## 3 Results
Considering the values of changes in the mean annual river temperatures, in each river, water temperature increased from 0.18 to 0.49 \({}^{\circ}\)C per decade. In each case the changes are statistically significant at a level of 0.05. Among the analysed rivers, the greatest water temperature increase can be seen to occur in the Wda River, and the lowest in the Bobr River. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**River**} & \multicolumn{3}{c}{**Temperature**} & \multirow{2}{*}{**a**} & \multirow{2}{*}{**b**} & \multirow{2}{*}{**Mo/Po**} & \multirow{2}{*}{**Underetimate**} & \multirow{2}{*}{**Overestimate**} \\ \cline{2-2} \cline{6-9}  & **Min** & & & & & & & \\ \hline Drweca & 0.1 & 21.8 & 9.8 & 0.9839 & 0.1491 & 8.8 & (8.8–21.9) & (0.1–8.8) \\ Leba & 0.5 & 16.3 & 8.2 & 0.9753 & 0.0174 & 0.7 & (0.7–16.3) & (0.5–0.7) \\ Lyna & 0.1 & 22.4 & 9.4 & 0.9918 & 0.0237 & 2.9 & (2.9–22.4) & (0.1–2.9) \\ Pisa & 0.1 & 23.0 & 9.6 & 1.0184 & \(-\)0.3877 & 21.1 & (0.1–21.1) & (21.1–23.0) \\ Wda & 0.2 & 19.9 & 9.0 & 0.9702 & 0.1871 & 6.3 & (6.3–19.9) & (0.2–6.3) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The quality of the prediction of river water temperatures was based on the multilayer perceptrone network/g model based on lake water temperature and air temperature from three meteorological stations. Figure 5: Linear slope (**a**,**c**,**e**,**g**,**j**) and Sen slope (**b**,**d**,**f**,**h**,**j**) values based on data reconstructed by means of multilayer perceptrome network models in the context of values obtained based on measurement data (blue line) and values obtained from the best multilayer perceptrome network/g model (red line) for rivers: Drweca (**a**,**b**), Leba (**c**,**d**), Lyna (**e**,**f**), Pisa (**g**,**h**) and Wda (i,j). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Period**} & \multirow{2}{*}{**Böbr \({}^{*}\)**} & \multirow{2}{*}{**Drawa \({}^{*}\)**} & \multirow{2}{*}{**Elk \({}^{*}\)**} & \multirow{2}{*}{**Guber \({}^{*}\)**} & \multicolumn{2}{c}{**River**} & \multirow{2}{*}{**Drweca**} & \multirow{2}{*}{**Leba**} & \multirow{2}{*}{**Lyna**} & \multirow{2}{*}{**Pisa**} & \multirow{2}{*}{**Wda**} \\ \cline{5-5} \cline{7-11}  & & & & & & & & & & \\ \hline Nov & **0.68** & **0.65** & **0.65** & **0.65** & **0.55** & **0.73** & **0.44** & **0.66** & **0.77** & **0.64** \\ Dec & **0.50** & **0.35** & **0.40** & 0.36 & **0.43** & **0.47** & **0.37** & **0.43** & **0.52** & **0.48** \\ Jan & \(-0.13\) & \(0.12\) & \(-0.18\) & \(-0.18\) & \(-0.18\) & \(-0.08\) & \(-0.18\) & \(-0.20\) & \(0.03\) & \(0.11\) \\ Feb & \(-0.17\) & \(-0.10\) & \(-0.03\) & \(-0.04\) & \(-0.16\) & \(0.00\) & \(-0.04\) & \(0.07\) & \(0.15\) & \(0.18\) \\ Mar & \(-0.12\) & \(0.02\) & \(0.06\) & \(0.12\) & \(0.24\) & \(0.30\) & \(0.19\) & \(0.26\) & \(0.47\) & \(0.41\) \\ Apr & **0.39** & \(0.32\) & \(0.40\) & \(0.35\) & **0.45** & \(0.41\) & **0.39** & \(0.45\) & **0.79** & **0.42** \\ May & \(0.17\) & \(0.15\) & \(0.30\) & \(0.32\) & \(0.12\) & \(0.06\) & **0.30** & \(0.46\) & \(0.35\) & **0.55** \\ Jun & **0.44** & **0.49** & **0.65** & \(0.57\) & **0.60** & **0.53** & **0.52** & **0.84** & **0.80** & **0.72** \\ Jul & \(0.27\) & \(0.22\) & \(0.27\) & \(0.22\) & **0.44** & \(0.14\) & **0.48** & **0.43** & \(0.44\) & **0.49** \\ Aug & \(0.18\) & **0.50** & **0.53** & \(0.28\) & **0.50** & **0.37** & **0.48** & **0.63** & **0.69** & **0.53** \\ Sep & **0.24** & **0.40** & **0.61** & **0.40** & **0.51** & **0.53** & **0.40** & **0.61** & **0.48** & **0.60** \\ Oct & \(0.24\) & **0.45** & \(0.40\) & \(0.37\) & \(0.36\) & **0.45** & **0.34** & \(0.41\) & **0.34** & **0.48** \\ Year & **0.18** & **0.33** & **0.30** & **0.25** & **0.29** & **0.34** & **0.28** & **0.44** & **0.47** & **0.49** \\ \hline \hline \end{tabular} Bold—values statistically significant at a level of 0.05 based on Mann–Kendall test; *—reconstructed data.  
\end{table} 
Table 4: Trendline slope values (Sen slope) in \({}^{\circ}\)C per decade in river waters in Poland.