<![CDATA[Purpose: This study aimed to assess the spatial and temporal characteristics of meteorological drought using the Standardized Precipitation Index (SPI) and evaluate its implications for sustainable water resources management in Way Kanan Regency, Indonesia. The study also examined the association between major drought events and El Niño–Southern Oscillation (ENSO) phases and assessed changes in irrigation water requirements under drought conditions. Method: Monthly precipitation data derived from the PERSIANN-CCS satellite for the period 2003–2025 were used to calculate SPI at 1-, 3-, 6-, and 12-month time scales. Drought intensity, frequency, duration, and spatial distribution were analysed across four major rice-producing districts. Historical drought events were subsequently compared with ENSO phases using the Oceanic Niño Index (ONI), while irrigation water requirements were estimated using the CROPWAT 8.0 model under normal and drought conditions. Findings: The results identified 2003, 2015, and 2019 as the principal meteorological drought years, with SPI-3 providing the most representative assessment of seasonal agricultural drought. Pakuan Ratu exhibited the highest drought vulnerability among the study districts. Severe drought events consistently coincided with El Niño conditions, particularly during the strong 2015 event, and resulted in substantial increases in irrigation water requirements ranging from 57.8% to 65.2% relative to normal conditions. Scenario analysis further projected irrigation water demand increases of approximately 20–65% under future El Niño conditions, depending on event intensity. Research Implications: Integrating multi-temporal SPI assessment with seasonal ENSO monitoring provides a practical framework for strengthening drought early warning systems, optimizing irrigation scheduling, and supporting climate-resilient water resources management in tropical agricultural regions. Originality: This study presents an integrated district-scale framework that combines multi-temporal SPI analysis, climate variability assessment through ENSO comparison, and irrigation water demand modelling to support evidence-based and sustainable water resources management. Unlike previous studies that primarily focused on drought characterization, this research explicitly links drought severity with irrigation water requirements, providing actionable information for adaptive agricultural water management under increasing hydroclimatic variability.]]>
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