Network-scale modelling of bedload transport in Alpine rivers using D-CASCADE model

Quantifying sediment transport dynamics in Alpine rivers is essential for predicting their geomorphological evolution, for managing flood risks and fluvial ecosystems, as well as for sustainable management of hydropower schemes. However, actual data on sediment transport, particularly for the bedload fraction, are often very scarce (if not absent altogether) due to the challenges inherent in collecting such information. Thus bedload transport dynamics have to be predicted at the basin scale by relying on limited (in space and time) field observations. However, models capable of simulating bedload transport at the network scale in mountain rivers are very few, and to the best of our knowledge, their validation has never been carried out.

The primary objective of this research is to evaluate the performance of the D-CASCADE model – after adapting it to work in Alpine rivers – to simulate bedload transport dynamics at a network scale in the Sulden/Solda river basin (Italian Alps). The Sulden catchment was selected due to the sediment transport monitoring station present at its outlet (130 km²) as well as for the long duration of bedload transport throughout the year due to its nivo-glacial hydrological regime. Since 2014, bedload transport has been continuously monitored in the Sulden River using geophones, which provide high-frequency data on bedload movement and capture temporal variations in bedload transport. To calibrate the geophone signals, regular bedload sampling was conducted. The data obtained from these samples provided detailed insights into the grain size distribution of the transported material at the outlet reach of the modelled network. This empirical information was crucial in fine-tuning the adapted D-CASCADE model and refining existing transport capacity formulas to characterize the connectivity properties of the Sulden network in terms of bedload flux dynamics, path lengths and velocities as well as sediment budgeting of the different reaches.

Preliminary validation of the adapted D-CASCADE model shows a promising agreement between predicted and observed bedload transport rates at the monitoring station. The model demonstrates the potential in reconstructing bedload transport patterns across the entire river network, identifying key sediment sources contributing to the overall sediment flux. Additionally, the model illustrates the spatial and temporal variability in bedload transport, highlighting the complexity of sediment dynamics in Alpine rivers.