SnowSat-an AI approach towards efficient hydropower production
Purpose and goal
Climate change is rapidly altering the snow conditions all over the world, especially in high latitudes. Accurate depiction of snow distribution and amount is highly valuable for water management and climate studies, but still remains a big challenge. In this project, we aim to use Artificial Intelligence (AI) and Internet-of-Things (IoT) for improving the estimation of snow water storage in Sweden from satellite observations.
Expected results and effects
This project will lead to improved management of the hydropower sector, increased hydropower production, and enhanced preparedness to extreme weather events. This will further contribute to Sweden’s zero net-emission goal and help the society develop better climate mitigation and adaptation strategies.
Planned approach and implementation
This project consists of five major components: (1) develop a unique and comprehensive ‘ground truth’ snow dataset, (2) investigate the performances of different satellite observations for describing snow depth, (3) perform a benchmark of AI algorithms for snow depth and snow density estimation, (4) generate a novel and high-quality snow amount product, and (5) prototype a snow service portal based on the newly developed snow product.