Drought is a major climatic hazard in the Mediterranean region, particularly in the Tensift river basin in Morocco. It has severe implications for water availability, agriculture, and local economies. However, traditional monitoring systems often fail to provide timely drought warnings. This study explores the integration of satellite and reanalysis data to enhance early warning systems, aiming to improve drought detection and monitoring across the Mediterranean. The effectiveness of the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) based on satellite data from the Climate Hazards Group Infrared Precipitation (CHIRPS) and reanalysis data (ERA5-Land) was assessed using Receiver Operating Characteristic (ROC) curve analysis, comparing them to ground observations from 1981 to 2021. This study focused on optimizing thresholds and timescales for these indices to improve drought detection. The integration of CHIRPS and ERA5-Land significantly enhanced the detection of drought events compared to conventional methods. The ROC analysis identified optimal threshold levels for SPI and SPEI, which improved their detection performance. The Pearson Type III distribution was found to be the most suitable for SPI calculations, while the Log-logistic distribution was best for calculating SPEI. Integrating satellite and reanalysis data significantly advances drought characterization in the Tensift basin, facilitating more proactive drought management. This method proves crucial for mitigating impacts and supporting decision-makers in sustainable water resource management. Future research should aim to integrate these indices with socio-economic impacts to develop a comprehensive drought risk management strategy.