## 4 Results
### Wet Snow and Streamflow Interaction  
To understand better how wet-snow dynamics are connected to baseflow, a depletion curve was drawn. Only melting cycles with a duration higher than 48 days were chosen for this analysis, thus supporting the representativeness of the analysis having enough S1-SAR images per analyzed cycle. All these curves show a similar shape that can be described like a piecewise function composed by three parts (Figure 9):  
* Part 1 is represented by a linear and an almost horizontal function. Here, there is a high increase in the number of wet snow pixels with almost no change in baseflow response. Hence, this part reflects the delay observed between the beginning of the melting period and the actual response in the river;
* Part 2 can be represented by a power function. In this case, there is an increasing pattern in both variables, which means that both processes, the melting and the baseflow response were occurring at the same time;
* Part 3 follows again a linear function, but in this case, with a vertical pattern. Therefore, the behavior here is the opposite compared to Part 1, that is, we observe an increase in baseflow with limited contribution of wet snow pixels. Then, this part represents the time when almost no contribution from wet snow is happening but baseflow is still contributing to the streamflow. The black symbols over the curves verified this temporal pattern. For example, in the blue curve that represents the 2017-2018, each of them marks the 25% (\(\bullet\)), 50% (\(\times\)), and 75% (+) of the total time of each cycle. These black symbols are almost aligned in all curves and marks approximately for each case the beginning and end of the three parts of the piecewise function explained above. Moreover, and despite observing this common shape for all curves, these three defined parts were smoothed toward a unique linear pattern when we move from right (brown curve) to left (blue curve) in Figure 9. These differences are connected to the total amount of snow storage during the accumulation period of each melting cycle. For the same number  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Melting** & **Beginning** & **End** & **Duration** & **Precipitation** & **Snowfall** & **Average Daily** & **Average Minimum** & **Mean** & **Maximum** \\
**Cyde** & **Beginning** & **End** & **(Days)** & **(mm)** & **(mm)** & **Temperature** & **Daily Temperature** & **SWE** & **SWE** \\  & & & & & & & (°C) & **(mm)** & **(mm)** \\ \hline \multicolumn{10}{c}{2016–2017} \\ C-1 & 17-11-2016 & 05-12-2016 & 18 & 256 & 159 & 0.5 & –3.0 & 85.2 & 140.2 \\ C-2 & 11-21-2016 & 04-01-2017 & 24 & 92 & _67_ & 1.3 & –2.0 & 85.8 & 125.2 \\ C-3 & 09-02-2017 & 04-05-2017 & 84 & 233 & 140 & 3.5 & –0.6 & 23.9 & 78.7 \\ C-1 & 05-01-2018 & 23-01-2018 & 18 & 41 & 36 & 0.2 & –4.0 & 14.3 & 26.4 \\ C-2 & 29-01-2018 & 16-02-2018 & 18 & 32 & 31 & 2.9 & –7.2 & 12.43 & 25.9 \\ C-3 & 28-02-2018 & 09-08-2018 & 162 & 585 & 395 & 7.3 & 3.2 & 43 of wet snow pixels, the blue curve generates a considerably higher amount of baseflow than the brown curve. Since S-1 SAR imagery was able to detect wet snow pixels but not the total liquid content stored in the snowpack, the observed patterns suggested that SWE in the blue curve was higher than in the brown one. When analyzing the maximum SWE achieved in each of the accumulation cycles that preceded each of the observed melting cycles, this hypothesis was verified. The blue curve had a maximum SWE of 184 mm while the brown one reached just 43 mm (Table 3). Extending this analysis to the rest of the cycles, we observed that the pattern is fulfilled, from left to right, for blue (184 mm), green (78 mm), orange (61 mm), purple (52 mm), and brown (43 mm). That is, the higher the maximum SWE achieved in the snow cycle, the more linear relationship between wet snow pixels contributing to the runoff and baseflow is found.