Rapid Finite-Fault Models for the 2023 Mw 7.8 Kahramanmaraş, Türkiye, Earthquake Sequence
Abstract
In the immediate aftermath of devastating earthquakes such as in the 6 February 2023 Kahramanmaraş sequence in southcentral Türkiye, key stakeholders and the public demand timely and accurate earthquake information. Especially for large events, finite‐fault models provide important insights into the rupture process and enable interpretation of the observed ground shaking, which can improve situational awareness and facilitate rapid assessment of future hazards. Using strong‐motion waveforms recorded during the Kahramanmaraş sequence, we simulate a real‐time playback and calculate how a finite‐source model computed with the Finite‐fault rupture Detector (FinDer) algorithm would evolve for the 𝑀w 7.8 Pazarcık, 𝑀w 7.6 Elbistan, and 𝑀w 6.4 Yayladağı earthquakes. Using template matching FinDer compares observed and predicted ground‐motion acceleration amplitudes to determine the orientation and spatial extent of fault rupture. We test both generic crustal and fault‐specific templates from ground‐motion models and rupture geometries of the east Anatolian and Çardak–Sürgü faults. In the second step, we estimate the seismic slip along the source models from the backprojection of the seismic displacement amplitudes. The algorithms achieve excellent performance for all three earthquakes, and the final source models and slip profiles available within tens of seconds of the rupture nucleation match well with models computed days to weeks after the events occurred. The temporal evolution of the source models for the Pazarcık and Elbistan earthquakes suggests that FinDer can provide insight into the rupture kinematics of large earthquakes. Cascading instrument failures as well as power and data telemetry interruptions during the Pazarcık earthquake led to an early termination of signals at a significant number of near‐source stations. We show that FinDer is robust enough to cope with this type of degradation in network performance that can occur in large earthquakes, in general.
Copyright and License
© 2024 Seismological Society of America.
Acknowledgement
This study was supported by the EU project “A Digital Twin for Geophysical Extremes” (DT‐GEO) and has been financially supported by Horizon Europe under Grant Agreement No 101058129. J. Andrews was supported by the New Zealand Ministry of Business, Innovation, and Employment Contract Number C05X2003 for the Rapid Characterization of Earthquakes and Tsunami (RCET) program. The authors would like to thank David Wald (U.S. Geological Survey [USGS]) for conducting the Prompt Assessment of Global Earthquakes for Response (PAGER) analysis for the Finite‐fault rupture Detector (FinDer) models and the ShakeAlert team for related discussions. The authors are grateful for the constructive review of an earlier version of this article by Editor‐in‐Chief Allison Bent and two anonymous referees.
Data Availability
FinDer is implemented in C++ and utilizes the open‐source Computer Vision (openCV; https://opencv.org/, last accessed March 2024) and Generic Mapping Tools (GMT; Wessel et al., 2013) software libraries. The authors perform seismic data playbacks for earthquake early warning (EEW) simulations using the tools available from https://github.com/SED-EEW/sc3-playback and https://github.com/FMassin/msrtsimuld (last accessed March 2024). Our playbacks are carried out within the SeisComP framework (https://github.com/SeisComP/seiscomp, last accessed March 2024) utilizing the ETHZ‐SED SeisComP EEW (ESE) modules (https://www.seiscomp.de/doc/base/addons/sed.html#sed-eew, last accessed March 2024), the QuakeML strong‐motion extension (http://quake.ethz.ch/quakeml/QuakeML2.0/StrongMotion, last accessed March 2024), and the SED SeisComP contributions (http://www.github.com/swiss-seismological-service/sed-SeisComP-contributions, last accessed March 2024). Strong‐motion accelerometer data used in this study were obtained from the Department of Earthquake, Disaster and Emergency Management Authority (AFAD) of Türkiye, through the Turkish National Strong Motion Network (doi: 10.7914/SN/TK), and downloaded from the Turkish Earthquake Data Center at https://tdvms.afad.gov.tr/continuous (last accessed August 2023). The National Earthquake Information Center (NEIC) finite‐fault and moment tensor solutions (Fig. 1), source time functions (Fig. 5), reference slip models (Fig. 6), and ShakeMaps (S1) are taken from https://earthquake.usgs.gov (last accessed March 2024). The AFAD earthquake catalogue is available at https://deprem.afad.gov.tr/event-catalog (last accessed December 2023). The performance of EAS in the Kahramanmaraş sequence is described in https://www.bbc.com/news/technology-66316462 (last accessed March 2024). The supplemental material consists of six parts: S1 shows the U.S. Geological Survey (USGS) intensity and peak ground acceleration (PGA) ShakeMaps for the 𝑀w 7.8 Pazarcık, 𝑀w 7.6 Elbistan, and 𝑀w 6.4 Yayladağı earthquakes; S2 contains details of the fault‐specific finite‐fault rupture detector (FinDer) templates; S3 contains the results for the generic FinDer templates (analogous to Figs. 2–7); S4 contains animations for the Pazarcık, Elbistan, and Yayladağı earthquakes, showing the temporal evolution of the FinDer(S) models for both the fault‐specific and generic FinDer templates; S5 contains a plot showing the available warning time for Antakya in the Pazarcık earthquake, as well as the time of exceedance of the various alert and damage thresholds for the Pazarcık and Elbistan earthquakes; S6 shows the Prompt Assessment of Global Earthquakes for Response (PAGER) reports calculated for the final FinDer source models of the Pazarcık and Elbistan earthquakes.
Conflict of Interest
The authors acknowledge that there are no conflicts of interest recorded.
Additional details
- ISSN
- 1938-2057
- European Research Council
- 101058129
- Ministry of Business, Innovation and Employment
- C05X2003
- Caltech groups
- Seismological Laboratory