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A Statistical Method for Associating Earthquakes with Their Source Faults in Southern California

Evans, Walker S. and Plesch, Andreas and Shaw, John H. and Pillai, Natesh L. and Yu, Ellen and Meier, Men-Andrin and Hauksson, Egill (2020) A Statistical Method for Associating Earthquakes with Their Source Faults in Southern California. Bulletin of the Seismological Society of America, 110 (1). pp. 213-225. ISSN 0037-1106. https://resolver.caltech.edu/CaltechAUTHORS:20200115-085049005

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Abstract

We present a new statistical method for associating earthquakes with their source faults in the Southern California Earthquake Center’s 3D Community Fault Models (CFMs; Plesch et al., 2007) in near‐real time and for historical earthquakes. The method uses the hypocenter location, focal mechanism orientation, and earthquake sequencing to produce the probabilities of association between a given earthquake and each fault in the CFM as well as the probability that the event occurred on a fault not represented in the CFM. We used a set of known likely associations (the Known Likely Sets) as training or testing data and demonstrated that our models perform effectively on these examples and should be expected to perform well on other earthquakes with similar characteristics including the full catalog of southern California earthquakes (Hauksson et al., 2012). To produce near‐real‐time associations for future earthquakes, the models have been implemented as an R script and connected to the Southern California Seismic Network data processing system operated by the California Institute of Technology and the U.S. Geological Survey to automatically produce fault associations for earthquakes of M ≥ 3.0 as they occur. To produce historical associations, we apply the method to the most recent CFM version (v.5.2), yielding modeled historical associations for all events of M ≥ 3.0 in the catalog of southern California earthquakes from 1981 to 2016. More than 80% of these events and 99% of moment within the geography covered by the CFM had a primary association with a CFM fault. The models can help identify clusters of small earthquakes that indicate the onset of activity associated with major faults. The method will also assist in communicating objective information about the faults that source earthquakes to the scientific community and general public. In the event of a damaging southern California earthquake, the near‐real‐time association will provide valuable information regarding the similarity of the current event to forecast scenarios, potentially aiding in earthquake response.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1785/0120190115DOIArticle
ORCID:
AuthorORCID
Meier, Men-Andrin0000-0002-2949-8602
Hauksson, Egill0000-0002-6834-5051
Additional Information:© 2020 Seismological Society of America. Manuscript received 13 May 2019; Published online 14 January 2020. Data used in this study were collected by the California Institute of Technology (Caltech) and U.S. Geological Survey (USGS) Southern California Seismic Network (doi: 10.7914/SN/CI); and distributed by the Southern California Earthquake Center (SCEC; doi: 10.7909/C3WD3xH1). This research was supported by USGS/National Earthquake Hazards Reduction Program (NEHRP) Grant Number G18AP00028 to Caltech; and by the SCEC (Contribution Number 9057), which is funded by National Science Foundation (NSF) Cooperative Agreement Number EAR‐1033462 and USGS Cooperative Agreement Number G12AC20038. Data and Resources: For hypocenters and all earthquake data other than focal mechanism nodal planes, we used 2016 update of Hauksson et al. (2012). For focal mechanism data, we used the 2016 update of Yang et al. (2012). These catalogs can be downloaded at http://scedc.caltech.edu/research-tools/alt-2011-dd-hauksson-yang-shearer.html and http://scedc.caltech.edu/research-tools/alt-2011-yang-hauksson-shearer.html (last accessed June 2018), respectively. We utilized training datasets of known associations (the Known Likely Sets), one for the Community Fault Model 2 (CFM 2) and one for the CFM 5. These associations were based on surface rupture, source inversions, or other seismologic, geodetic, or geologic studies. The CFM 2 Known Likely Set (Fig. 2; Tables 1 and 2, and Table S1) contains 1322 earthquakes clustered around nine faults (plus 71 earthquakes not associated with faults in the CFM), and the CFM 5 Known Likely Set (Fig. 2; Tables 1 and 2, and Table S2) contains 405 earthquakes clustered around eight faults (plus 134 earthquakes not associated with faults in the CFM). Known Likely Set data are provided in the supplemental material. Fault data consist of CFM v.2 and 5.2, containing 3D mappings of 153 and 325 southern California faults, respectively. The CFM is an object‐oriented, 3D description of the active faults in California that are deemed capable of generating moderate‐to‐large earthquakes (Plesch et al., 2007). Statistical analysis was performed in R (Zeileis and Grothendieck, 2005; Urbanek, 2012; Schlager, 2017; Adler et al., 2018; R Core Team, 2018).
Group:Seismological Laboratory
Funders:
Funding AgencyGrant Number
USGSG18AP00028
Southern California Earthquake Center (SCEC)UNSPECIFIED
NSFEAR‐1033462
USGSG12AC20038
Other Numbering System:
Other Numbering System NameOther Numbering System ID
Southern California Earthquake Center9057
Issue or Number:1
Record Number:CaltechAUTHORS:20200115-085049005
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200115-085049005
Official Citation:Walker S. Evans, Andreas Plesch, John H. Shaw, Natesh L. Pillai, Ellen Yu, Men‐Andrin Meier, Egill Hauksson; A Statistical Method for Associating Earthquakes with Their Source Faults in Southern California. Bulletin of the Seismological Society of America ; 110 (1): 213–225. doi: https://doi.org/10.1785/0120190115
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:100730
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:15 Jan 2020 17:10
Last Modified:06 Feb 2020 17:19

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