Unexpected far-field deformation of the 2023 Kahramanmaraş earthquakes revealed by space geodesy.
Published In: Science (pre-March 2025), 2024, v. 386, n. 6719. P. 328 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Ergintav, S.; Vernant, P.; Tan, O.; Karabulut, H.; Özarpacı, S.; Floyd, M.; Konca, A. Ö.; Çakır, Z.; Acarel, D.; Çakmak, R.; Vasyura-Bathke, H.; Dogan, U.; Kurt, A. İ.; Özdemir, A.; Ayruk, E. T.; Turgut, M.; Özel, Ö.; Farımaz, I. 3 of 3
Abstract
The spatiotemporal pattern of surface displacements from large earthquakes provides crucial insights about the deformation of Earth’s crust at various scales and the interactions among tectonic plates. However, the lack of extensive and large-scale geodetic networks near such seismic events hinders our thorough understanding of the large-scale crustal deformation resulting from earthquakes. Using Türkiye’s extensive and continuous global navigation satellite system (GNSS) network during the moment magnitude 7.8 and 7.6 Kahramanmaraş earthquakes on 6 February 2023, we show that large earthquakes can induce far-field crustal deformations (>700 kilometers), exceeding current predictions from elastic dislocation models. They can lead to the mobilization of tectonic plates and the triggering of far-field earthquakes, which carries profound implications for seismic hazard assessments and necessitates a new perspective on crustal deformation and earthquake mechanics. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Science (pre-March 2025). 2024/10, Vol. 386, Issue 6719, p328
- Document Type:Article
- Subject Area:Construction and Building
- Publication Date:2024
- ISSN:0036-8075
- DOI:10.1126/science.ado4220
- Accession Number:180320137
- Copyright Statement:Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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