| dc.description.abstract | Drought, a detrimental natural disaster, has extensive impacts on ecosystems, the environment, and human life globally. Its recent emergence in Taiwan has sparked significant concerns, especially for vital industries like semiconductor chip production. This dissertation uses satellite-based indices to monitor drought status, given the crucial role of accurate drought assessment in effective water management. The Temperature-Vegetation Dryness Index (TVDI), which combines Land Surface Temperature (LST) and Fractional Vegetation Cover (FVC) using empirical techniques, is widely utilized. However, its applicability is limited in regions with sparse vegetation, prompting the exploration of alternative methods. The recently introduced Temperature-Soil Moisture Dryness Index (TMDI), which substitutes the vegetation index with the Normalized Difference Latent Heat Index (NDLI), shows potential as a suitable alternative. The first key section of the dissertation presents advancements in the TMDI using the new Fractional Surface Water Availability (FSWA) derived from the NDLI. This section delves into refining edge selection within the LST–FSWA space to observe drought. A practical method has been adopted to accurately identify the dry and wet edges within this space. To evaluate the reliability of TMDI, the study conducted comprehensive assessments using various indicators, including the evapotranspiration (ET), Crop Water Stress Index (CWSI) derived from the Surface Energy Balance Algorithm for Land (SEBAL), Gross Primary Productivity (GPP), and precipitation data. The results reveal high correlations between the TMDI and SEBAL-derived CWSI, ET, and GPP, surpassing those obtained with TVDI. Moreover, strong associations between the TMDI and precipitation underscore its effectiveness in capturing drought patterns. This section also proposes a standard TMDI threshold for assessing drought in southwestern Taiwan from 2014 to 2021. The subsequent section of this dissertation applies the novel FSWA to monitor agricultural water stress and drought status at the national scale. The FSWA is employed alongside two other indices to analyze annual drought patterns in Australia from 2001 to 2022. The analyses reveal high correlations between the FSWA against soil moisture (SM), ET, and rainfall. Across most agricultural regions in Australia, the FSWA shows robust temporal correlations with the SM, ET, and rainfall. Furthermore, given the SWAT’s simplified calculations and wide applicability, its practical utilization has been evaluated at the global scale. It is found that the SWAT can represent SM and generate high-resolution drought maps. The SWAT was applied to assess global drought conditions from 2011 to 2022. The analysis of drought distributions and trends based on the SWAT index exhibited wide variations across different land cover types. In conclusion, both the TMDI and SWAT function as practically operational drought indices. The advanced TMDI, relying on the integration of only two variables: FSWA and LST, excels in regional-scale drought monitoring, particularly in agricultural zones. On the other hand, the satellite-based SWAT index, due to its broader scale applicability and more straightforward methodology, offers a viable alternative to empirical models. | en_US |