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Record W4406055970 · doi:10.1029/2024jf007807

The Abundance and Persistence of Plunging Flows in Bedrock Canyons

2025· article· en· W4406055970 on OpenAlexafffund
Max Hurson, Jeremy G. Venditti, Colin D. Rennie, Eva Kwoll, Kirsti Fairweather, Daniel R. Whealdon-Haught, Saber Ansari, Kyle M. Kusack, Michael Church

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British ColumbiaCanadian Hydrographic ServiceUniversity of OttawaUniversity of VictoriaSimon Fraser University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsCanyonBedrockPersistence (discontinuity)Abundance (ecology)GeologyGeographyEcologyGeomorphologyGeotechnical engineeringBiology

Abstract

fetched live from OpenAlex

Abstract Landscape scale bedrock erosion is the integration of bedrock erosion at the reach scale, which is driven by particle impacts from sediment transport caused by near‐bed hydraulics. Plunging flow hydraulics have been identified in bedrock canyons and cause velocity profile inversions, which enhance near‐bed velocities, sediment transport, and the potential for bedrock erosion. Observations of plunging flows are limited, and the frequency and statistical properties of this hydraulic phenomenon have not been investigated. Here, we define metrics to identify velocity inversions and use them to detect instances of plunging flows through a 375 km reach of the Fraser River where channel morphology is controlled by bedrock. Isolated plunging flows are identified as well as plunging flow complexes where a series of plunges cause the core of maximum velocity to remain depressed in the water column for a prolonged distance. A significant relationship between plunging flows and bedrock exposure is identified, and plunging flows occupy more than half of the bedrock confined reaches. Stronger plunging flows are correlated with deeper and narrower channels with higher maximum shear stresses. Plunging flows are also concentrated in steeper reaches, which likely represent knickzones in the river profile. We use particle abrasion‐based bedrock erosion models to show that plunging flows drive reach‐scale incisions in bedrock rivers, creating deep bedrock pools. These pools dominate the incision into the bedrock, which sets the base level for their drainage areas and in turn sets the pace of landscape evolution.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

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

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 head0.021
GPT teacher head0.301
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes2
Has abstractyes

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