| Popis: |
Soil Moisture (SM) remains one of the inevitable geophysical land surface variables, influencing climatological and hydrological fluxes that can control the interaction between Earth's surface and atmosphere. It is also a crucial land surface parameter indicating drought conditions in agricultural areas, significantly impacting agricultural production. The temperature vegetation dryness index (TVDI), a simplified surface dryness index based on vegetation index (VI) - land surface temperature (LST) triangle/trapezoidal spectral space, can monitor SM conditions in vegetation-covered areas.The present study estimated a high-resolution temperature vegetation dryness index (TVDI) for assessing SM over the largest river basin in India, Ganga Basin. Triangular feature space between LST and VI is generated to obtain the dry and wet edges to calculate TVDI over the Ganga basin for three years (2017, 2018, and 2019). Two different TVDI were developed using two vegetation indices, normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Estimated TVDI is evaluated using ESA CCI SM product. The relation of subsurface SM with TVDI is investigated using GLDAS Noah LSM SM available at four different layer depths (0–10, 10–40, 40–100, and 100–200 cm).The result shows that TVDI generated using EVI correlates better with SM than NDVI generated TVDI. The relationship between TVDI and SM was found to be closer in Summer (-0.49–0.62) than in post monsoon season. The applicability of TVDI in investigating SM at soil layer depth at 10-40 cm (r close to -0.6) was found to be better than that at depth 0-10 cm, especially during the summer season. The results reveal relevance of generated TVDI with satellite-derived information only, in SM monitoring and assessment, especially in the summer season, over the area of sparse in-situ SM network. |
