Akademik Veri Yönetim Sistemi
Applied Sciences (Switzerland), cilt.15, sa.7, 2025 (SCI-Expanded)
The recent expansion of the strong-motion observation network, along with the increase in data obtained during major earthquakes and efforts to create consistent metadata for source, path, and site effects for both old and new records, has significantly improved the quality of data and the level of modeling in Türkiye. The mainshock and aftershock records of the 6 February 2023 Kahramanmaraş earthquake doublet (MW 7.8 and 7.7), which are among the most destructive earthquakes in world history, constitute an up-to-date and important data source for this study. In this study, we present new ground-motion prediction models (GMPMs) for shallow crustal earthquakes using strong-motion data recorded in Türkiye. Our GMPMs are calibrated using 20,173 strong-motion records from 1565 shallow crustal earthquakes with depths of less than 35 km that occurred in Türkiye and its vicinity between 1976 and 2023. Our model is valid for magnitudes ranging from 4.0 to 7.8 (MW), and for the time-averaged 30 m shear wave velocity (VS30) values of 975 stations, which ranged from 131 to 1862 m/s. In the analyses performed, using the recently developed site amplification model, we calculated the model coefficients using the mixed-effects regression algorithms used by the GMPM developers. Additionally, a heteroscedastic model was created for aleatory variability as a function of MW. The closest distance to the surface projection of the fault plane (RJB) is between 0 and 350 km. Using the metadata prepared according to these criteria, we derived up-to-date ground-motion prediction models for horizontal-component peak ground velocity (PGV), peak ground acceleration (PGA), and 5% damped pseudo-spectral acceleration (PSA) response spectra, at 36 periods ranging from 0.01 to 10 s. The variability in the predictions was decomposed into within-event, between-event, and site-to-site deviations to determine the total standard deviations (σ). Compared to previous models, the proposed GMPMs were developed using a much richer database with recent major earthquakes, and the consistent estimates and lower residuals in the comparisons support the reliability of the models.