## 3 Results
### Prediction of Shearing in Relation to Surface Displacements  
One of the goals of the study was to develop a model that would be able to indicate the presence of a shear zone in relation to surface displacements. It was assumed that the shear displacements will affect the surface displacement. However, the analysis showed no unequivocal relationship visible at each measurement point. The displacement recorded by benchmarks can be influenced by many factors, and shearing is only one of them. In addition, the nature of the dependence at different dam locations may be different due to the different geological structures and a number of other factors. It was also noticed when comparing the annual increments of benchmark displacements with the increments  
Figure 3: Moran scatterplot for displacement velocity (**a**) and displacement acceleration (**b**). of displacements caused by shearing in individual locations. There is no correlation in the scattering diagram, and in addition, it can be seen that large surface displacements may appear in places where the amount of shear has not changed (Figure 5). The coefficient of determination \(R^{2}\) obtained for the relationship between the velocity resulting from shear and the velocity of benchmark displacement for the entire sample is only about 0.03, which indicates a lack of linear relationship between the variables. When looking at individual locations, it can be seen that there is a certain dependency. The displacement of adjacent benchmarks was also taken into account, for which sometimes there is a greater dependence than in the case of displacements in the same location (Figure 6). For each example, \(R^{2}\) values were determined for the linear regression fit between both the shear velocity and the displacement velocity of the benchmark at the same location and between the shear velocity and the displacement velocity of adjacent  
Figure 4: Hot spot analysis result for velocity and acceleration of displacement for two sample simulations. Figure 5: Relationship between surface displacements and shear displacements for all measurement points. benchmarks. For the presented examples, the values range from 0.27 to 0.84. In some cases, a higher value is obtained for the fit to adjacent benchmarks. This shows that the relationship between underground shear and surface displacement can be partially described by linear regression. However, it is necessary to add a variable related to the location to the analysis. Additionally, it can be seen that not only is the displacement at one specific point valuable information, but also in the adjacent surroundings. Due to the existence of different relationships in different locations, it was decided to use the GWR model to describe the observed phenomena. It is used to select regression coefficients relative to geographic location. The model uses the independent variables the velocity of benchmark displacement and the velocity of displacement of benchmarks in the vicinity, and the dependent variable is the velocity of displacement resulting from shearing. A model with \(\text{R}^{2}=0.455\) and \(\text{RMSE}=5\) was obtained, which means that the accuracy is medium, as it explains about 45% of the values. The second indicator shows the possible expected difference between the predicted and actual value. The obtained value in the case of small shears indicates the possibility of a significant relative difference in values. This confirms the assumption that underground shears do not depend only on surface displacements, but the result can be used to estimate the shear risk. Hence, the decision was made to streamline the presentation of results, focusing solely on the level of risk. Predicted higher shear values correspond to greater risk and lower shear values mean less risk. An exemplary visualization of the results with a comparison of the risk of shearing in three years is shown in Figure 7. Attention should be paid to the changes in risk areas over time.