Advanced Techniques for Enhanced Drought Monitoring Utilizing the Temperature-Soil Moisture Dryness Index (TMDI)

Droughts, as severe climatic phenomena, pose substantial risks to sensitive areas globally. In Taiwan, where critical sectors such as semiconductor manufacturing are particularly vulnerable, the effects of droughts are of great concern. Various satellite indices have been developed to monitor drought status. The Temperature-Vegetation Dryness Index (TVDI), based on the Land Surface Temperature (LST) and Fractional Vegetation Cover (FVC), has been extensively used. The newly-proposed Temperature-Soil Moisture Dryness Index (TMDI), derived from the LST–Normalized Difference Latent Heat Index (NDLI) trapezoidal space, presents a more effective alternative to the TVDI. This study enhances TMDI by incorporating the novel Fractional Surface Water Availability (FSWA), focusing on better edge definition in the LST–FSWA space for drought monitoring. The capabilities of these indices were evaluated against metrics such as Surface Energy Balance Algorithm for Land (SEBAL)-based evapotranspiration (ET), Crop Water Stress Index (CWSI), Gross Primary Productivity (GPP), and in-situ precipitation. Notably, the TMDI showed stronger correlations with ET (r = –0.94) and CWSI (r = 0.93) compared to other indices. Moreover, the TMDI closely aligns with CWSI and GPP and is most responsive to precipitation (r = –0.60). Leveraging CWSI classifications, a novel TMDI threshold is proposed to assess drought conditions across southwestern Taiwan from 2014 to 2021. Generally, the TMDI effectively captures spatiotemporal drought patterns, providing essential insights for water management, irrigation planning, and the achievement of sustainable development goals.