Bedload transport: a walk between randomness and determinism. Part 2. Challenges and prospects

Abstract

By the late nineteenth century, the scientific study of bedload transport had emerged as an offshoot of hydraulics and geomorphology. Since then, computing bedload transport rates has attracted considerable attention, but whereas other environmental sciences have seen their predictive capacities grow over time, particularly thanks to increased computing power, engineers and scientists are unable to predict bedload transport rates to within better than one order of magnitude. Why have we failed to improve our predictive capacity to any significant degree? A commonly shared view is that the study of bedload transport has more in common with the earth sciences than hydraulics: bedload transport rates depend on many processes that vary nonlinearly, involve various time and space scales, and are interrelated to each other. All this makes it difficult to view bedload as merely particle transport in a turbulent flow -something which can be studied in the laboratory in isolation from the natural environment. Over the last two decades, more emphasis has been put on the noisy dynamics characterizing bedload transport. This Vision Paper makes a strong case for recognizing noise (e.g. bedload transport rate fluctuations) as an intrinsic feature of bedload transport. Improving our predictive capacities requires a better understanding of the origins and nature of noise in bedload transport. This paper also reviews some of the challenges that need to be addressed in current research and teaching.

A new front condition for non-Boussinesq gravity currents

“…In the present manuscript's companion paper (Ancey, 2020), I outline some future prospects for the field; I also return to the question of why progress is currently so slow.…”

“…Sediment is transported at an average constant rateq s (as will be illustrated by Fig. 1 in the companion article (Ancey, 2020), the exact meaning of "average" in terms of timescale is more complicated than it first appears, but this will not be examined here). The sediment is composed of particles of similar size.…”

“…Some recent review papers have covered specific aspects of bedload transport (Hager, 2018;James, Jones, Grace, & Roberts, 2010;Papanicolaou, Elhakeem, Krallis, Prakash, & Edinger, 2008;Wainwright et al, 2015), but the topic is vast, and I will mainly give a hydraulic perspective. In a companion paper (Ancey, 2020), I outline some of the key challenges and prospects for bedload transport calculation. Additional material is provided in the online supplemental material (see the public data repository figshare: https://doi.org/10.6084/m9.…”

Short communication: Multiscalar roughness length decomposition in fluvial systems using a transform-roughness correlation (TRC) approach

“…rock chutes) could be isolated and determined for flood conditions. Also, multiscalar roughness length decomposition may contribute to an understanding of bedload transport processes, where accurate predictions rely on partitioning bed stresses between grain and form scales (Ancey, 2020).…”

“…Decomposing roughness lengths into different scales may contribute to an understanding of channel morphodynamics given that energy dissipation is increasingly recognized as a condition governing system behaviour (Eaton and Church, 2004;Nanson and Huang, 2018;Church, 2015). Also, the partitioning of bed stresses between grain and form scales is an important step in predicting bedload transport (Ancey, 2020).…”