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Abstract The San Fernando Valley (SFV), part of the Los Angeles metropolitan area, is a seismically active urban environment. Large-magnitude earthquakes, such as the 1994 Mw 6.7 Northridge event that occurred on a blind fault beneath the valley, caused significant infrastructure damage in the region, underscoring the need for enhanced seismic monitoring to improve the identification of buried faults and hazard evaluation. Currently, the Southern California Earthquake Data Center operates four broadband instruments within the valley; however, the network’s ability to capture small earthquakes beneath the region may be limited. To demonstrate how this data gap can be filled, we use recordings from the SFV array, comprised of 140 nodal instruments with interstation distances ranging from 0.3 to 2.5 km that recorded for one month. High-anthropogenic noise levels in urbanized areas tend to conceal earthquake signals; therefore, we applied a previously developed machine learning model fine-tuned on similar waveforms to detect events and pick seismic phases. In a two-step event association workflow, isolated phase picks were first culled, which eliminated false positive detections and reduced computational runtime. We located 62 events within a 209 km radius of our array with magnitudes ranging from ML 0.13 to 4, including 36 new events that were undetected by the regional network. One event cluster reveals a previously unidentified (5.3 km × 4 km) blind fault zone located ∼5 km beneath the southern part of the valley. Seismicity from this zone is rare in the regional catalog (<3 events per year), despite producing a Mb 4.4 event in 2014. Our results highlight the benefits of detecting small-magnitude seismicity for hazard estimation. Temporary nodal arrays can identify critical gaps in regional monitoring and guide site selection for permanent stations. In addition, our workflow can be applied to complement seismic monitoring in other urban settings.
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A Detailed Earthquake Catalog for the San Jacinto Fault‐Zone Region in Southern California
Abstract We develop an automated processing procedure to derive a new catalog of earthquake locations, magnitudes, and potencies and analyze 9 years of data between 2008 and 2016 in the San Jacinto fault‐zone region. Our procedure accounts for detailed 3‐D velocity structure using a probabilistic global‐search location inversion and obtains high‐precision relative event locations using differential travel times measured by cross‐correlating waveforms. The obtained catalog illuminates spatiotemporal seismicity patterns in the fault zone with observations for 108,800 earthquakes in the magnitude range −1.8 to 5.4. Inside a focus region consisting of an 80‐km by 50‐km rectangle oriented parallel to the main fault trace, we estimate a 99% detection rate of earthquakes with magnitude 0.6 and greater and detect and locate about 60% more events than those present in the Southern California Seismic Network catalog. The results provide the most complete catalog available for the focused study region during the analyzed period and include both deeper events and very shallow patches of seismicity not present in the regional catalog. The seismicity exhibits a variety of complex patterns that contain important information on deformation processes in the region. The fraction of event pairs with waveforms having cross‐correlation coefficients ≥0.95 is only about 3%, indicating diverse processes operating in the fault zone.
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- Award ID(s):
- 1722561
- PAR ID:
- 10372155
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Solid Earth
- Volume:
- 124
- Issue:
- 7
- ISSN:
- 2169-9313
- Page Range / eLocation ID:
- p. 6908-6930
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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