Implementing rapid, probabilistic association of earthquakes with source faults in the CFM for southern California

Walker S. Evans, Andreas Plesch, Won Lee, Natesh Pillai, John H. Shaw, Men-Andrin Meier, & Egill Hauksson

Published August 14, 2017, SCEC Contribution #7597, 2017 SCEC Annual Meeting Poster #076

We present a statistical method to identify the fault (or sets of candidate faults) that generated an earthquake using information provided soon after these events occur. This effort bridges the information provided by increasingly sophisticated near real-time seismograph networks with SCEC’s 3D Community Fault Models (CFM’s). We used an earthquake dataset and evaluated its relationship with the CFM, to assess what properties of earthquakes serve as the best predictors of the fault on which they occurred. We used a series of training datasets consisting of earthquakes that occurred after CFM 2.0 was developed, for which there were known associations with faults. We established that spatial proximity (distance), focal mechanism (nodal plane orientation), and earthquake history (spatial and temporal clustering) can be combined to assign a probability that a given earthquake was associated with one or more source faults in the model (or on a fault not in the model). We are currently implementing this capability through the Southern California Earthquake Data Center (SCEDC). Specifically, we have calculated probabilities for updated earthquake hypocenter and focal mechanism catalogs (through 2016) using the latest fault representations (CFM v. 5.2). In addition, we have developed an implementation of the code for use at the SCEDC. After testing, this will provide an automated, rapid assessment of earthquake source fault probabilities that can be updated as information about earthquakes is refined. The SCEDC will host this catalog locally and submit this new attribute to the ANSS ComCat national catalog. The SCECDC will also submit this product near-real time to NEIC to make it part of their web pages and part of the ANSS ComCat.

This information is of critical value, as it offers an approach to provide objective, rapid associations between recorded earthquakes and their causative fault(s). This will be useful in communication objective information about earthquakes to responders, the scientific community, and general public. Moreover, if the probabilistic association can be computed in actual real-time, future EEW algorithms can potentially use such information to infer if an ongoing rupture is occurring on a large fault that presents a significant regional hazard. Ultimately, the association scheme should lead to more effective earthquake response.

Key Words
CFM, earthquake faulting, earthquake early warning

Evans, W. S., Plesch, A., Lee, W., Pillai, N., Shaw, J. H., Meier, M., & Hauksson, E. (2017, 08). Implementing rapid, probabilistic association of earthquakes with source faults in the CFM for southern California. Poster Presentation at 2017 SCEC Annual Meeting.

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