# Soil Moisture Monitoring at Kilometer Scale: Assimilation of Sentinel-1 Products in ISBA
## 6 Conclusions  
This study investigated the benefits of assimilating satellite-derived soil moisture (SSM) products from the Sentinel-1 (S1) satellite in the ISBA land surface model at a spatial resolution of 1 km, from 2017 to 2019, using the LDAS-Monde tool, for two regions in Southern France and one in Spain. The validation of the S1 SSM was carried out by comparing it with in situ measurements of soil moisture at a depth of 5 cm from the SMOSMANIA network and Meteopole-Flux in France and the REMEDHUS network in Spain. The results showed a good agreement between the two datasets for most of the stations at 18:00 UTC, with some difficulties during summer due to irrigation processes in Spain, as the REMEDHUS stations are located in semi-arid croplands. The SSM simulations were generally more precise than the S1 SSM observations, and the ISBA simulations could be used together with in situ observations to validate the S1 SSM. Three different experiments were carried out to study the influence of the assimilation of S1 SSM and PROBA-V LAI, alone and together, on the simulated soil moisture at the 0.01-0.04 m (WG2) and 0.20-0.40 m (WG5) soil layers. It was shown that the S1 SSM assimilation alone had little effect on the soil moisture at both depths, across all seasons. In contrast, there was a more pronounced effect on soil moisture in the root zone (WG5) for the other two experiments. Over agricultural areas, the effect of the three experiments on WG5 differed, and the assimilation of S1 SSM had a greater impact on the analysis results. Similar results were observed for the three regions considered in this study. Since the impact of S1 SSM was particularly visible over agricultural areas, this shows that S1 SSM observations can help to detect and monitor drought impacts on agriculture. The observed synergies between S1 SSM and satellite-derived LAI suggest that high-resolution SSM products have added value in a data assimilation context. This was particularly true over irrigated areas, as irrigation was not represented in the ISBA simulations. This finding contrasts with previous results based on low-resolution SSM products. Future work will focus on the assimilation of S1 backscatter, as it provides information from both SSM and LAI [12]. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs15174329/s1](https://www.mdpi.com/article/10.3390/rs15174329/s1)]([https://www.mdpi.com/article/10.3390/rs15174329/s1](https://www.mdpi.com/article/10.3390/rs15174329/s1)), Figure S1 for the comparison of S1 SSM with in situ observations; Figure S2, Figure S3, and Figure S4 for the modeling results over the Toulouse region; Figure S5, Figure S6, and Figure S7 for the modeling results over the Salamanca region. Tables S1 and S2 are for the comparison of S1 SSM and OL WG2 with in situ observations. Reference [51] is cited in the supplementary materials. Conceptualization, O.R.-M., J.-C.C., B.B., N.B., C.M., A.N., J.-P.W. and M.Z. ; methodology, O.R.-M., B.B. and J.-C.C. ; investigation, O.R.-M., B.B. and J.-C.C. ; formal analysis, O.R.-M.; supervision, J.-C.C. ; writing--original draft preparation, O.R.-M.; writing--review and editing, J.-C.C. All authors have read and agreed to the published version of the manuscript. This research was funded by the TAPAS project of the TOSCA Programme from CNES, France (Centre National d'Etudes Spatiales). The S1 SSM product is available from the THEIA data portal ([[https://thismc.cines.teledetection.fr/map?c=1.761582,43.7451297,8.04](https://thismc.cines.teledetection.fr/map?c=1.761582,43.7451297,8.04)]([https://thismc.cines.teledetection.fr/map?c=1.761582,43.7451297,8.04](https://thismc.cines.teledetection.fr/map?c=1.761582,43.7451297,8.04)), accessed on 30 August 2023).