Verbeterde sneeuwhydrologie met Sentinel-1: Van Radar-Sneeuw Interacties tot Nauwkeurigere Rivierafvoer Voorspellingen

Seasonal snow plays a vital role in Earth's hydrological cycle, serving as a temporary water reservoir supplying approximately one-sixth of the global population. However, accurately quantifying the amount of water stored in snow, particularly in complex mountainous terrain, remains a significant challenge. This research addresses this challenge by leveraging data from ESA's Sentinel-1 satellite mission. By assimilating Sentinel-1-derived snow depth into a coupled routing and land surface model, we obtained an improvement in streamflow simulations, enhancing both the timing and volume of snowmelt contributions. A second component of this research focuses on understanding the interactions between C-band radar waves and snow. Through tower-based and mobile sled-based radar experiments, we revealed considerable volume scattering within the snowpack and showed how stratigraphical changes can introduce potential uncertainties in retrieval algorithms. This refines our ability to interpret Sentinel-1 satellite data and leverage it for accurate snow depth estimation and its application in water resource management.