## 5 Discussion  
This paper evaluates the performance of X- and C-band SAR data on soil moisture retrieval using a semi-empirical scattering model. Compared with [PERSON]'s model, the semi-empirical model establishes the soil moisture estimated mechanisms and depicts the soil moisture status and vegetation precisely. As shown in Figure 6, the semi-empirical model shows a more favorable correlation with measured soil moisture than [PERSON]'s model. However, there are several factors affecting the inversion results, for example, speckle noises of remote sensing data, restrictions of field observations, and uncertainties of scattering methods. In Figure 6, the results showed a similar estimation accuracy using the proposed model at both X- and C-bands. The R and RMSE are not very satisfying. Several reasons need to be clarified and discussed here. First, for the models used in this paper, the vegetation canopy might be the most important input parameter in vegetation-covered soil moisture retrieval. Thus, the uncertainties of the models mainly depend on this variable. For the influence of vegetation canopy from the radar signal, biophysical parameters (e.g., NDVI, NDWI, LAI or crown water content) are used to calculate the vegetation effects on radar signature [68; 69; 70; 71; 72; 73]. Then, the SAR configurations would be responsible for these unsatisfying results. As we know, the L-band microwave sensor was considered as the optimal choice in the potential applications for the incorporation of soil moisture estimates [74]. However, the operational L-band satellite radiometers have the limitation of moderately coarse spatial resolution. Though C-band SAR data have very high spatial resolution, they are more sensitive to vegetation canopy than L-band data in vegetated regions. The X-band SAR can describe the accurate characteristics of the soil surface more accurately than the C- and L-bands when observing at the same incidence angle. Thus, the X-band sensor is susceptible to vegetation cover and is typically sensitive to low-biomass land cover. The effectiveness and availability of L-, C- and X-bands SAR data in soil moisture retrieval should be evaluated  
Figure 9: Pyramid plot of estimated soil moisture at X- and C-bands over the three field sites. in the future work. Furthermore, addressing the generalization of the empirical model is an important issue for soil moisture products. In the study, ground measurements and three representative field sites were used to evaluate the effectiveness and feasibility of the model. They reveal that our model can be suitable for any vegetation-covered regions. Meanwhile, constructing simple and effective scattering models will play an important role in soil moisture monitoring and product development. Therefore, further study on the empirical model is both necessary and significant. In addition, surface roughness is also regarded as one of the most important variables in soil moisture retrieval. Surface roughness parameters, especially correlation length, fail to depict the actual shape of soil surface and are not constant according to the applicable conditions [75; 76]. Thus, several combined roughness parameters were proposed to improve the estimated accuracy of surface roughness and reduce the uncertainties of structural coefficients [56; 63; 77]. More work is needed to obtain the optimal vegetation and soil parameters in vegetation-covered soil moisture estimates. As shown in Figure 7, the soil moisture maps at X- and C-bands are slightly different. Soil moisture varying from 0.05 to 0.30 cm\({}^{3}\)/cm\({}^{3}\) indicates a slightly dry soil condition due to reduced rainfall in September. Actually, for Site c#, the X- and C-bands SAR overestimated the soil moisture in the middle of the southern parts, which can be explained because no measurements were conducted in this area to calibrate the proposed model. A small natural land with shrubs and riparian trees lies in the middle of southern region. A stream runs towards the northeast and remains dry for the whole year.