Indices-based assessment of vulnerability to agricultural drought in the tropical semi-arid ecosystem using time-series satellite and meteorological datasets

The core aims of the present study are first to compute the Scaled Drought Condition Index (SDCI) by integrating Precipitation Condition Index (PCI), Temperature Condition Index (TCI), and Vegetation Condition Index (VCI) for the northeast (NE) monsoon period during the year 2000 to 2019 in the tropical semi-arid ecosystem of Tamil Nadu (TN) state of southern India. Secondly, to assess the dynamics of vulnerability to agricultural drought by using SDCI and identify the critical vulnerability zones in TN state. The PCI, TCI, and VCI were computed from time-series Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) products, Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance of MOD11A2, and vegetation indices of MOD13Q1, respectively. The results explain that about 0.1, 13.0, and 39.5% of TN state especially in the northern, NE, western, and southern zones are vulnerable to extreme, severe, and moderate vulnerability to agricultural drought, respectively. In the drought year (2016), about 79.9% area of TN state experienced extreme vulnerability to agricultural drought. The validation of SDCI with the 3-month Standardized Precipitation Index (3-SPI) and Vegetation Health Index (VHI) for the dry year (2016) and wet year (2010) shows a moderate to a strong a positive correlation. It evidently shows the influence of rainfall on overall vegetation and agricultural drought. The study amply reveals that PCI, TCI, and VCI are the most important indices associated with agricultural drought and are clearly explained by the robust SDCI computed from temporal CHIRPS and MODIS datasets in the effective assessment of vulnerability to agricultural drought in the TN state.