## 3 Results  
### Modeling Results Calibration Process  
The mathematical modeling itself using FEM was first performed for the purpose of calibrating the compiled model for the average values of the GWL for the hydrological years 1995-2020, and then verification of the model was performed for the maximum level of GWL corresponding to the month of April 2006. The calibration of the model consisted of setting the hydraulic and hydrogeological parameters of the aquifer with a detailed view of the area of the future TEN-T route. The calibration parameters were the drainage and infiltration resistance values of the bottom of the streams and the inflow from the slopes of the Little Carpathians in the west and northwest of the area. Another calibration factor was the choice of the interpolation method in the parameterization of the environment. For the parameterization of the input data, the TinInt method appeared to be the most suitable. The selected parameterization results are shown in Figures 8 and 9. The results of the calibration, i.e., the determination of differences between the measured and simulated GWL values in the monitored area (deviation), are presented in graphic form, as these values are only informative. For the average GWL, they are shown in Figure 11 and for both the average and maximum GWL in Figure 12. The color differentiation of the numbers outlined in the figures indicates positive or negative differences between the measured and simulated values. A positive value (blue) meant that the simulated value was greater than the measured value, and correspondingly, if the value was negative (red), then the simulated groundwater level was lower than the measured value. It can be seen from the images that there are, of course, differences in the average GWL status, and the differences near the area of interest are, at most, up to \(\pm\)0.70 m. These differences were not negligible, but we believed that even considering the variance in the GWL from 1.33 to 6.33 m, these values were acceptable, which was also confirmed by other calibration criteria, the results of which are shown in the Table 1. Further refinement of the results could be achieved by choosing a different model, as discussed in [31]. However, this was not the primary objective of our research. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Model** & **Average GWL** & **Maximum GWL** \\ \hline Minimum deviation (m) & \(-\)0.86 & \(-\)0.95 \\ Maximum deviation (m) & +0.72 & +0.83 \\ _RMSE_ (m) & 0.127 & 0.288 \\ _NRMS_ (\%) & 1.46 & 3.13 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of the simulation results for the cluster near the planned TEN-T track project. Figure 10: Demonstration of the gradual refinement of the finite element mesh (maximum element length of 150 m and minimum element length of 2 m) (**a**–**h**) in the center of Bratislava and (**i**–**n**) in the Petrzalka region [17]. ((**e,f**) openings are indicated by a red rectangle). The results of the calibration, i.e., the determination of differences between the measured and simulated can also be compared with the calibration criteria i.e., the quantitative comparative criteria for determining the quality of the model, were determined by the Root Mean Squared Error (\(RMSE\)) [32] calculation, as follows:  
\[RMSE=\left[\frac{1}{n}\sum_{i=1}^{n}(h_{m}-h_{s})_{i}^{2}\right]^{0.5}, \tag{5}\]  
where \(n\) is the number of checkpoints (observation wells), \(h_{m}\) is the measured GWL (m a.s.l) value at a certain control point \(i\), and \(h_{s}\) is the simulated GWL (m a.s.l) value at the same location. Another method for determining the calibration criteria (except for the deviation (difference in Figure 11) and \(RMSE\)) could be the Normalized Root Mean Squared (\(NRMS\))  
Figure 11: Comparison of the simulation results. The difference (m) between the simulated and measured GWL values (average for the period 1995–2020) in (**a**) the center of Bratislava and (**b**) the Petrzalka region [17].