Time Variance in Snowmelt Partitioning: A Mechanistic Modeling Approach to Explore the Role of Catchment Structure and Pre‐Snow Rainfall

Abstract Understanding how snowmelt is partitioned into different hydrologic flowpaths/storages—and how this partitioning varies over time—is essential for predicting water availability and quality under climate variability. In this study, we examine the time‐variance of snowmelt partitioning patterns (SPP) in response to interannual variations in antecedent (Fall) rainfall before snowmelt seasons, across two snow‐dominated catchments in Canada and Sweden with contrasting geologic and topographic features. Using integrated subsurface–surface flow and transport modeling, combined with observational data, we simulate the partitioning of snowmelt into shallow flowpath, deep flowpath, evapotranspiration, and long‐term storage. To generalize our findings beyond the two case studies, we design a suite of virtual experiments that systematically vary catchment slope and the extent of the hydraulic conductivity's vertical and lateral heterogeneity. Results show that lateral heterogeneity in conductivity mediates the sensitivity of snowmelt partitioning to interannual variations in antecedent rainfall. While laterally homogeneous catchments display minimal sensitivity of snowmelt partitioning pattern to wet or dry Fall rainfall conditions, catchments with heterogeneous lateral structure store a significantly larger portion of snowmelt and reduce snow‐sourced shallow flow contributions in years with high pre‐snow rainfall than years with low pre‐snow rainfall. In contrast, while slope and vertical conductivity architecture govern SPP, they play a limited role in mediating SPP's temporal sensitivity to antecedent rainfall variability. These findings reveal that subsurface structure—including the extent of lateral subsurface heterogeneity—modulates the influence of climate variability on snowmelt partitioning and catchment hydrologic function. This has implications for predicting streamflow responses, groundwater recharge, and solute transport under changing climate regimes, and highlights the importance of representing time‐variable hydrologic behavior in hydrologic models.