LAUSR

Soil Moisture (SM) data play an important role in different fields of research like hydrology, agriculture, climatology, etc. In this article, global positioning system interferometric reflectometry technique was used to estimate SM. Estimated SM data have been validated and compared with collocated in situ probe, Soil Moisture and Ocean Salinity (SMOS) satellite measurements, ECMWF ERA-5, and NASA Global Land Data Assimilation System (GLDAS); the former shows a good correlation of 0.98 but the magnitudes of SMOS, ERA-5 are overestimated and GLDAS data are underestimated. Variability of SM with rainfall and energy fluxes like latent and sensible heat fluxes from ERA-5 and GLDAS data are investigated. Observed SM values are positively correlated with rainfall during the study period. Seasonal variations of SM with rainfall in different monsoons are clearly noticed. Latent heat fluxes are more during spring, summer months and positively correlated with rainfall, whereas sensitive heat fluxes show negative correlation.