In order to predict streamflow and understand the associated snow dynamics in a data scarce situation for the snow-dominated, wooded, hilly Alaknanda River basin in India's Western Himalayan area, the Soil and Water Assessment Tool (SWAT) model was set up. Measured discharge from 2010 to 2012 and 2013 to 2015 were used as calibration and validation data in the current study, respectively. As a warm-up period, data from the first two years (2008–2009) were used. To incorporate SWAT in the study, ArcSWAT interface was used, and parameter optimization was performed using SWAT-CUP/SUFI2 algorithm (Sequential Uncertainty Fitting version 2). The sensitivity analysis revealed that the streamflow of the region is influenced by 20 parameters, indicating their significant role in shaping the hydrological patterns. The temperature lapse rate (TLAPS) was observed to be the most significant parameter. The values of Nash Sutcliffe Efficiency (NSE), the coefficient of determination (R2) and the Percent Bias (PBIAS) for the calibration period were 0.91, 0.92, and + 5.1%, respectively. The validation (2013–2015) of the streamflow data resulted in the values of the NSE, R2, and PBIAS as 0.84, 0.86, and − 2.9%, respectively. In the Alaknanda River Basin, 58.3% of the total precipitation of the whole year was converted into streamflow/total runoff. About 10.61% of the streamflow/total runoff was contributed by the snowmelt of the region, thereby significantly affecting the discharge of the region.