Hydrological response to the drought estimation using Thermal Remote Sensing: A case study of the Little River Experimental Watershed in Georgia region, U.S

Drought is a serious hydroclimatic hazard. It is typically recognized as a precipitation deficit resulting from rain timing and spatial distribution. Droughts may be using quantitative drought indices based on rainfall, streamflow, or water supply data. In contrast to conventional precipitation-based drought indices, remotely-sensed drought indices have a substantial advantage in that they do not require high-quality precipitation observations. For example, the Evaporative Stress Index (ESI) generated with the Atmosphere-Land Exchange Inverse (ALEXI) remote sensing model does not require in situ. However, it can reasonably provide spatially-distributed drought products on a routine basis. The ESI’s remote-sensing basis is able to provide robust drought products in regions with minimal ground-based meteorological infrastructure. Here we evaluate ESI’s performance as compared to other standard precipitation-based drought indices and drought classification recorded in retrospective United States Drought Monitor reports. Furthermore, we investigate the operational efficacy of the ESI compared to other drought indices, Palmer Drought Severity Index and Vegetation Health Index, to characterize soil moisture and streamflow data in Little River Experimental Watershed at Georgia region, U.S.