a
more complete, detailed model for the entire seismogenic zone with reasonable computational cost, providing
new insights into the governing rheologic and structural processes.

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Research Program: 
Earth Surface & Interior Program (ESI)
Funding Sources: 
NASA Award Number 80NM0018D0004