Assessing seismic displacements and early warning using kinematic PPP with MADOCA real-time products: A case study of 2023 Kahramanmaras , (Türkiye) earthquakes

dc.contributor.authorBirinci, Sinan
dc.contributor.authorSogukkuyu, Furkan
dc.contributor.authorSaka, Mehmet Halis
dc.date.accessioned2025-10-29T11:24:31Z
dc.date.issued2024
dc.departmentFakülteler, Mühendislik Fakültesi, Harita Mühendisliği Bölümü
dc.description.abstractEarly warning and emergency hazard response studies in large earthquakes require rapid and reliable determination of earthquake magnitude. The magnitude of an earthquake can be estimated based on peak ground displacement (PGD) values captured from high-rate GNSS records. In this study, two major earthquakes that hit Kahramanmaras, Province on February 6, 2023, were investigated by using the real-time Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) technique to confirm the usability of GNSS in early warning. Data from high-rate (1-Hz) GNSS stations were evaluated with the real-time kinematic PPP approach utilizing the multi-GNSS advanced demonstration tool for orbit and clock analysis (MADOCA) products and JPL's GipsyX software. In addition, static PPP was also used to identify the permanent displacements caused by earthquakes. Static PPP results demonstrated that significant displacements were detected at stations close to the epicenters, particularly the 446.86 cm horizontal displacement in the EKZ1 station. Considering the kinematic PPP results revealed that when PGD values calculated from seismic waves, functional model, and updated coefficients were implemented, the moment magnitude of the Pazarc & imath;k earthquake was estimated as Mw 7.78, which was reported as Mw 7.8 by USGS and Mw 7.7 by AFAD, whilst the magnitude of the Elbistan earthquake was computed as Mw 7.56, which was reported as Mw 7.5 by USGS and 7.6 by AFAD. Overall, this study validates the effectiveness of the real-time GNSS PPP as an attractive alternative for analyzing coseismic events and supporting early warning.
dc.identifier.doi10.1016/j.measurement.2024.114527
dc.identifier.issn0263-2241
dc.identifier.issn1873-412X
dc.identifier.scopus2-s2.0-85188730322
dc.identifier.scopusqualityQ3
dc.identifier.urihttps://doi.org/10.1016/j.measurement.2024.114527
dc.identifier.urihttps://hdl.handle.net/20.500.14854/9959
dc.identifier.volume230
dc.identifier.wosWOS:001219291100001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofMeasurement
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20251020
dc.subjectReal-time kinematic PPP
dc.subjectMADOCA products
dc.subjectGNSS seismology
dc.subjectEarthquake magnitude estimation
dc.titleAssessing seismic displacements and early warning using kinematic PPP with MADOCA real-time products: A case study of 2023 Kahramanmaras , (Türkiye) earthquakes
dc.typeArticle

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