Surface Water Availability-Temperature Index (SWATI) for Global Drought Monitoring

Drought assessment is critical for effective water resource allocation and irrigation management, especially in the era of climate change (CC). The satellite-derived Surface Water Availability-Temperature Index (SWATI) has shown its high applicability for estimating agricultural drought conditions. The SWATI is developed by integrating three satellite variables, namely, the Normalized Difference Latent Heat Index (NDLI), the Normalized Difference Vegetation Index (NDVI), and the Land Surface Temperature (LST). This study examined the ability of SWATI to monitor soil moisture (SM) and drought status from national to global scales. To assess the performance of SWATI, five hydrometeorological datasets relevant to drought assessment, such as downscaled Global Land Surface Satellite (GLASS) SM, SM Active Passive (SMAP) SM, Moderate Resolution Imaging Spectroradiometer (MODIS) Evapotranspiration (ET), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) rainfall, and Temperature-Vegetation-Shortwave infrared reflectance Dryness Index (TVSDI), were utilized. The national analysis revealed that the SWATI can effectively indicate the SM, as evidenced by its high correlation coefficients (r) with the high-resolution GLASS SM. At the continental scale, the SWATI showed stronger correlations with SMAP SM ( $- 0.83\le r \le -0.54$ ; $p~\lt 0.01$ ) compared to the TVSDI ( $- 0.80\le r~\le -0.47$ ; $p~\lt 0.01$ ). Moreover, the spatiotemporal correlation evaluation indicated good consistencies between the SWATI and four datasets (SMAP SM, MODIS ET, CHIRPS rainfall, and TVSDI), with over 43% of the global area showing the highest consistency. It is concluded that the SWATI can represent SM and generate high-resolution drought maps. Furthermore, the SWATI was used to assess global agricultural drought conditions from 2001 to 2022. The analysis of drought distributions and trends based on SWATI showed wide variations across different land cover types and climate conditions. Overall, the satellite-based SWATI is an effective drought monitoring method, and its further utilization will be essential for irrigation management in data-scarce regions.