A Comprehensive Earthquake Focal Mechanism Catalog for Nevada Obtained Through Deep Learning Algorithms
The state of Nevada is one of the most seismically active areas of the United States, with numerous active fault systems throughout the Walker Lane and Basin and Range tectonic faults. Despite high rates of seismic activity, Nevada currently lacks a comprehensive catalog of earthquake focal mechanisms that could be used to better understand seismotectonic processes. Determining the focal mechanisms of small earthquakes poses a considerable challenge due to the difficulty of distinguishing phase arrivals and first-motion polarities from noise. To address this issue, we augment the first-motion polarity database maintained by the Nevada Seismological Laboratory with additional measurements obtained using a convolutional neural network algorithm. We then complement polarity data with new measurements of S/P amplitude ratios to provide additional constraints on event mechanisms. By incorporating both existing and newly obtained data, we construct a comprehensive focal mechanism catalog for the state of Nevada from 2008 through 2023, utilizing a revised implementation of the HASH method originally developed by Hardebeck and Shearer (2002). With the new focal mechanism catalog, we analyze changes in focal mechanism characteristics resulting from significant mainshocks like the 2020 Mw6.5 Monte-Cristo and other prominent earthquake sequences like the Spanish Springs, Hawthorne, Nine-Mile Ranch, and Sheldon sequences. The enhanced resolution of the new catalog will play a crucial role in advancing our understanding of the crustal stress field, mechanisms triggering earthquakes, fault zone geometry, and strain partitioning across the state.
Session: Network Seismology: Recent Developments, Challenges and Lessons Learned - III
Type: Oral
Room: Tubughnenq’ 5
Date: 5/2/2024
Presentation Time: 08:45 AM (local time)
Presenting Author: Avigyan Chatterjee
Student Presenter: Yes
Additional Authors
Avigyan Chatterjee Presenting Author Corresponding Author achatterjee@unr.edu University of Nevada, Reno |
Gaurav Srikar gauravsrikar@nevada.unr.edu University of Nevada, Reno |
Colin Pennington pennington6@llnl.gov Lawrence Livermore National Laboratory |
William Walter walter5@llnl.gov Lawrence Livermore National Laboratory |
Daniel Trugman dtrugman@unr.edu University of Nevada, Reno |
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A Comprehensive Earthquake Focal Mechanism Catalog for Nevada Obtained Through Deep Learning Algorithms
Session
Network Seismology: Recent Developments, Challenges and Lessons Learned
Description