SCEC Award Number 22076 View PDF
Proposal Category Individual Proposal (Integration and Theory)
Proposal Title Using Local Earthquake Shear Wave Anisotropy to Quantify Stress Changes Over Time
Investigator(s)
Name Organization
Daniel Trugman University of Nevada, Reno Nadine Igonin University of Texas at Austin
Other Participants
SCEC Priorities 1d, 2d, 2c SCEC Groups Seismology, SDOT, FARM
Report Due Date 03/15/2023 Date Report Submitted 05/31/2023
Project Abstract
 We use a high-resolution dataset of shear wave splitting to examine the relationship between anisotropy and fault structure near the San Jacinto fault. As part of this project, we developed a Python package for shear wave splitting analysis that integrates well with other SCEC and SCEDC datasets. With these computational tools in hand, we make systematic measurements of shear wave splitting parameters for different clusters and stations throughout the study region with an aim to unravel what factors cause anisotropy at a local scale and what the implications are for earthquake processes. This project supported a 1st-year PhD student in gaining experience in seismic data processing and interpretation that will be foundational in her scientific career going forward.
Intellectual Merit Our work is the first to apply systematic shear wave splitting at scale to a fault zone as active and complex as the San Jacinto, which is one of the keystone regions in the SCEC ecosystem. The techniques we have developed can provide new fundamental insights into the physical origins of seismic anisotropy at local scales and their implications for earthquake rupture processes and the evolution of fault systems.
Broader Impacts This project supported a 1st-year PhD student in the first chapter of her thesis, gaining research experience in seismology, data processing, and geophysical interpretation that will be foundational in her scientific career going forward. The work was presented at GSA Cordilleran Section annual meeting and will evolve into a peer reviewed manuscript in the near future. In addition, we have developed a user-friendly software package for shear wave splitting analysis that once finalized will be a valuable tool for other scientists to built on our work.
Exemplary Figure Figure 1: Example of method and quality control assessment. (a-f) rotation of the raw data (a-b) into fast and slow components (c-d), followed by energy maximization of the primary transformed component (e-g) to determine the best pair of splitting parameters (h).