## 5 Results and Discussion
### Effect of Individual Processing Steps on Soil Moisture Estimation  
To evaluate the influence of the individual processing steps, the resulting soil moisture values are compared with the in-situ measured values from the eight CRNP stations within the Rur catchment as well as six capacitance station at 0.025 m and 0.1 m soil depth within the Apulian Tavoliere site. To relate the estimated soil moisture to the CRNP data and capacitance measurements, the mean estimated soil moisture around each location within a diameter of 200 m was calculated and was chosen to match the detection radius of the CRNP stations. We focus on the main processing steps that were used to create the temporally and spatially high-resolution time series from multi-orbit Sentinel-1 scenes. In this regard, the estimated soil moisture from incidence angle normalisation (IA), incidence angle normalisation and Fourier Series (IA + FS) and incidence angle normalisation, Fourier Series and vegetational adapted (IA + FS + VA) time series are compared (Tables 4 and 5). Since the agricultural crops at the respective CRNP sites change annually in some cases, the methods are evaluated for the individual years 2018, 2019 and 2020, using the coefficient of determination (R\({}^{2}\)) as well as the unbiased Root Mean Square Error (uRMSE). It needs to be mentioned that by comparing soil moisture estimations from C-band SAR observations to in-situ measurements from CRNP station, different soil depths are considered. While C-band only represents the first upper centimeters of soil, CRNP represents a soil depth between 15 cm to up to 70 cm, depending on the soil moisture condition. In general, a strong correlation between surface and root zone soil moisture was observed, when comparing SMOS near-surface soil moisture measurements to root-zone in-situ data [90]. Nonetheless, under extreme dry conditions, remotely sensed soil moisture shows a reduced variability, due to the limited storage capacity of the upper soil layer compared to the root zone soil moisture [91]. On the other hand, when comparing point data from capacitance sensors from 0.025 m and 0.1 soil depths, the spatial soil heterogeneity can result in soil moisture values, which are not representative for the area covered by the radar signal. Especially when losing contact to the surrounding soil, capacitance probes can lead to unreasonable values. In this regard, CRNP measurements are more suitable, providing an integrated soil moisture value over its footprint area. However, in this study, no significant difference between CRNP and capacitance measurements were found, regarding the performance of the introduced soil moisture estimation, whether due to different soil depth nor different spatial footprints of both in-situ instruments. Figure 9: Comparison between vegetation corrected and non-corrected estimated soil moisture to in-situ measured soil moisture at the CRNP station RU_C_006. Using only the incidence angle normalisation, both low to high correlations between in-situ measured and estimated soil moisture are achieved for the Rur catchment as well as Apulian Tavoliere site. In general, the Rur catchment had mean R\({}^{2}\) values of 0.36-0.47 and mean uRMSE of 0.054-0.058 m\({}^{3}\)/m\({}^{3}\) for the individual years (Table 4). Almost no correlation is observed at the CRNP station SE_C_001 in 2019 and 2020 with R\({}^{2}\) of 0.06 and 0.07, while the highest correlations are observed in 2020 at the CRNP