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Record W4281774949 · doi:10.1029/2021wr031527

Aerial Observations and Numerical Simulations Confirm Density‐Driven Streamwise Vortices at a River Confluence

2022· article· en· W4281774949 on OpenAlexafffund
Jason Duguay, Pascale M. Biron, Jay Lacey

Bibliographic record

VenueWater Resources Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversité de SherbrookeEnvironment and Climate Change Canada
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsConfluenceTributaryVortexLagrangian coherent structuresMesoscale meteorologyPointwiseGeologyMixing (physics)MechanicsParticle image velocimetryFlumeDensity contrastGeometryHydrology (agriculture)PhysicsFlow (mathematics)GeomorphologyTurbulenceOceanographyGeographyMathematicsComputer scienceGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract When rivers collide, complex three‐dimensional coherent flow structures are generated along the confluence's mixing interface. These structures mix streamborne pollutants and suspended sediment and have considerable bearing on the morphology and habitat quality of the postconfluent reach. A particular structure of interest—streamwise orientated vortices (SOVs)—were first detected in numerical simulations to form in pairs, one on each side of the mixing interface rotating in the opposite sense of the other. Since, it has proven difficult to detect SOVs in situ with conventional pointwise velocimetry instrumentation. Despite the lack of clear evidence to confirm their existence, SOVs are nevertheless considered important drivers of mixing and sediment transport processes at confluences. Additionally, their causal mechanisms are not fully known which hinders a complete conceptual understanding of these processes. To address these gaps, we analyze observations of strongly coherent SOVs filmed in aerial drone video of a mesoscale confluence with a stark turbidity contrast between its tributaries. Eddy‐resolved modeling demonstrates the SOVs' dynamics could only be accurately reproduced when a density difference (Δ ρ ) was imposed between the tributaries (Δ ρ = 0.5 kg/m 3 )—providing compelling evidence the observed SOVs are indeed a novel density‐driven class of SOV. This work confirms that SOVs exist, expands understanding of their generative processes and highlights the important role of small density gradients (e.g., ≤0.5 kg/m 3 ) on river confluence hydrodynamics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.297
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2022
Admission routes2
Has abstractyes

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