Understanding hydrological processes is crucial for effective watershed management, with SWAT+ being one of the widely adopted models for analyzing water balance at watershed scales. While hydrological components are often assessed through sensitivity analysis, calibration, and validation, parameter sensitivity during dry periods (low-flow conditions) when baseflow is predominant remains a relevant focus, especially for watersheds like Majalaya, Indonesia, which experience distinct low-flow periods. This study analyzes water balance components in the Majalaya watershed, Indonesia, using SWAT+ across the 2014–2022 period, focusing on low-flow conditions. This study employs a two-step calibration approach using various datasets, including ground rainfall (2014–2022), NASA POWER meteorological data, MODIS land cover, DEMNAS terrain, and DSMW soil types, and the streamflow data for model calibration. The first calibration step optimized the overall performance (R2 = 0.41, NSE = 0.41, and PBIAS = −7.33), and the second step improved the baseflow simulation (R2 = 0.40, NSE = 0.35, and PBIAS = 12.45). A Sobol sensitivity analysis identified six primary parameters, i.e., CN3_SWF, CN2, LATQ_CO, PERCO, SURLAG, and CANMX, as the most influential for streamflow calibration, with CN3_SWF and CN2 being the most critical. This study demonstrates SWAT+’s effectiveness in watershed management and water resource optimization, particularly during low-flow conditions.