Drought is a natural disaster that significantly impacts the agricultural sector, water availability, and public welfare. This study aims to identify drought in rice fields in West Sumatra using the Standardised Precipitation Index (SPI) and Normalised Difference Drought Index (NDDI) methods. The SPI is used to determine drought based on rainfall deviations from normal conditions over a given period. The NDDI is used to measure drought conditions based on soil moisture and vegetation conditions. The novelty of this study lies in the spatial-temporal integration of SPI and NDDI for West Sumatra, an approach rarely applied in Indonesia, as well as in linking rainfall variability with paddy vegetation responses for early detection of agricultural drought. The SPI analysis identified 370 drought events, affecting a total of 2,377.40 ha, or 1.01% of the total rice fields, in July 2023, while the NDDI analysis revealed a much wider drought coverage, reaching 198,772.11 ha (84.76%) categorised as severe to extremely dry. The difference in results between the two indices indicates that statistically adequate rainfall does not necessarily reflect sufficient groundwater availability to support vegetation growth. These findings emphasise the importance of integrating meteorological indicators with land and crop conditions for more accurate agricultural drought monitoring. These findings support adaptive planting patterns and efficient irrigation management, enhancing agricultural resilience to drought and contributing to SDG 2 (Zero Hunger) and SDG 6 (Clean Water and Sanitation).