Abstract ID: 3.9400 | Accepted as Talk | Talk/Oral | TBA | TBA

Bedload transport plays a critical role in shaping river systems, with significant implications for hydropower plant operations, riverine ecosystems, and the mitigation of natural hazards related to sediment transport and flooding. Despite its importance, the potential evolution of bedload transport capacity under future climate change in Alpine glacierized catchments remains poorly understood. We seek to address this gap by coupling a glacio-hydrological model to bedload transport capacity equations. This can inform how climate-driven changes in discharge are expected to affect bedload transport capacity in such catchments.

We rely on spatially interpolated meteorological datasets as model input for historical climate conditions and on corresponding climate change projections for an ensemble of future scenarios, both provided by MeteoSwiss. We use a semi-lumped hydrological model including an extended temperature-index melt model formulation (the melt model of Hock, 1999) to simulate glacier ice and snowmelt and mean discharge at the daily scale. We model the glacial area and volume changes over time using the delta-h method of Huss et al. (2010). To resolve sub-daily discharge variability, we developed a downscaling method based on the principle of maximal entropy. This method disaggregates mean daily discharge to daily flow duration curves at hourly time steps by relying on meteorological and hydrological variables. These flow duration curves are then integrated with bedload transport capacity formulations to estimate the maximum bedload volumes which could take place under conditions of unlimited sediment supply.

Our analysis was carried out in numerous gauged and ungauged high elevation glaciarized catchments across Switzerland, providing an extensive assessment of spatial variability in bedload transport capacity. This methodology is designed to be scalable to the entire Alpine region, offering a broader perspective on how climate change is modifying bedload transport rates and volumes.