Snow Information for Hydropower

September 2020 till August 2021

Executive summary

The hydropower industry generates over €64B each year and snow meltwater accounts for approximately one quarter of this turnover. Hydropower operators need accurate information on snow quantities and snow melt in their catchment for reliable streamflow forecasts. These forecasts are paramount for an efficient production planning, flood protection, and water resources management. Today, hydropower stations are losing around 10% of potential profits, because quantifying the water bound in snow is very challenging in highly variable mountain areas. Current approaches to quantify this snow water equivalent within catchments typically lack sufficient accuracy, spatial coverage and temporal resolution.

To solve this problem, SNOWi will combine the strengths of multi-satellite observations, mobile ground measurements and numerical weather forecasts into one comprehensive snow monitoring system. Our Swiss partner ExoLabs computes daily high-resolution information on the spatial snow cover distribution based on multiple optical and SAR-based satellite observations in near-real time. Our Norwegian partner Think Outside´s small and lightweight radars offer multiple deployment options for basin wide mapping of the snow water equivalent, and snow melting status. UBIMET has developed a physical snow balance model based on highly precise weather forecasts for mountainous regions. Continuous recalibration of this snow model based on spatially explicit satellite observations and highly precise ground measurements will result in accurate high-resolution products on snow depth, snow water equivalent and liquid snow melt. This service will be available via a user-friendly API, helping hydropower companies to improve their water management, in order to waste less water and sell energy for the optimal price to improve overall profits.

Project partners

Project funding

SNOWi is one of 15 winning product development projects of the H2020 Parsec Accelerators program and receives financial support of the EC and PARSEC Accelerator.