Three‐Dimensional Flow Above River Bedforms: Insights From Numerical Modeling of a Natural Dune Field (Río Paraná, Argentina)

Lefebvre, Alice

doi:10.1029/2018jf004928

Cited by 28 publications

(28 citation statements)

References 49 publications

(168 reference statements)

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“…Johns and Xing, 1993; Omidyeganeh and Piomelli, 2013; Chen et al ., 2015). Of particular relevance to our study, Lefebvre (2019) used numerical modelling to show that the lateral orientation of the lee‐side slope relative to the mean direction of the flow passing over the bedform is a primary control of the lee‐side flow separation and turbulent wake production. Lefebvre (2019) found that as the lee‐side slope became less perpendicular to the mean flow direction, flow separation was reduced.…”

Section: Discussionmentioning

confidence: 99%

“…Of particular relevance to our study, Lefebvre (2019) used numerical modelling to show that the lateral orientation of the lee‐side slope relative to the mean direction of the flow passing over the bedform is a primary control of the lee‐side flow separation and turbulent wake production. Lefebvre (2019) found that as the lee‐side slope became less perpendicular to the mean flow direction, flow separation was reduced. The exclusion of bedform three‐dimensionality in our model should be considered when extrapolating our results to natural rivers.…”

Section: Discussionmentioning

confidence: 99%

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Sand settling through bedform‐generated turbulence in rivers

Yuill

Wang

Meselhe

et al. 2020

Earth Surf Processes Landf

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Fluvial bedforms generate a turbulent wake that can impact suspended-sediment settling in the passing flow. This impact has implications for local suspended-sediment transport, bedform stability, and channel evolution; however, it is typically not well-considered in geomorphologic models. Our study uses a three-dimensional OpenFOAM hydrodynamic and particle-tracking model to investigate how turbulence generated from bedforms and the channel bed influences medium sand-sized particle settling, in terms of the distribution of suspended particles within the flow field and particle-settling velocities. The model resolved the effect of an engineered bedform, which altered the flow field in a manner similar to a natural dune. The modelling scenarios alternated bed morphology and the simulation of turbulence, using detached eddy simulation (DES), to differentiate the influence of bedform-generated turbulence relative to that of turbulence generated from the channel bed. The bedform generated a turbulent wake that was composed of eddies with significant anisotropic properties. The eddies and, to a lesser degree, turbulence arising from velocity shear at the bed substantially reduced settling velocities relative to the settling velocities predicted in the absence of turbulence. The eddies tended to advect sediment particles in their primary direction, diffuse particles throughout the flow column, and reduced settling likely due to production of a positively skewed vertical-velocity fluctuation distribution. Study results suggest that the bedform wake has a significant impact on particle-settling behaviour (up to a 50% reduction in settling velocity) at a scale capable of modulating local suspended transport rates and bedform dynamics.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Sand settling through bedform‐generated turbulence in rivers

Yuill

Wang

Meselhe

et al. 2020

Earth Surf Processes Landf

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“…This implies that dune shape has a major impact on energy decay. Recent simulations using 3D dune beds relate the presence and size of the flow separation zone and the wake, to the presence and properties of the slip face, as compared to the crest line or bedform height (Lefebvre, 2019). Approximations of the presence and size of reverse flow and wake can be derived from a bathymetric map (Lefebvre, 2019).…”

Section: Introductionmentioning

confidence: 99%

Observations of dune interactions from DEMs using through-water Structure from Motion

et al. 2020

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The role of three-dimensionality (3D) in modulating both flow and sediment transport remains poorly understood. 3D bed elevation measurements are difficult to obtain due to irregular dune shapes and submergence. Using photogrammetric tools for topographic reconstruction has become popular in surface studies, yet water refraction makes through-water image capturing of submerged dunes still challenging. We show that throughwater images and Structure from Motion (SfM) tools can produce accurate Digital Elevation Models (DEMs) of a measured dune field, with a high level of detail. It is a low-cost and non-intrusive alternative for submerged bed elevation measurements. We provide a detailed SfM workflow, introduce and discuss the use of camera coordinates and underwater ground control points, and processing steps needed to obtain high accuracy DEMs. Our method results in DEMs with mm resolution in controlled laboratory conditions. New data for 23 dune field DEMs from 6 experiments were obtained and are presented. The dune field DEM time series provide insights on dune interaction processes. In our experiments, merging and defect creation were most common. Merging decreases the number of bedforms, and defect creation is responsible for more bedforms. Dunes continue to interact and jostle after achieving equilibrium. Simple crests are much more frequently observed than irregular, sinuous or double crests. Two-dimensional (2D) crest shapes were observed, although crest shapes were generally of 3D nature. Observed dune migration rates are not steady and vary in time and space. Bedform splitting speeds up dune migration, whilst neighbouring dunes tend to accelerate or decelerate. We identify a cascade of processes and show that 3D DEMs at high frequency are required to resolve observed rapid deformations and interaction of dunes. The identified dune interaction processes are inherent to sediment flux (variability), whereas the temporal component of the underlying sediment transport processes is still not well understood in relation to average transport.

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“…(2018) provided technical details of the free access software named Bedforms‐ATM (Bedforms Analysis Toolkit for Multiscale Modeling), which proposes standardizing the scale‐based discrimination and dimensionality quantification of natural bed forms in a single platform and whose structure encourages its expandability via collaboration from the community of users. The use of Bedforms‐ATM to conduct scientific research has been reported by Lefebvre (2019).…”

Section: Introductionmentioning

confidence: 99%

“…For example, Bradley and Venditti (2017) have compiled flow and dune dimension data for bed forms in unidirectional flows, and have made the data available as supplementary material; researchers have published nearly 400 000 datasets to date through the data publisher PANGAEA, including 125 related to bed forms; Gutierrez et al (2018) provided technical details of the free access software named Bedforms-ATM (Bedforms Analysis Toolkit for Multiscale Modeling), which proposes standardizing the scale-based discrimination and dimensionality quantification of natural bed forms in a single platform and whose structure encourages its expandability via collaboration from the community of users. The use of Bedforms-ATM to conduct scientific research has been reported by Lefebvre (2019).…”

Section: Introductionmentioning

confidence: 99%

Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end

Gutiérrez

Lefebvre

Núñez‐González

et al. 2020

Earth Surf Processes Landf

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In recent years, open and data‐driven science has fostered very important scientific breakthroughs. This study describes the challenges and opportunities for the scientific community devoted to bed form dynamics research in adopting such scientific paradigms through, for example, engineered data sharing, formal recognition of scientists who collect the data, and collaborative development of free accessible software. It highlights that once these actions are completed, the potential application of deep learning techniques could substantially improve bed form models and the scientific understanding of bed form dynamics. Likewise, it discusses the potential of Bedforms‐ATM, a free available software, to standardize some bed form data analysis techniques. We propose that the technical challenges be tackled by following scholarly accepted/proposed standards (e.g. FAIR Guiding Principles, Geoscience Papers of the Future), using the body of knowledge being built on the matter by some institutions (e.g. Federation of Earth Science Information Partners), and through technical discussions at scientific meetings such as MARID. © 2020 John Wiley & Sons, Ltd.

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Three‐Dimensional Flow Above River Bedforms: Insights From Numerical Modeling of a Natural Dune Field (Río Paraná, Argentina)

Cited by 28 publications

References 49 publications

Sand settling through bedform‐generated turbulence in rivers

Sand settling through bedform‐generated turbulence in rivers

Observations of dune interactions from DEMs using through-water Structure from Motion

Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end

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