## 4 Discussion  
The results obtained in Section 3 show that the detection of heavy rainfall using S1-SSM values is highly dependent on the time lag between the heavy rainfall event and the S1-SSM acquisition. Figure 5 showed that, on average, SSM values varied between 15 vol.% for five mm of accumulated precipitation in six days to about 22 vol.% for accumulated precipitation greater than 100 mm in six days. In addition, when the accumulated precipitation was less than 30 mm, 75% of the pixels (0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\)) showed SSM values lower than 22 vol.%, and the remaining 25% had SSM values between 20-28 vol.%. On the other hand, when the accumulated precipitation is higher than 100 mm in six days, 75% of the pixels have SSM values higher than 22 vol.%, while the remaining 25% of the pixels have SSM values between 20-22 vol.%. Moreover, for six days of cumulative precipitation between 30-100 mm, the SSM values varied between 15-28 vol.%. Thus, the results show that low rainfall of less than 30 mm in six days and very heavy rainfall greater than 100 mm in six days generally result in different soil moisture conditions in approximately 75% of the cases. However, it remains difficult to distinguish between high SSM values (around 28 vol.%) corresponding to (1) light rain the day before the S1 acquisition, (2) heavy rainfall a few days before the radar acquisition, or (3) various light rainy episodes during several days preceding the radar acquisition. Therefore, the SSM maps with a revisit period of six days do not always allow us to discriminate wet soil following a light rain at a date very close to the date of acquisition of the S1 image, and wet soil following a heavy rain that took place several days before the S1 acquisition date. Moreover, we have analyzed the impact of heavy rainfall (cumulative rainfall more than 60 mm in 24 hours or more than 80 mm in 48 hours) on S1-SSM values as a function of the number of days that separated the heavy rainfall event and the S1 acquisition date (\(\Delta t=t_{\text{S1}}-t_{\text{Herry Rainfall}}\)). These threshold values of 60 mm and 80 mm were selected according to Meteo-France recommendations ([[http://pluiesextremes.meteo.fr/france-metropole/Statistiques-et-records.html](http://pluiesextremes.meteo.fr/france-metropole/Statistiques-et-records.html)]([http://pluiesextremes.meteo.fr/france-metropole/Statistiques-et-records.html](http://pluiesextremes.meteo.fr/france-metropole/Statistiques-et-records.html))). Figure 7 shows the SSM values as a function of \(\Delta t\) for cumulative rainfall greater than 60 mm in 24 hours (Figure 7a) and 80 mm in 48 hours (Figure 7b). For example, \(\Delta t=0\) corresponds to a heavy rainfall event that occurred during the past 24 hours (or 48 hours) of the S1 acquisition. In the case of a cumulative rainfall greater than 60 mm in 24 hours (Figure 7a), we find that the SSM average values decreases from 25.4 vol.% for \(\Delta t=0\) to 20.8 vol.% for \(\Delta t=5\) days (S1 image acquired six days after the heavy rainfall event). In the case where the cumulative rainfall is greater than 80 mm in 48 hours (Figure 7b), we find that SSM average values are similar (23 vol.%) after a heavy rainfall that took place during the past 48 hours of the S1 acquisition or after a heavy rainfall during the 48 hours that took place six days before the S1 acquisition. Figure 7: S1-SSM distribution as a function of the number of days that separate the heavy rainfall event and the acquisition date of S1. **(a)** Heavy rainfall with 60 mm of cumulative precipitation in 24 hours, **(b)** heavy rainfall with 80 mm of cumulative precipitation in 48 hours. The effect of the temporal resolution of satellite images on detecting heavy rainfall events was further studied with soil moisture data from SMAP at higher temporal resolution [7]. For this reason, we have re-established Figure 5 with SMAP data at 9 km \(\times\) 9 km spatial resolution (Figure 8).