This study investigated drought monitoring using the Standardized Precipitation Index (SPI) and evaluated drought characteristics, including severity, magnitude, and duration, under climate change conditions at the Qazvin synoptic station. The analysis covered the historical period (1986–2014) and three future periods (2026–2050, 2051–2075, and 2076–2100) under the SSP2-4.5 and SSP5-8.5 scenarios. SPI was calculated at 3-, 6-, 9-, and 12-month time scales. Three climate models, including BCC-CSM2-MR, MRI-ESM2-0, and MPI-ESM1-2HR, were combined using an artificial neural network approach, and drought characteristics were calculated based on the ensemble model outputs. Under the SSP2-4.5 scenario, drought characteristics showed a limited increase compared with the historical period. During 2026–2050, short-term droughts at the 3-month time scale (SPI_3) had a mean severity of 1.10, a mean magnitude of 0.62, and 21 drought events, indicating an increase in drought magnitude compared with the historical period. Under the SSP5-8.5 scenario during 2076–2100, long-term droughts at the 12-month time scale (SPI_12) reached an average duration of 6 months, a mean magnitude of 0.48, and a mean severity of 5.05, indicating more persistent and severe long-term drought conditions. Overall, the results suggest that climate change may increase the occurrence of short-term droughts (SPI_3) and intensify the severity and duration of long-term droughts (SPI_12). These findings highlight the importance of adaptation planning and sustainable management of water and agricultural resources, as prolonged droughts may have cumulative impacts on natural resources, agricultural production, and the local economy.