### Modified Rel Model and Proposed Piecewise Approach
The final version of our proposed Modified REL model was developed to model the signal loss and reflection effects between the Tx and Rx more accurately as follows:  
\[RSSI_{modifiedREL}[dBm]=P_{t}[dBm]+G_{td}[dBi]+G_{rd}[dBi]- \tag{7}\] \[L_{FSPL}[dB]+F_{modifiedREL}[dB]\pm L_{diff}[dB]-A[dB]\]  
where \(P_{t}[dBm]\) is the Tx power, \(G_{td}[dBi]\) and \(G_{rd}[dBi]\) are the Tx and Rx antenna for the direct wave direction gains, respectively, \(L_{FSPL}[dB]\) is the free space path loss, \(F_{modified\,fidREL}[dB]\) is the improved pattern propagation factor, \(A[dB]\) is the rain attenuation [23], and \(L_{Diff}[dB]\) is the diffraction loss (can be positive or negative) caused by the bending of the signal around obstacles. In the calculations for the \(L_{Diff}\) parameter according to all measurements, because the measurement distance (\(d\)) was smaller than the distance corresponding to 60% of the Fresnel zone (\(D_{06}\)), \(L_{Diff}\) was taken as 0 dB in the calculations. Moreover, based on the meteorological data, the rain attenuation parameter \(A[dB]\) was considered only for the M1 scenario. The roughness coefficient \(\rho_{s}\) used to determine the effective Fresnel reflection coefficient while calculating the \(F_{modifiedREL}\) was calculated according to the \(\sigma_{h}[m]\) (RMS surface height) value corresponding to the sea state according to the Beaufort scale [24]. \(\beta_{0}\) (RMS surface slope), required for the calculation of the shadowing coefficient (\(S\)), was estimated according to the meteorological data of the measurement days and comments of the boat captain on the regional weather and sea conditions [11; 12]. Considering the Beaufort scale, the wave heights and wind intensities specified in the meteorological data of the measurement days correspond to 2 and 3 sea states [25]. When the wave height--\(\beta_{0}\) graph created based on the measurements is examined, it is seen that \(\beta_{0}\) varies between 0.04 and 0.07 for 1-4 m wave height [26]. For our study, the default \(\beta_{0}\) values were taken into consideration as below 0.04 due to the wave height being at most 0.5 m in the scenarios, and the best \(\beta_{0}\) estimation was performed for the lowest RMSE [1]. The obtained \(\beta_{0}\) values were consistent with the meteorological data. As a result, using the above-defined parameters in the Modified REL model, the signal loss was estimated more accurately. This model provides a more accurate calculation of signal power both in free space and in environments with complex effects, such as reflection and diffraction. Optimization of the \(h_{rbest}\) parameter and the addition of angle-dependent gains make the model more robust and show superior performance with lower error rates in different environments. Finally, in this study, a piecewise modeling approach was also proposed that aims to represent the complex propagation characteristics more accurately by separating the signal propagation into two different regions. This model, which we call the Proposed Piecewise model, divides the propagation medium into two regions using the \(d_{break}\) point, which is calculated from Fresnel zone theory, similar to the dual-slope model approach, using the Modified REL model for the first region and the log-distance model for the second region. The basis of the model is the use of different path loss models for both regions as follows:  
\[ProposedPiecewise= \begin{cases}RSSI_{ModifiedREL}&for\quad d\leq d_{break}, \quad(Region1)\\ RSSI_{log-distance}&for\quad d>d_{break},\quad(Region2)\end{cases}  \tag{8}\]  
The breakpoint (\(d_{break}=\frac{4h_{t}h_{obs}}{\lambda}\)) determines the boundary between two different propagation regions and is calculated using the Fresnel zone theory that calculates the breakpoint using \(h_{t}\), \(h_{rbest}\), and \(\lambda\).