| dc.description.abstract | Due to a lack of typhoon landfalls in 2020-2012, Taiwan has faced water resource problems, leading to a spring drought in 2021 that impacted both industrial and agricultural sectors, which require extensive water supplies. Advances in remote sensing technology have led to various drought indices to capture surface responses during droughts. The Surface Water Availability and Temperature (SWAT) index combines the Normalized Difference Latent Heat Index (NDLI), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST) to estimate surface dryness using Euclidean distance. This study proposes a modified SWAT by incorporating the coefficient of determination (R²) of NDLI, NDVI, and LST with meteorological drought indices, including the Palmer Drought Severity Index (PDSI) and Standardized Precipitation-Evapotranspiration Index (SPEI). The findings from this adjustment method are used to assess the spatial and temporal characteristics of drought events using the modified SWAT and its correlation with El Niño-Southern Oscillation (ENSO). The Köppen-Geiger climate classification is used to describe zonal characteristics. MODIS is used to retrieve surface dryness conditions based on SWAT, and TerraClimate data is used to retrieve meteorological drought. The study period ranges from January to May, from 2002 to 2021, focusing on spring droughts. The results reveal that SPEI-6 is the most suitable for SWAT weighting, improving correlations with vegetation water stress and meteorological drought, suggesting that Taiwan′s surface conditions are more influenced by longer periods of drought. Taiwan mostly experienced wet or normal surface dryness levels, with occasional mild, moderate, and severe dryness, predominantly in the western and southern regions linked to agricultural practices. Decreasing trends occurred near human settlements, while increasing trends were observed in remote forest areas, suggesting anthropogenic influences in accessible regions. Topographical and geographical features, rather than climate zones, primarily influence correlation directions with ENSO phases, which initially affect precipitation patterns. | en_US |