Water Resources Research Act Program

Details for Project ID UT_2025_Johnson

Novel Snowtography Edge Computer Vision System (SECVS) for monitoring catchment-scale snowpack variation in Parleys Creek Watershed, Utah

Institute: Utah
Year Established: 2025 Start Date: 2026-01-01 End Date: 2026-12-31
Total Federal Funds: $32,000 Total Non-Federal Funds: $32,000

Principal Investigators: Ryan Johnson

Project Summary: Current snow monitoring methods, crucial for water supply forecasts in the western US, can be expensive to implement across entire watersheds and are spatially discontinuous. This project aims to develop an affordable alternative using camera vision, machine learning, and edge computing, called ?Snowtography?, to support snow depth monitoring across a key water-supplying catchment in Northern Utah, Parleys Creek. The project will prototype a spatially distributed snow monitoring network that uses computer vision to determine snow depth from camera images and seamlessly share it with our data server. The system will mimic a wildlife camera, but be adapted for monitoring catchment snow depth. System deployment will use state-of-the-art machine learning algorithms to identify site locations that capture the heterogeneity of the catchment. This work will kickstart future research to refine the system, improve its accuracy, and combine it with existing snow models to create detailed snow maps. This research is a first step in showing that the camera-based approach can provide reliable snow data at a lower cost, helping to improve water management decisions.??