## 2 Methodology and Site Description  
### Sea Water Elevation Prediction  
Sea water level is a random process resulting from the simultaneous combination of several mechanisms, three of which are found to be dominant, those being tidal-induced oscillations and oscillations due to barometric pressure changes and wind-generated waves. Although characterized by different time scales, those three mechanisms simultaneously contribute to the absolute sea water elevation definition. Tidal-induced sea water oscillations are driven by tidal forcing, which is induced by simultaneous inter gravity forces between the Sun, Moon and Earth. Tidal-induced changes are characterized as a mixed semidiurnal type at the location of interest, with main periodic intervals corresponding to both semi diurnal and diurnal ones. Compared to tidal oscillations, sea level changes induced by barometric pressure changes are aperiodic with time scales corresponding to two main factors: (i) daily barometric pressure changes corresponding to daily scale air temperature change and (ii) time scales corresponding to the time necessary for the air mass transfer from different geographic locations to the location of interest to occur. The latter corresponds to time scales usually equal to several hours. Wind-generated waves are characterized by very small time scales, up to 8 s in the area of interest, and these are generated as a result of the air mass kinematic energy transfer to the sea surface. Previous research [22] has shown that tides characterizing the Adriatic Sea basin consist mainly of seven dominant constituents, of which three are diurnal (O1, P1 and K1) and four are semidiurnal (N2, M2, S2 and K2). In its origin, each constituent represents a sinusoidal function with an associated amplitude, period, and phase, contributing to the full tidal signal. To determine the unknown values of the amplitudes, periods and phases, the original signal is initially transferred from the time to frequency domain by applying the Discrete Fourier Transform (DFT) [22]. DFT results are often plotted as Amplitude Spectral Density (ASD). By normalizing magnitudes with number of samples, the amplitude of each frequency can be easily obtained. Due to the fact that DFT calculations are time demanding [23], Fast Fourier Transform (FFT) [24] incorporated in Python in SciPy library [23] has been used for faster transfer of signals from the time to frequency domain. Based on the determined tidal constituent parameters, the tidal-induced sea level can be simulated using a linear superposition of sine functions corresponding to the number of relevant constituents:  
\[h_{t}=\sum_{i=1}^{7}A_{i}\times\sin\left(\frac{2\pi t}{t_{pi}}+\frac{2\pi\varphi _{i}}{360}\right),\ t=0,\ 1,\ \ldots,\ M \tag{1}\]  
where \(h_{t}\) is the simulated sea level [m], \(A_{i}\) is the amplitude [m], \(t_{pi}\) is the period [h] and \(\varphi_{i}\) phase [\({}^{\circ}\)] of \(i\)-th constituent, \(M\) is the sample size and \(t\) is relative time [h]. Simulated sea level \(h_{sea}\) can be calculated as a superposition of tidal harmonics from Equation (2) by adding the mean sea level value calculated from the observed sea level signal:  
\[h_{sea}=h_{t}+\overline{h} \tag{2}\]  
where \(h_{t}\) represents tidally induced sea level oscillations and \(\overline{h}\) represents the mean sea level value. Increasing the barometric pressure by 1 [cm] of the saltwater column leads to a decrease in the sea level by approximately 1 [cm] and inversely, decreasing the barometric pressure by 1 [cm] raises the sea level by 1 [cm] [25]. This effect is called the Invert Barometric effect (IB). The sea level rise caused by the change of the barometric pressure can be calculated as follows:  
\[h_{at}=\frac{-p_{a}}{\rho g} \tag{3}\]  
where \(h_{at}\) is the sea level change resulting from a change in barometric pressure, \(p_{a}\) is the barometric pressure [Pa] change, \(\rho\) is the density of sea water [kg/m\({}^{3}\)] and \(g\) is the gravitational acceleration [m/s\({}^{2}\)].