## 4 Discussion  
For the study site, as it is shown in Figure 6, with decreasing hazard level, the distribution of the magnitudes gets narrower and tends to the maximum possible magnitude of the closest source. These justify the assumption to use the marginal distribution for magnitudes since the distribution of the magnitudes is getting narrow at the low hazard levels interesting from the point of view of nuclear safety. The estimation of the exceedance probability for maximum fault displacement, \(\overline{D}\) (Figure 7a) is overconservative, because all earthquakes at the fault with rupture length \(L\) are assumed to be centered relative to the site (\(l/L=0.5\)) and \(\mathbf{r}=0\), see Figure 3. Note, the contribution of the closest bin remains around 10% for all hazard levels as it is seen in Figure 6b. Therefore, the calculation that accounts just the magnitude distribution for the proximal to the site bin (\(w_{i}\)\(m_{r=0,i}\)) should provide a more reasonable estimation of the displacement hazard as it is shown in Figure 7b. The conservatism of the calculation of the exceedance probability versus displacement could further be reduced if the empirical  
Figure 8: Mean hazard curve for distributed faulting displacement. correlation for averaged displacement \(D_{\text{ave}}\) would be used in Equations (10) and (11) according to [PERSON] and Coppersmith [22]. The above considerations on the conservativeness are valid for the estimation of the mean hazard curve for the contribution of the distributed faulting. The mean hazard curve in Figure 6 shows that the contribution of distributed faulting is much less than the on-fault displacement. The uncertainties of the empirical correlation for \(D\) are considered via standard deviations given for the corresponding empirical correlations. The epistemic and aleatory uncertainties regarding seismotectonic modelling is accounted for in the PSHA for all hazard levels. Thus, instead of the logic-tree modelling that is required by the probabilistic fault displacement hazard analysis, the epistemic uncertainties are accounted for in the logic tree modeling of the seismotectonic sources in the probabilistic seismic hazard assessment. As it has been mentioned in the introduction, trenching reveals a late-Pleistocene (approximately 20 thousand years old) \(20\div 25\) mm horizontal movement [11]. The observed displacements are indicated in Figure 7a,b. By chance, these values sit on the curve \"minus standard deviation\" at \(\approx\)\(5\times 10^{-5}/\text{a}\) in case of more conservative estimation obtained by Equation (10). If the less conservative analysis is made using Equation (11), the observed indications of the movement fit to the mean hazard curve. The coincidence of the observed in the trenching movements with the predicted one could be interpreted as proof of the adequacy of the proposed calculation procedure. Of course, these rather uncertain indications of near-surface displacement are insufficient for the empirical validation of the proposed methodology. Unfortunately, at the studied site, the only evidence of the near surface displacements is the mentioned above indications. Data or observations on surface displacements in the entire central part of the Pannonian Basin are practically missing. Therefore, there are two actions planned for systematic validation of the methodology. First, a step-by-step comparison of the proposed method with the probabilistic fault displacement hazard evaluation procedure could be performed. Validation of the methodology against the empirical data should also be a research task for the future. An option could be a trial implementation of the method for a site where both probabilistic seismic hazard assessment and probabilistic fault displacement hazard assessment have been made, as for example for the Krsko nuclear site in Slovenia, see [PERSON] et al. [23]. However, such a comparison requiring international cooperation exceeds the frame of the recent paper.