# A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Turkiye
## 1 Introduction
[20] derived a model only for PGA using 221 records of 122 events with earthquake magnitude \(M_{W}\geq 4.0\), without considering fault types, and using an epicenter distance (\(R_{qri}\)) \(<100\) km. [PERSON] et al. [10] proposed models for PGA and PSA based on a database that considered the geometric mean of two horizontal components from 195 acceleration records of 17 earthquakes (\(M_{W}\geq 5.0\)) that occurred in Northwestern Turkiye. The dataset included records with source-to-site distances \(R_{JB}<100\) km, and site classifications were determined based on \(Vs\) values. [PERSON] and [PERSON] [12] proposed equations for PGA and PSA using a dataset consisting of 168 strong-motion records belonging to 49 earthquakes (\(M_{W}\) 4.0-6.4) that occurred in the Western Anatolia Region, with a focal distance (\(R_{hyp}\)) of 15-200 km and the horizontal-vertical spectral ratio (HVSR) for the site class. These GMPMs are derived from old catalogues of Turkish data and tend to overestimate ground motions, which can be attributed to assumptions made by their developers due to inadequate database information (i.e., estimated ground conditions, source -site distance measurements, and hybrid magnitude scaling; [PERSON] et al. [21]) about the time they were derived. [PERSON] and [PERSON] [4] developed models for PGA and PSA using 1259 horizontal component records of 573 events in the magnitude range of \(3.5\leq M_{W}\leq 7.6\), a source-to-site distance \(0\leq R_{bg}\leq 200\) km, associated with ground class \(V_{S30}\), and categorized according to SoF (\(S\)S: 70%, \(NS\): 28%, and \(RS\): 2%). For the reliability of GMPMs, comprehensive metadata consisting of correctly calculated seismological parameters, well-defined source-site metrics, in situ measured \(V_{S30}\) values, and high-quality recorded and processed strong-motion records with appropriate procedures come to the fore. The reliability of the estimated ground motion directly depends on the characteristics of the dataset. The errors and uncertainties (epistemic and aleatory) in the dependent and independent variables should ideally be kept to a minimum. Epistemic uncertainties are factors that need to be considered in prediction equations, and they arise from insufficient knowledge of seismic-source mechanisms, wave spreading paths, and site effects. Aleatory uncertainty is attributed to outcomes that cannot be predicted, whereas epistemic uncertainty is attributed to missing information. To account for epistemic uncertainties when determining the seismic hazard level of a region, both regional and global GMPEs may be used [4]. For reliable seismic hazard studies in different countries or regions, appropriate GMPMs need to be developed and used. In recent years, international projects have been initiated due to the need for access to and the improvement of strong-motion data for earthquake engineering and engineering seismology applications. The primary aim of these projects is to collect significant ground-motion records on a global scale, ensure the consistent and reliable processing of all data, and create comprehensive metadata describing source, path, and site effects for these records, making them accessible to everyone. One of the comprehensive projects developed for this purpose is the two-phase Next-Generation Attenuation (NGA) Ground Motion Project, supported by PEER, comprising the NGA-West1 and NGA-West2 projects [22; 23]. Another good example is the Engineering Strong-Motion (ESM) dataset developed by the European Plate Observing System (EPOS) project. Within the scope of the ESM program, it has established a standard for the dissemination of metadata and parameters for engineering seismology applications in Europe, similar to NGA-West in the USA [24]. Similarly, the first comprehensive compilation and processing of the strong ground-motion dataset in Turkiye was carried out by [PERSON] et al. [21] for 4671 strong-motion records between 1976 and 2007.