## 5 Discussion
### Sentinel-1 Revisit Time  
First, these limitations were influenced by the soil texture, field capacity, and rapid drying of the soil, which could impact the effectiveness of irrigation event detection. The rapid drying of the soil necessitated a sensor with a higher temporal resolution to detect quick changes in soil moisture content, such as an increase due to irrigation followed by a decrease due to drying. Previous studies confirmed the importance of a maximum time delay of three days between an irrigation event and the subsequent SAR image to accurately detect the event's impact on the SAR backscattering signal [44; 48]. Beyond this timeframe, it becomes challenging to detect the effect of an irrigation event. The temporal resolution of the S1 SAR should ideally be no more than three days for a more effective irrigation detection [16; 43].  
The 6-day revisit time of the S1 SAR constellation poses a significant challenge in detecting irrigation events due to the rapid dry-out of certain soil surfaces, as previously mentioned. It also creates difficulties in distinguishing the effects of rainfall and irrigation events, especially in the worst-case scenario, where both rain and irrigation occur between the same two consecutive acquisition dates. The increase in SSM values after rainfall and irrigation may be similar, even for different amounts, which makes it even more difficult. In the specific case described in the P2 plot (Figure 8b), there was a missed irrigation detection on 5 August 2018 following a heavy rainfall event (\(\cong\)33 mm) on 2 August 2018, which likely caused a significant increase in soil moisture, resulting in high SSM values. This missed detection could be attributed to the method's inability to effectively distinguish between the impact of the heavy rainfall and the irrigation. As a result, the occurrence of the irrigation event went undetected, leading to a false negative detection. It is worth noting that this particular case was observed only once in the analysis due to the applied filters and methods used to distinguish between rainfall and irrigation events. These filters involved analyzing Optirrig SSM simulations and SSM at both plot and grid scales, asdescribed in Section 3. Unfortunately, due to an anomaly affecting S1B, the revisit time for S1 SAR data has increased from 6 days to 12 days, as only S1A remains operational. This reduced revisit frequency presents a challenge for SSM estimation frequency and accurate irrigation detection and monitoring. To address this challenge, an effective strategy involves integrating SSM estimations from other SAR data sources. Collaborating with SAR satellites like ALOS PALSAR, RADARSAT, and COSMO-SkyMed can provide supplementary SSM data, effectively augmenting the frequency of observations. Additionally, leveraging the benefits of small- or micro-SAR satellites, which can be launched in constellations, offers a promising solution. These satellites provide increased revisit frequencies and higher spatial resolutions, which are essential for capturing frequent and detailed observations of irrigation patterns and soil moisture dynamics. By combining the data from different SAR sources, both large and small, a more comprehensive dataset covering a broader range of time intervals and spatial scales can be created. This integrated approach can significantly enhance the potential for the precise analysis of irrigation patterns and soil moisture dynamics, despite the limitations imposed by the reduced revisit time. Moreover, there is promising news on the horizon--the launch of a new constellation of SAR satellites, namely, Sentinel-1C, is planned for the end of 2023. Once operational, Sentinel-1C is expected to mitigate the revisit time challenge by providing more frequent observations, bolstering the accuracy of irrigation detection and soil moisture estimation efforts.