Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 2022 | public
Journal Article

The 2020 Westmorland, California Earthquake Swarm as Aftershocks of a Slow Slip Event Sustained by Fluid Flow

Abstract

Swarms are bursts of earthquakes without an obvious mainshock. Some have been observed to be associated with transient aseismic fault slip, while others are thought to be related to fluids. However, the association is rarely quantitative due to insufficient data quality. We use high-quality GPS/GNSS, InSAR, and relocated seismicity to study a swarm of >2,000 earthquakes which occurred between 30 September and 6 October 2020, near Westmorland, California. Using 5 min sampled Global Positioning System (GPS) supplemented with InSAR, we document a spontaneous shallow M_w 5.2 slow slip event that preceded the swarm by 2–15 hr. The earthquakes in the early phase were predominantly non-interacting and driven primarily by the slow slip event resulting in a nonlinear expansion. A stress-driven model based on the rate-and-state friction successfully explains the overall spatial and temporal evolution of earthquakes, including the time lag between the onset of the slow slip event and the swarm. Later, a distinct back front and a square root of time expansion of clustered seismicity on en-echelon fault structures suggest that fluids helped sustain the swarm. Static stress triggering analysis using Coulomb stress and statistics of interevent times suggest that 45%–65% of seismicity was driven by the slow slip event, 10%–35% by inter-earthquake interactions, and 10%–30% by fluids. Our model also provides constraints on the friction parameter and the pore pressure and suggests that this swarm behaved like an aftershock sequence but with the mainshock replaced by the slow slip event.

Additional Information

The authors thank Sebastian Hainzl, Kathryn Materna, the associate editor, editor Satoshi Ide, and one anonymous reviewer for insightful and detailed comments, which greatly helped improve the quality of the manuscript. Generic Mapping Tool version 6 (Wessel et al., 2019) and Matlab version 2020a were used to analyze data and prepare figures. This work greatly benefited from the seismic waveform and seismic catalogs accessible from the Southern California Seismic Network data repository (https://scedc.caltech.edu), processed 5 min and daily sampled GPS data from Nevada Geodetic Laboratory (http://geodesy.unr.edu/; Blewitt et al., 2018), and C-band Synthetic Aperture Radar (SAR) images acquired by the Sentinel-1 satellite (available through Copernicus Open Access Hub: https://scihub.copernicus.eu/), along with seismic phase association software PhaseLink (https://github.com/interseismic/PhaseLink; Ross, Yue, et al., 2019), hypocenter inversion software HypoSVI (https://github.com/Ulvetanna/HypoSVI; Smith et al., 2021), earthquake relocations software GrowClust (https://github.com/dttrugman/GrowClust; Trugman & Shearer, 2017), independent component analysis software vbICA (Gualandi & Pintori, 2020), Schuster spectrum software (http://www.tectonics.caltech.edu/resources/schuster_spectrum/; Ader & Avouac, 2013), and solid Earth tides calculation software solid (Milbert, 2018). The authors thank Adriano Gualandi for providing codes for GPS processing and Coulomb stress calculations. This research is partly supported by the National Science Foundation (NSF) Grants EAR-1821853 and EAR-2034167 and the University of Southern California / Southern California Earthquake Center Grant SCON-00003725. M.A. is funded by the Swiss National Science Foundation (SNF) Grant P2ELP2_195127. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023