Integrating a Blowing Snow Module for Enhanced Representation of Snow Dynamics and Surface in the HydroBlocks modeling framework

To maintain computational efficiency and avoid adding too many uncertainties into Land Surface Models (LSMs) with fine-scale parameterization, many efforts have been made to improve sub-grid representations of heterogeneous landscapes. HydroBlocks LSM stands out as a model that employs advanced hierarchical clustering methods, utilizing field-scale satellite-derived data to construct sub-grid tiles or clusters. The Noah-MP land surface model is applied within each tile. Unlike conventional tiling approaches, knowing the spatial location of the clusters provides the opportunity to incorporate the interactions across the distinct clusters. Presently, they interact through the subsurface flow processes. Despite the comprehensiveness of these models, both Noah-MP and HydroBlocks lack consideration for the wind-induced snow transport which plays a pivotal role in snow-related hazards. Other than that, the sublimation and redistribution of wind-blown snow in exposed environments contributes significantly to variations in snow depth. It not only exerts local influence on surface water and energy balance, but also can have expansive impact since the snowmelt is critical for the water availability of downstream basins. To address this limitation, we propose the integration of a blowing snow module into HydroBlocks. This module, inspired by the Prairie Blowing Snow Model, consists of physical-based wind transport and sublimation algorithms. Clusters will be categorized into source and sink regions considering their topography and vegetation. The redistribution of snow mass at every timestep will be calculated based on the wind condition and the adjacent borders between clusters. This research seeks to pave the way for modeling other mass transport processes between tiles which considers the complex interactions within heterogeneous landscapes.