Modeling and Assessment of Vegetation Water Content on Soil Moisture Retrieval via the Synergistic Use of Sentinel‐1 and Sentinel‐2

Abstract

AbstractAs an indispensable surface parameter, soil moisture is of great significance for analyzing global water cycle, establishing the hydrological model and assessing drought. Due to differences in the capability of establishing vegetation water content (VWC) models based on different vegetation indices, the influence of the different VWC models on retrieval accuracy has not been effectively assessed. Therefore, the suitability of vegetation parameters obtained from different VWC models established by different vegetation indices for accurate soil moisture retrieval requires further investigation. In this study, the different VWC models were established by different vegetation indices derived from Sentinel‐2 data and compared. Based on the Sentinel‐1 Synthetic Aperture Radar and Sentinel‐2 data, combined with microwave scattering models, the impact of different VWC models on the accuracy of soil moisture retrieval was investigated using the Look Up Table algorithm. The results indicate that, an exponential relationship between the measured VWC and different vegetation indices was obtained in the growth cycle of winter wheat, except for quadratic relationship of Modified Soil Adjusted Vegetation Index vegetation index. Compared with other VWC models, higher accuracy of VWC could be retrieved using NDWI1, and the short‐wave infrared band located at 1610 nm achieved higher accuracy than the band located at 2190 nm. With respect to all VWC models, the combination of near‐infrared and short‐wave infrared bands was more suitable for VWC retrieval. When the contribution of soil scattering exceeded that of vegetation scattering, the results of soil moisture retrieval with different VWC models established by vegetation indices exhibit no discernible difference, regardless of the differences that occurred in VWC itself.