Abstract. Despite debate in the rainfall–runoff hydrology literature about the merits of physics-based and spatially distributed models, substantial work in cold-region hydrology has shown improved predictive capacity by including physics-based process representations, relatively high-resolution semi-distributed and fully distributed discretizations, and the use of physically identifiable parameters that require limited calibration. While there is increasing motivation for modelling at hyper-resolution (< 1 km) and snowdrift-resolving scales (≈ 1 to 100 m), the capabilities of existing cold-region hydrological models are computationally limited at these scales. Here, a new distributed model, the Canadian Hydrological Model (CHM), is presented. Although designed to be applied generally, it has a focus for application where cold-region processes play a role in hydrology. Key features include the ability to do the following: capture spatial heterogeneity in the surface discretization in an efficient manner via variable-resolution unstructured meshes; include multiple process representations; change, remove, and decouple hydrological process algorithms; work at both a point and spatially distributed scale; scale to multiple spatial extents and scales; and utilize a variety of forcing fields (boundary and initial conditions). This paper focuses on the overall model philosophy and design, and it provides a number of cold-region-specific features and examples.