Expansion of the NEIC finite fault modeling capabilities to include regional seismic and geodetic data
Abstract
One of the key products produced at the USGS National Earthquake Information Center (NEIC) in response to significant earthquakes is the finite fault model (FFM). The FFM is used to inform downstream products such as ShakeMap ground motion estimates, which in turn are used as input into loss estimates (PAGER) and ShakeCast, a damage assessment system used by a variety of agencies, emergency planners, and utility operators. Critically, shaking at a given location is dependent on distance to the ruptured portion of the fault (as opposed to distance to the earthquake hypocenter, where slip begins), among other factors. Because large earthquakes can involve slip over tens to hundreds of kilometers of a fault, it is vital to rapidly assess the amount and location of slip along the fault. Previously at the NEIC, FFMs were typically computed in several hours using teleseismic data only, for which it is generally possible to obtain an FFM for earthquakes ~M7.0 or larger. Here we will report the initial results of a collaborative effort between the Centro Sismologico Nacional in Chile, the NEIC, and the University of Oregon to introduce joint modeling of regional strong motion and high rate GNSS, in addition to teleseismic data, into the NEIC FFM. We will show specific examples from the July 8, 2021 M6 Antelope Valley, CA and July 29, 2021 M8.2 Chignik, AK earthquakes that demonstrate the improved performance of this joint method. Results with regional data show there is potential for significant reduction in the time to the first FFM solution. Additionally, using these new methods the magnitude threshold can be potentially lowered to ~M6.0. As strong motion and GNSS networks develop worldwide and data-sharing increases, it is our goal that joint inversion of these data streams, alongside teleseismic data, will become routine processing within the USGS NEIC.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.S55F0208R