This work introduces a model specifically designed for high-resolution snow depth estimation, leveraging in situ snow observations and snow-off lidar terrain features to provide an accessible and cost-effective method for snowpack modeling in regions lacking high-quality data products or collection networks. This work demonstrates that reliable basin-scale snow depth estimates can be achieved in difficult environments with very few observations and low institutional costs.