## 1 Introduction
In most studies, the contribution from vegetation has been expressed in terms of one of the physical parameters attached to it (biomass, leaf area index, vegetation water content, vegetation height). The contribution of the soil is generally modeled as a function of soil moisture and surface roughness (defined by the root mean square surface height and the correlation length). The possibility of retrieving soil parameters in vegetated surfaces was widely investigated using C-band Synthetic Aperture Radar [59, 60, 61, 62, 63, 64, 65, 66]. Many studies showed that it is possible with SAR imagery to estimate the soil moisture with accuracy from 0.02 to 0.10 cm\({}^{3}\)/cm\({}^{3}\) (RMSE). [PERSON] _et al._[59] showed the potential of data in the C and X bands to estimate both soil moisture and the LAI on winter wheat plots using the water cloud model. Accuracies of 0.065 cm\({}^{3}\)/cm\({}^{3}\) and 0.64 m\({}^{2}\)/m\({}^{2}\) for soil moisture and the LAI, respectively, were obtained. [PERSON] _et al._[60] coupled a canopy scattering model (the Michigan Microwave Canopy Scattering model) with a soil scattering model (the Oh model) to estimate soil moisture and vegetation water content for a soybean canopy (VWC between 0.02 and 0.97 kg/m\({}^{2}\)) from fully polarimetric data at both L and C bands. The root mean square error of the soil moisture estimate was approximately 0.02 cm\({}^{3}\)/cm\({}^{3}\). [PERSON] _et al._[65] estimated soil moisture using ASAR images (C-band) of wheat plots (LAI between 0.01 and 3.7 m\({}^{2}\)/m\({}^{2}\) and VWC between 0.15 and 0.93 kg/m\({}^{2}\)) using the water cloud model with an accuracy of approximately 0.06 cm\({}^{3}\)/cm\({}^{3}\). [PERSON] _et al._[62] combined the Oh model and the water cloud model to estimate the soil moisture over an agriculture vegetation area (wheat, peas, lentil, fallow, pasture and canola) using Radarsat-2 images in polarimetric mode (C-band). The soil moisture was estimated with an accuracy of 0.06 cm\({}^{3}\)/cm\({}^{3}\) for plots with a canopy height between 11 and 97 cm and a water content range between 0.54 kg/m\({}^{2}\) and 5.10 kg/m\({}^{2}\). [PERSON] _et al._[67] estimated the soil moisture over soybean plots using SAR X-band data with an accuracy of 0.03 cm\({}^{3}\)/cm\({}^{3}\) (VWC and LAI reach 1.8 kg/m\({}^{2}\) and 4.5 m\({}^{2}\)/m\({}^{2}\), respectively). [PERSON] _et al._[68] estimated from ASAR images the soil moisture of irrigated wheat plots with an accuracy of approximately 0.09 cm\({}^{3}\)/cm\({}^{3}\) (VWC between 0.45 and 3.41 kg/m\({}^{2}\)). To monitor water stress in irrigated systems and support irrigation scheduling decisions, the limited accuracy of individual soil moisture estimates may be compensated for by the amount of available SAR images. For example, [PERSON] [69] demonstrated the benefit of soil moisture monitoring by improving irrigation schedules in gravity-irrigated plots of hay. While the benefit of having highly resolved information is obvious in water balance monitoring, the relevance of SAR products for this purpose needs to be better characterized. **The main objective** of this paper is to analyze whether the X-band SAR data currently accessible by the four CSK and two TSX satellites is sensitive enough to provide useful information for the monitoring of irrigated grasslands in southeastern France. This study will focus on the following questions: (i) Is the X-band radar signal sensitive to soil moisture in dense grassland? (ii) Can the X-band detect the beginning of irrigation and monitor the duration of irrigation for each plot, even when the vegetation is well developed? (iii) Is it possible to derive useful parameters related to vegetation characteristics (vegetation height, biomass, vegetation water content, and leaf area index) from the X-band radar signal for this type of irrigated grassland?