## 3 Data Analysis
### Effect of S1-SSM Temporal Resolution  
The behavior of soil moisture values following rainfall events was then studied as a function of the time lag between the rainfall date and the S1-SSM date. In fact, soil moisture values are mainly affected by precipitation events, evaporation, runoff, and snow melt. In this analysis, only the effect of precipitation was studied. To study the effect of the time difference between the date of S1-SSM maps and the date of rainfall events, S1-SSM values were plotted as a function of the recorded six days of cumulative precipitation values (Figure 5). For the 0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\) GPM grid, the mean S1-SSM values were calculated from each available S1-SSM map. The cumulative precipitation was computed for six days, because the revisit time of derived S1-SSM maps is for six days over our study site. The results showed that for low cumulative precipitation for six days preceding the S1-SSM map date (for example, less than 20 mm), the soil moisture values are distributed on a wide range between 10-25 vol.% (Figure 5). This wide range of S1-SSM values was expected, since low precipitation would induce high S1-SSM values if the precipitation occurs in the 24 hours preceding S1 acquisition, whereas low precipitation would not induce an increase of S1-SSM if it occurs a couple of days before S1 acquisition. As the cumulative precipitation for six days is high (for example 100 mm, Figure 5), the S1-SSM values become more homogenous and high. Indeed, high cumulative precipitation for six days (for example, higher than 100 mm) induces high S1-SSM values, even if the precipitation occurs six days before S1 acquisition, in particular during winter, and the evaporation rate is low. Figure 4: Temporal evolution of temperature and precipitation data recorded at a local meteorological station in Auch, Cocitanie region. Figure 5: S1-SSM distribution as a function of six days of cumulative precipitation (revisit time of S1-SSM = six days). To illustrate the results presented in Figure 5, three cases of rainfall events with different time intervals between the S1-SSM map's date and the rainfall date were studied for Gard Department of Occitanie. First, for the S1-SSM map of 16 October 2016, the latest rainfall event before 16 October 2016 took place on 12 October 2016 with an average cumulative precipitation of 100 mm in 24 hours (Figure 6a.) Then, between 12 October 2016 and 16 October 2016, no precipitation was recorded. The soil moisture map of 16 October 2017 shows wet soil conditions with S1-SSM values between 20-25 vol.%. On the other S1-SSM map acquired on 26 January 2017, a rainfall event occurred on the same date a few hours before the S1 acquisition date (26 January 2017) with 20 mm of cumulative precipitation (Figure 6b). Consequently, the soil moisture attained very high values: higher than 25 vol.%. The department didn't encounter any rainfall event for 29 days prior to 26 January 2017 (the soil moisture map that was acquired six days before 26 January 2017 showed soil moisture values of 13 vol.%). Similar soil moisture values were recorded on the S1-SSM map of 27 January 2018 (Figure 6c), where the department was affected by a light rain event 24 hours before the S1-SSM date (nine mm). Wet soil moisture values higher than 25 vol.% were estimated over the department. Prior to this rainfall event on 26 January 2018, no events were detected for the previous six days, and the soil moisture values six days before presented dry values (15 vol.%). This result assures that the detection of rainfall events on S1-SSM is highly dependent on the S1-SSM revisit time. Indeed, a few mm of precipitation just 24 hours before the S1-SSM map shows higher soil moisture values (for example on 27 January 2018) than an extreme event rainfall event (for example on 12 October 2016) four days before the S1-SSM map (16 October 2016). Thus, the six days of temporal resolution of the S1-SSM map doesn't always permit the detection of an extreme rainfall event.