Assessing the potential of temperature/vegetation index space to infer soil moisture over Ganga Basin.

• TVDI applied for the first time over Ganga Basin to examine the SM variation. • High TVDI values are observed in central plateau and hill agro-climatic zone. • TVDI developed using EVI shows better correlation with SM compared with the NDVI generated TVDI. • Spatial and temporal valuation of TVDI shows that its applicability can be used mainly in the summer season. • TVDI have high negative correlation with SM for the 10–40-cm soil depth range. Soil Moisture (SM) is a critical parameter for land–atmosphere interaction, measuring drought conditions in agricultural areas, and it can significantly affect surface water and agricultural production. Based on remote sensing observations, the temperature vegetation dryness index (TVDI) can be generated to evaluate SM at a large spatial scale. Land Surface Temperature (LST) and Vegetation Index (VI) plots are generated to obtain the triangular/trapezoidal space to calculate TVDI. For the present study, TVDI was calculated by using LST and normalized difference vegetation index (NDVI) or the enhanced vegetation index (EVI) for a period of three years (2017, 2018, and 2019) over the Ganga Basin. The applicability of the TVDI at soil depths of 0–10, 10–40, 40–100, and 100–200 cm was also examined. The result from the study indicates that, a better correlation is obtained between TVDI generated using EVI and SM compared to TVDI generated using NDVI. Temporal variation of TVDI with SM shows that TVDI (EVI) almost captures the maximum and minimum SM variation in most locations. Also, SM at 10–40 cm shows a better negative correlation (r close to −0.5) with TVDI (EVI) than 0–10 cm depth for the summer season. The result thus reveals the potential of TVDI in assessing SM especially in summer season, while using EVI as the vegetation index. [ABSTRACT FROM AUTHOR]