# A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Turkiye
## 4 Results and Discussion  
Using ground-motion data recorded in Turkishye, we present a set of GMPMs derived from recordings of shallow earthquakes in active crustal regions and for application in Turkiye. While developing the prediction model, a thorough review of the existing literature was conducted to focus on the parameters and determine the functional form that could facilitate the analyses. Subsequently, the applicability of the selected form was examined, and the model coefficients were calculated for the chosen model with the existing dataset. The proposed models are developed for horizontal-component PGA, PGV, and 5%-damped PSA response spectra, at 36 periods ranging from 0.01 to 10 s. The new models provide a reliable description of horizontal ground-motion amplitudes for shallow (<35 km) crustal earthquakes in highly active tectonic regions such as Turkiye over a wide range of magnitudes, distances, and site conditions. Compared with other models, the GMPM model obtained from this study constitutes up-to-date and unique near-source data that include recent main shocks and aftershocks of the Van (23.10.2011, \(M_{\rm W}\) 7.1), Sivrice-Elazg (24.01.2020, \(M_{\rm W}\) 6.8), Aegean Sea (30.10.2020, \(M_{\rm W}\) 7.0), and Duzce (23.11.2022, \(M_{\rm W}\) 5.9) earthquakes and the Kahramanmaras earthquake doublet (Pazarck, Mw 7.8 and Elbistan, \(M_{\rm W}\) 7.7) on 6 February 2023. Therefore, our model uses a well-defined new large dataset  
Figure 13: Comparison of median 5%-damped response spectral acceleration (PSA) from the predictive model of this study with respect to some local and global GMPMs. The comparisons are made for a 5S events and rock site (\(V_{530}\) = 760 m/s) representing two different magnitude–distance scenarios: \(M_{\rm W}\) 6.0 and \(R_{\rm JB}\) 100 km (**top**), and \(M_{\rm W}\) 7.2 and \(R_{\rm JB}\) 15 km (**bottom**). Abbreviations: [PERSON] et al. [37], ASK14; [PERSON] et al. [15], BSSA14; [PERSON] [38], CB14; [PERSON] and Youngs [16], CY14; [PERSON] [43]; I14; [PERSON] et al. [17]; ASB14; [PERSON] et al. [6]; [PERSON]; [PERSON] et al. [7]; KAAH13; [PERSON] et al. [8]; [PERSON]; [PERSON] et al. [18]; [PERSON]; [PERSON] et al. [9]; B21; [PERSON] [19], IS23. (20,173 records, 1565 events, 957 stations) and represents a rare example on a regional scale. It is calibrated using data with moment magnitudes ranging from 4.0 to 7.8, distances from 0 to 350 km, and \(V_{530}\) values between 131 and 1862 m/s. Ground-motion intensity measures (GMIMs) are preferred as the median of the orientation-independent amplitudes (RotD50), and the source-to-site metrics are defined based on the closest distance to the surface projection of the fault plane (\(R_{JB}\)). Events are categorized according to style of faulting (SoF) as strike-slip (\(SS\)), normal-slip (\(NS\)) and reverse-slip (\(RS\)) events. To reduce epistemic uncertainties as much as possible, strong-motion records with moment magnitude, faulting style, in situ measured \(V_{530}\), and well-calculated distance information are included in the dataset. In this study, we calculated each coefficient using mixed-effects regression. A two-stage regression analysis was used to derive the model coefficients. In the first stage, the model coefficients were estimated, followed by a residual analysis under the assumption of homoscedasticity. In the second stage, we relaxed this assumption and applied a heteroscedastic variance model, where variance depended on magnitude. Consistent predictions observed in comparisons with global or local GMPMs support the reliability of the proposed model. To increase the confidence interval of the standard deviations calculated from statistical studies, the data sets need to be further improved. The most significant reductions in standard deviation can be achieved by defining site conditions using only in-situ measured \(V_{530}\) values and using events with moment magnitudes based solely on moment tensor solutions.