Bedload Transport in Laboratory Rivers

Lajeunesse, É.; Devauchelle, Olivier; Lachaussée, Florent; Claudin, Philippe

doi:10.1002/9781118971437.ch15

Cited by 12 publications

(11 citation statements)

References 83 publications

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“…When modeling unisize tracer sediment dispersion under normal flow conditions, the SILKE model is similar to the one developed by Lajeunesse et al (2013Lajeunesse et al ( , 2017Lajeunesse et al ( , 2018, which is based on the sediment balance model developed by Charru et al (2004), Charru and Hinch (2006), Charru (2006), and Lajeunesse et al (2010). The difference is that the SILKE model includes particle diffusion, and we maintain the active layer concept, whereas Lajeunesse et al (2013Lajeunesse et al ( , 2017Lajeunesse et al ( , 2018 model the number of static and moving particles. In section 3.4, we will analytically compare both models.…”

Section: Conservation Equationsmentioning

confidence: 99%

A Well‐Posed Alternative to the Hirano Active Layer Model for Rivers With Mixed‐Size Sediment

2019

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The active layer model (Hirano, 1971) is frequently used for modeling mixed‐size sediment river morphodynamic processes. It assumes that all the dynamics of the bed surface are captured by a homogeneous top layer that interacts with the flow. Although successful in reproducing a wide range of phenomena, it has two problems: (1) It may become mathematically ill‐posed, which causes the model to lose its predictive capabilities, and (2) it does not capture dispersion of tracer sediment. We extend the active layer model by accounting for conservation of the sediment in transport and obtain a new model that overcomes the two problems. We analytically assess the model properties and discover an instability mechanism associated with the formation of waves under conditions in which the active layer model is ill‐posed. Numerical simulations using the new model show that it is capable of reproducing two laboratory experiments conducted under conditions in which the active layer model is ill‐posed. The new model captures the formation of waves and mixing due to an increase in active layer thickness. Simulations of tracer dispersion show that the model reproduces reasonably well a laboratory experiment under conditions in which the effect of temporary burial of sediment due to bedforms is negligible. Simulations of a field experiment illustrate that the model does not capture the effect of temporary burial of sediment by bedforms.

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Section: Conservation Equationsmentioning

confidence: 99%

A Well‐Posed Alternative to the Hirano Active Layer Model for Rivers With Mixed‐Size Sediment

2019

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“…However their measurement proves difficult during active transport. On the other hand, experimental and field investigations provide the total concentration of tracers, c (Sayre and Hubbell, 1965;Lajeunesse et al, 2017). This quantity is conservative, as the total amount of tracers, M = c dx, is preserved.…”

Section: Propagation Of a Plume Of Tracersmentioning

confidence: 99%

“…Laboratory measurements of bedload often use top-view images (Martin et al, 2012;Lajeunesse et al, 2017). Unless individual particles can be tracked, the tracers at rest are usually indistinguishable from those entrained by the flow.…”

Section: Propagation Of a Plume Of Tracersmentioning

confidence: 99%

“…E is the erosion rate, defined as the number of bed particles set in motion per unit time and surface. Similarly, the deposition rate D is defined as the number of bedload particles settling on the bed per unit time and surface (Charru et al, 2004;Charru, 2006;Lajeunesse et al, 2010b;Seizilles et al, 2014;Lajeunesse et al, 2017).…”

Section: Entrainment Of Tracersmentioning

confidence: 99%

“…For instance, Lajeunesse et al (2017) tracked a plume of dyed particles in an experimental channel. Although the flow was constant in the laboratory, the tracers still dispersed as they traveled downstream.…”

Section: Introductionmentioning

confidence: 99%

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Advection and dispersion of bedload tracers

Lajeunesse¹,

Devauchelle²,

James³

2017

Preprint

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We use the erosion-deposition model introduced by Charru et al. (2004) to simulate numerically the evolution of a plume of bedload tracers entrained by a steady flow. In this model, the propagation of the plume results from the stochastic exchange of particles between the bed and the bedload layer. We find a transition between two asymptotic regimes. At early time, the tracers, initially at rest, are progressively set into motion by the flow. During this entrainment regime, the plume, strongly skewed in 5 the direction of propagation, continuously accelerates while spreading non-linearly. With time, the skewness of the plume eventually reaches a maximum value before decreasing. This marks the transition to an advection-diffusion regime in which the plume becomes increasingly symmetrical, spreads linearly, and advances at constant velocity. We derive analytically the expressions of the position, the variance and the skewness of the plume, and investigate their asymptotic regimes. Our model assumes steady state. In the field, however, bedload transport is intermittent. We show that the asymptotic regimes become 10 insensitive to this intermittency when expressed in terms of the distance traveled by the plume. If this finding applies to the field, it might provide an estimate for the average bedload transport rate.

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Monitoring gravel augmentation in a large regulated river and implications for process‐based restoration

Arnaud

Piégay

Béal

et al. 2017

Earth Surf Processes Landf

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International audienceThe artificial gravel augmentation of river channels is increasingly being used to mitigate the adverse effects of river regulation and sediment starvation. A systematic framework for designing and assessing such gravel augmentations is still lacking, notably on large rivers. Monitoring is required to quantify the movement of augmented gravel, measure bedform changes, assess potential habitat enhancement, and reduce the uncertainty in sediment management. Here we present the results of an experiment conducted in the Rhine River (French and German border). In 2010, 23 000 m3 of sediments (approximately the mean annual bedload transport capacity) were supplied in a by-passed reach downstream of the Kembs dam to test the feasibility of enhancing sediment transport and bedform changes. A 620-m-long and 12-m-wide gravel deposit was created 8 km downstream from the dam. Monitoring included topo-bathymetric surveys, radio-frequency particle tracking using passive integrated transponder (PIT) tags, bed grain size measurement, and airborne imagery. Six surveys performed since 2009 have been described (before and after gravel augmentation, and after Q2 and Q15 floods). The key findings are that (i) the augmented gravel was partially dispersed by the first flood event of December 2010 (Q1); (ii) PIT tags were found up to 3200 m downstream of the gravel augmentation site after four years, but the effects of gravel augmentation could not be clearly distinguished from the effects of floods and internal remobilization on more than 3500 m downstream; (iii) linear and log-linear relationships linking bedload transport, particle mobility, and grain size were established; and (iv) combined bathymetry and PIT tag surveys were useful for evaluating potential environmental risks and the first morpho-ecological responses. This confirmed the complementary nature of such techniques in the monitoring of gravel augmentation in large rivers

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Bedload Transport in Laboratory Rivers

Cited by 12 publications

References 83 publications

A Well‐Posed Alternative to the Hirano Active Layer Model for Rivers With Mixed‐Size Sediment

A Well‐Posed Alternative to the Hirano Active Layer Model for Rivers With Mixed‐Size Sediment

Advection and dispersion of bedload tracers

Monitoring gravel augmentation in a large regulated river and implications for process‐based restoration

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