Flooding disasters, reproduction of salmonids, and development of Earth landscapes are all heavily impacted by the quantity and the quality of sediment transported by rivers. Yet after more than a century of work we have no satisfactory theory for sediment transport. Therefore empirical sediment transport formulas often poorly compare with field measurements, by sometimes order of magnitudes. Such poor formulas are used in engineering softwares based on two-phase shallow water equations, giving therefore overall unreliable results. Hence it is difficult to assess, for example, the impact upon a stream of extreme sediment-laden floods, which is an issue for public safety, management of water resources, and environmental sustainability within the critical zone. An important reason for our limited ability to predict sediment transport, is due to the very wide range of grain sizes leading to size segregation, also named grain size sorting. This phenomenon largely modifies fluxes and results in patterns that can be seen ubiquitously in nature, such as armouring.

The overall objective of this proposal is to conduct a multi-scale and multi-disciplinary study of size segregation in sediment transport to ultimately improve sediment transport modeling.

The specific objectives of the project focused on bedload transport are to (i) improve our understanding of the physical processes in size segregation, especially particle-particle interactions and the feedback with the transporting fluid; (ii) develop a hierarchy of process-based models at different scales for understanding, predicting and upscaling (iii) incorporate validated elementary segregation formulations in classical sediment transport models.

SegSed@ EGU2020