## 2 Materials and Methods
### Seismic Scenarios  
We compiled a set of seismic scenarios to assess the seismic hazard in the broader WGoC area in terms of maximum expected strong ground motion from specific seismic sources. These scenarios were generated through stochastic simulations for a predicted maximum magnitude (M\({}_{\text{max}}\)) for well-studied known faults in the area. Simulations were performed using a stochastic finite-fault model based on a dynamic corner frequency approach with the EXSIM code [80, 81]. The modeling strategy was based upon the discretization of the earthquake fault plane into smaller subfaults, each of which was considered as a potential earthquake source. The point-source stochastic method [82] was employed to generate synthetic time series for each subfault. The summation of the individual contributions of each subfault, along with a suitable time delay, led to the final ground motion parameters at the sites of interest. This approach has been widely implemented worldwide [83], as well as in Greece [84, 85, 86, 87, 88]. The anticipated strong ground motion at a given site is a result of a complex physical process that includes the relative contribution of source, path, and local site effects. Source effects describe the characteristics of the accumulated strain release from the fault, which, when released, results in the generation of an earthquake. These include, among others, the source dimensions (length, width), the moment magnitude (M\({}_{\text{w}}\)), the slip distribution for the causative fault, and the stress parameter (\(\Delta\sigma\)). After the earthquake nucleation and rupture, seismic waves travel through the Earth's crust; therefore, path properties must also be taken into account. Their propagation is most strongly affected by two path parameters; i.e., the geometrical spreading and the anelastic attenuation, which is controlled  
Figure 2: The logic tree constructed to calculate PGA, PGV, and S\({}_{\text{a}}\). All branches have the same weighting coefficient. Results were generated for return periods of 475 and 950 years for both PGA and PGV and 475 years for S\({}_{\text{a}}\). Abbreviations: VAM16: [PERSON] et al. [65], CHO18: [PERSON] et al. [78], SAK16: [PERSON] [77], DAT07: [PERSON] and [PERSON] [76], SKA07: [PERSON] et al. [75], SKA03: [PERSON] et al. [75], MAR02: [PERSON] et al. [74]. by the quality factor (Q). Ultimately, the local site properties play an important role in the resulting surface ground motions, given that the impact of the shallower layers may lead to significant amplification of the seismic waves. These effects are treated by the EXSIM code using the kappa (\(\kappa_{0}\)) parameter [89] and user-defined soil amplification factors. As a first step to obtain high-resolution model parameters for the desired earthquake scenarios, we performed a stochastic simulation of the most recent strong (M\({}_{\rm w}\geq 6.0\)) earthquake in the study area; namely, the 1995 Aigion M\({}_{\rm S}\) = 6.2 (M\({}_{\rm w}\) = 6.5 according to the Global Centroid Moment Tensor (CMT) project) mainshock [29]. Modeling of past earthquakes in the study area can significantly help in constraining the path and site components of strong ground motion through comparison with GMPEs, as well as with real strong motion data. In the case of the Aigion 1995 mainshock, 17 recordings from seismic stations up to an epicentral distance of 140 km are available, allowing the calibration of the synthetic results through an iterative procedure to achieve the best fit. The final model parameters are summarized in Table 1. The causative fault's dimensions and geometry (strike and dip) were adopted following [29] and the upper edge of the fault plane was set according to the model from [PERSON] et al. [90], which is in compliance with the geometry of the seismogenic layer of the study area. The slip distribution onto the fault plane was modeled through a random slip pattern, given that detailed finite-fault slip inversions are not available for this case.