Topography and vegetation are critical factors influencing catchment hydrology; however, their individual contributions are often underestimated in hydrological models. This limitation is particularly evident in cold, mountainous regions such as the Mongolian Plateau, where observational data are sparse. To address this, we employed a stepwise, top-down modelling strategy based on the FLEX framework to systematically assess the influence of topography and vegetation on hydrological processes in the Bogd Uliastai and Zavkhan Guulin river basins. Beginning with a lumped model (FLEX<sup>L</sup>), we successively integrated snow processes (FLEX<sup>L</sup>-S), topographic distribution (FLEX<sup>D</sup>), and finally, a landscape-based parameterization accounting for vegetation heterogeneity (FLEX<sup>T</sup>). Both FLEX<sup>D</sup> and FLEX<sup>T</sup> outperformed the lumped models in simulating runoff and SWE. Interestingly, FLEX<sup>T</sup> showed similar performance to FLEX<sup>D</sup>—likely due to limited vegetation heterogeneity—it offers more physically realistic parameterization by explicitly representing landscape units, suggesting its potential in more complex basins. Snowmelt contributions to streamflow were quantified as 23.5 %±1.3 % and 14.7 %±1.6 % in the Bogd Uliastai and Zavkhan Guulin river basins, respectively, with peaks in spring and a clear increase with elevation. At high elevations, delayed snowmelt resulted in sustained runoff, while lower elevations responded more rapidly to rainfall. The explicit representation of vegetation heterogeneity further improved the model’s capacity to capture landscape complexity and dominant hydrological mechanisms. This study underscores the pivotal roles of topography and vegetation in runoff generation and demonstrates the effectiveness of a stepwise modelling framework for improving hydrological understanding in cryospheric and data-scarce regions.