The Stormwater Management Model (SWMM) is a widely used tool for assessing the hydrological performance of infiltration swales. However, validating the accuracy of SWMM simulation against observed data has been challenging, primarily because well-functioning infiltration swales rarely produce surface runoff, especially over short monitoring periods. This study addresses this challenge by using measured subsurface water storage levels for calibration and validation. The study evaluated three SWMM modules, namely, the snowpack, aquifer, and low-impact development (LID) modules, to simulate subsurface water storage levels of an infiltration swale located in a cold climate region during snow and snow-free periods. Global sensitivity analysis was used to identify influential parameters within these modules. The findings revealed that only a few parameters significantly influenced model outputs. Moreover, the aquifer module outperformed the LID module in simulating subsurface water storage due to limitations in setting the initial saturation of the LID module. Furthermore, simulation accuracy was better during snow-free periods due to challenges in simulating snow dynamics during snow periods with the snowpack module. The calibrated models offer valuable insights into the long-term hydrological performance of infiltration swales, enabling practitioners to identify events that trigger flooding in these systems.