Estimation of soil moisture through water cloud model using sentinel -1A SAR data

Abstract

Soil moisture(SM) is a key parameter to study the land – atmosphere interfaces in term of agriculture, meteorology and hydrology to understand the cycle of evaporation and drought mechanism. In this study, a semi-empirical model i.e. water cloud model (WCM) was used to estimate the SM in the area of Varanasi district, India using C- band Sentinel -1A SAR data. In this regards three type of vegetation descriptors (LWAI, LAI and fveg) were chosen in WCM to check the potential of inversion scheme. WCM parameterization was done using non-linear least square optimization algorithm. The statistical analysis in the case of V1 = V2 = fveg indicated high correlation between the estimated SM with the in-situ observation (R2 = 0.847, RMSE = 3.23). Therefore, the vegetation descriptor i.e. fveg computed from Landsat-8 satellite data was found better in WCM for the estimation of SM more accurately. © 2019 IEEE