## 2 Materials and Methods  
Ground displacement data measured by GPS are taken from the website [24]. These data represent displacements of the Earth's surface in three orthogonal directions, which we will further denote as E, N, and Up for displacements in the west-east, north-south and vertical directions, with a time step of 5 min [25]. Figure 1a shows the positions of GPS points for measuring displacements of the Earth's surface, as well as 16 numbered reference points. These points will be further needed to assess the spatial correlations between the properties of the Earth's surface tremors. Reference point positions were noted as the centers of 16 clusters of GPS stations using the K-means method [26]. The numbering was performed by decreasing the latitude of the reference points. Figure 1b presents the density of GPS stations, which were estimated by Gaussian kernel method [26] with bandwidth 0.5\({}^{\circ}\) (\(\approx\)56 km), within a regular 30 \(\times\) 30 network of nodes which covered the region. Figure 1c shows a graph of the daily number of operational GPS stations for 13 years of observations, 2009-2021. By operational stations on the current day, we mean those stations for which the total number of missing data does not exceed 10% of the duration of the daily window of 288 counts with a time step of 5 min, that is, no more than 28 values. Missing data are filled in with \"plausible\" artificial data, the values of which are determined by the behavior of the signals in adjacent intervals of the same length as the length of the gap. This data replenishment operation is described in detail in [19]. Minimum Normalized Wavelet-Based Entropy \(\mathit{En}_{\mathit{W}}\) and Wavelet-Based Spectral Index \(\beta_{\mathit{W}}\)  
Let \(c_{j}^{(k)}\) be wavelet coefficients of the analyzed signal \(x(t)\), \(t\ =\ 1,\ldots,L\)-discrete index numbering successive readings. The upper index \(k\) is the number of the detail level of the orthogonal wavelet decomposition, the lower index \(j\) numbers the sequence of time interval centers in the vicinity of which the signal convolution with finite elements of the basis is calculated. Below, 17 orthogonal Daubechies wavelets were used: 10 ordinary bases with minimal support with the number of vanishing moments from 1 to 10 and 7 so-called Daubechies symlets [27], with the number of vanishing moments from 4 to 10. For each of the bases, the normalized entropy of the distribution of squares was calculated coefficients and found a basis that provides the minimum entropy:  
\[\mathit{En}_{\mathit{W}}\ =\ -\sum_{k}^{m}\sum_{j\ =\ 1}^{M_{k}}p_{j}^{(k)}\cdot \ln(p_{j}^{(k)})/\ln(N_{r})\rightarrow\min,\ \ p_{j}^{(k)}\ =\ |c_{j}^{(k)}|^{2}/\sum_{l,j}|c_{i}^{(l)}|^{2} \tag{1}\]  
Here, \(m\) is the number of detail levels taken into consideration, and \(M_{k}\) is the number of wavelet coefficients at the detail level with the number \(k\). The number of levels \(m\) depends on the length \(L\) of the analyzed sample. For example, if \(L\ =\ 2^{n}\), then \(m\ =\ n\), and \(M_{k}\ =\ 2^{(n-k)}\). The condition \(L\ =\ 2^{n}\) is necessary for applying the fast wavelet transform. If the length \(L\) is not equal to a power of two, then the signal \(x(t)\) is padded with zeros to the minimum length \(N\), which is greater than or equal to \(L\): \(N\ =\ 2^{n}\geq L\). In this case, among the number \(2^{(n-k)}\) of all wavelet coefficients at the level \(k\), only \(L\cdot 2^{-k}\) coefficients correspond to the decomposition of the real signal, while the remaining coefficients are approximately equal to zero due to the addition of zeros to the signal \(x(t)\).