SCEC Award Number 21098 View PDF
Proposal Category Collaborative Proposal (Data Gathering and Products)
Proposal Title Synthesis of fault geometry, seismicity, and deep structural fabric to constrain Community Fault (CFM) and Rheology (CRM) Models
Investigator(s)
Name Organization
Debi Kilb University of California, San Diego Vera Schulte-Pelkum University of Colorado, Boulder
Other Participants
SCEC Priorities 3b, 3a, 1b SCEC Groups CXM, SDOT, Seismology
Report Due Date 03/15/2022 Date Report Submitted 02/20/2024
Project Abstract
 We combine newly available southern California data sets to provide constraints for refinement of the SCEC Community Fault Model (CFM) as well as development of the Community Rheology Model (CRM). We compare CFM 5.3, contrasts in rock fabric imaged by receiver functions, and microseismicity in the GrowClust and QTM catalogs. Our work leverages recent receiver function results using azimuthal harmonic arrivals to image the depth, amplitude, and strike of conversions from contrasts in dipping foliation and dipping contrasts between isotropic bodies, an approach particularly well suited to mapping shear zones, dipping faults, and tectonic boundaries. We highlight general parallelism of receiver function- derived crustal fabric strikes with strikes of nearby faults in the CFM and find multiple instances of alignment of receiver function-derived strikes with planar features delineated in relocated seismicity. Below the seismogenic zone, we find lower crustal distributed fabric in the southern Sierra Nevada paralleling exhumed ductile fabric aligning with the reactivated Kern Canyon Fault. We also find near-fault structure imaged by data from dense station deployments along the San Jacinto fault and the San Andreas Fault near Parkfield showing deep pervasive fault-parallel fabric, fine structure of the Ridgecrest and Coso areas with orthogonal features in seismicity and receiver function imaging, and fabric contrasts imaged at the boundaries of crustal conductors from magnetotellurics. In most of southern California, deep distributed fabric aligns with past tectonics. Rather than defining individual shear zone geometries, we favor an approach that defines anisotropy of viscosity in lithospheric blocks.
Intellectual Merit We use newly available data sets to provide constraints for refinement of the SCEC Community Fault (CFM) as well as development of the Community Rheology (CRM) models, both in accordance with SCEC5 research goals. This suite of independent data include the CFM 5.3 (Maechling et al., 2020; Nicholson et al., 2020; Plesch et al., 2020), receiver function (RF) imaging of faults and intracrustal tectonic structural grain (Schulte-Pelkum et al., 2020b), and refined earthquake catalogs that include a template- based catalog (Ross et al., 2019) and updates to the SCSN catalog (Hauksson et al., 2012) including the GrowClust version (Trugman and Shearer, 2017). The synthesis of the CFM and catalog products with our
RF deep crustal fabric imaging is an original approach that supports improvements to CFM geometries, particularly at depth, and provides constraints for shear zones and block rheology for the CRM.
Broader Impacts A strength of this work is the cross-disciplinary aspect of the study, that includes data and resources from seismicity catalogs, 3D receiver function imaging, and 3D geologic fault models. Regular interaction between researchers within these sub-disciplines leads to cross-fertilization between the different CXMs, which in turn increases their value beyond the SCEC community. Discussions at the 2021 SCEC annual meeting with geologists, CFM researchers, geodynamicists, and seismologists have already opened new research avenues. Improvements to the CXMs benefit broader society through e.g., improved hazard estimates. Results were presented at the SCEC annual meeting, at AGU Fall meetings, and as part of lectures in undergraduate classes.
Exemplary Figure Figure 2: Cross section perpendicular to the SSAF north of the Salton Sea. QTM relocated seismicity (pink), inverted resistivity from MT (background color), inferred SAF (thick white), and CFM surface faults (thin white) from Share et al. (2023); RF harmonic arrivals (white squares) with fabric dip sense (black bars) above/below converting contrast (red).