Advection and dispersion of bed load tracers

Lajeunesse, É.; Devauchelle, Olivier; James, François

doi:10.5194/esurf-6-389-2018

Cited by 21 publications

(52 citation statements)

References 49 publications

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“…The advective velocity in both models is mathematically equivalent if we consider that the number of static and moving particles in their model is represented by the active layer thickness and the particle activity, respectively, in our model. The diffusivity of the model by Lajeunesse et al () depends on the square of the particle step length and inversely on the particle travel time. Our results are mathematically equivalent to theirs if we relate the deposition rate to the inverse of the particle travel time.…”

Section: Instability Well‐posedness and Dispersionmentioning

confidence: 99%

“…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%

“…An advection-diffusion equation for the propagation of tracer sediment in the long term was also obtained by Lajeunesse et al (2018) using their sediment balance model. In the following, we compare their resulting equation to the one of the SILKE model.…”

Section: Tracer Sediment Dispersionmentioning

confidence: 99%

“…For instance, the active layer thickness is representative of the range of elevations at which the sediment interacts with the flow and that are responsible for significant vertical mixing, and this property is not physically equivalent to the number of static particles. Moreover, while in the model by Lajeunesse et al (2018), the number of static particles is a variable of the model under unsteady conditions; in our case the active layer thickness is a priori assigned (or related to flow and bed properties).…”

Section: Tracer Sediment Dispersionmentioning

confidence: 99%

“…A different approach for modeling tracer dispersion consists of accounting for the number of static and moving particles in the bed. In this way, Lajeunesse et al (, , ) model dispersion of a plume of unisize tracer sediment under normal flow conditions. Ancey et al (, ) considered the statistics of unisize sediment transport and showed that this can be well captured using a discrete statistic theory (i.e., birth‐death discrete Markov processes).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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: Instability Well‐posedness and Dispersionmentioning

confidence: 99%

Section: Conservation Equationsmentioning

confidence: 99%

Section: Tracer Sediment Dispersionmentioning

confidence: 99%

Section: Tracer Sediment Dispersionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2019

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Lost and found: Maximizing the information from a series of bedload tracer surveys

MacVicar

Papangelakis

2021

Earth Surf Processes Landf

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Bedload particle tracking is a technique used to better understand sediment dynamics in rivers. Despite technical advances, tracers may be missed in field surveys. The missed tracers may bias the study results even where recovery rates are high, for example if they are preferentially buried close to the seeding site or transported downstream of the surveyed reach. The goal of the current study is to demonstrate that more information can be extracted from a series of bedload tracer surveys by carefully considering the fate of missing and found tracers and implementing a set of strategies to include the (incomplete) information on sediment displacement metrics. A set of open-source Matlab algorithms collectively called PITtrack are described that perform the calculations. Results from two tracer datasets show that commonly used sediment displacement metrics are sensitive to the inclusion of the missing tracers, even for cases with high recovery rates. Metrics that describe the variance and skewness of the tracers as they disperse are particularly sensitive. The recommended strategy is to include (a) inferred positions of tracers that are missing but unmoved, (b) likely positions of tracers that are missing, moved, and movement can be attributed to a survey period within the uncertain period that meets a dominant flood criterion, and (c) last known positions of tracers considered lost because they go missing and are never found again. Overall the results offer a method to include all available information on missing tracers to better understand sediment dispersion. Future work should be done to assess the classification system for a wider range of field sites and further refine classification based on spatial or other information.

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Untangling the controls on bedload transport in a wood‐loaded river with RFID tracers and linear mixed modelling

Clark

Bennett

Ryan-Burkett

et al. 2022

Earth Surf Processes Landf

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Bedload transport is a fundamental process by which coarse sediment is transferred through landscapes by river networks and may be well described stochastically by distributions of grain step length and rest time obtained through tracer studies. To date, none of these published tracer studies have specifically investigated the influence of large wood in the river channel on sediment transport dynamics, limiting the applicability of stochastic sediment transport models in these settings. Large wood is a major component of many forested rivers and is increasing due to anthropogenic ‘Natural Flood Management’ (NFM) practices. This study aims to investigate and model the influence of large wood on grain‐scale bedload transport. We tagged 957 cobble to pebble sized particles (D50 = 73 mm) and 28 pieces of large wood (> 1 m in length) with radio frequency identification (RFID) tracers in an alpine mountain stream. We monitored the transport distance of tracers annually over 3 years, building distributions of tracer transport distances with which to compare with published distributions from wood free settings. We also applied linear mixed modelling (LMM), to tease out the influence of wood from other controls on likelihood of entrainment, deposition, and the transport distances of sediments. Tracer sediments accumulated both upstream and downstream of large wood pieces, with LMM analysis confirming a reduction in the probability of entrainment of tracers closer to wood in all 3 years. Upon remobilization, tracers entrained from positions closer to large wood had shorter subsequent transport distances in each year. In 2019, large wood also had a trapping effect, significantly reducing the transport distances of tracer particles entrained from upstream, that is forcing premature deposition of tracers. This study demonstrates the role of large wood in influencing bedload transport in alpine stream environments, with implications for both natural and anthropogenic addition of wood debris in fluvial environments.

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Advection and dispersion of bed load tracers

Cited by 21 publications

References 49 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

Lost and found: Maximizing the information from a series of bedload tracer surveys

Untangling the controls on bedload transport in a wood‐loaded river with RFID tracers and linear mixed modelling

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