Background: Climate change has increased the intensity and frequency of droughts globally and affected freshwater availability, particularly in developing regions with limited adaptive capacity. In Sumatra, prolonged droughts and reduced rainfall have increased vulnerability to drought, necessitating accurate projections to support climate resilience and sustainable water management. This study aims to assess drought projections in Sumatra from 2015 to 2100 in the Shared Socioeconomic Pathways 5-8.5 (SSP 5-8.5), which represents a high emission trajectory. Methods: CMIP6 monthly precipitation from the CMIP6 EC-Earth3 model was bias-corrected using Monthly Mean Bias Correction. The corrected precipitation was used to calculate Standardized Precipitation Index (SPI) to evaluate future drought conditions based on rainfall distribution. Findings: The SPI calculation results show that the frequency of severe droughts (SPI < -1.5) experiences significant interannual fluctuations, in line with rainfall patterns that exhibit oscillatory patterns every few years. The southern part of Sumatra emerged as the most drought-prone region with more than 140 drought events detected. The highest drought vulnerability occurs between March and May in the northern region, which has an equatorial rainfall pattern, while the peak drought vulnerability occurs between September and November in the southern region. Atmospheric circulations such as the ITCZ, ENSO, and IOD, as well as topographic and geographic factors, play a crucial role in regulating drought in Sumatra. Conclusion: Future droughts in Sumatra will be more frequent, occurring in short but severe periods compared to weak, long-lasting droughts. The influence of atmospheric circulation will change with climate change and future anthropogenic pressures, increasing the unpredictability of droughts. Novelty/Originality of this article: This study integrates climate projections with robust and efficient drought index calculations to assess future droughts. Supported by comprehensive spatio-temporal analysis, the findings of this study can provide key-insights for climate resilience and sustainable meteorological-based water management efforts. However, uncertainties remain related to single-model dependency, emission scenario assumptions, and SPI’s precipitation-only formulation.
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