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Record W3082242226 · doi:10.1002/rra.3699

Experiments on restoring alluvial cover in straight and meandering rivers using gravel augmentation

2020· article· en· W3082242226 on OpenAlexafffund
Matilde Welber, Elli Papangelakis, Peter Ashmore, Bruce MacVicar

Bibliographic record

VenueRiver Research and Applications · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of WaterlooWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlluviumCover (algebra)GeologyChannel (broadcasting)SedimentHydrology (agriculture)GeomorphologyGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Successful management of natural and engineered channels with discontinuous alluvial cover requires knowledge of how the cover develops and evolves. We report on physical model experiments designed to compare alluvial cover dynamics in straight and sinuous fixed‐bed channels at a range of gravel‐bed material supply rates and constant discharge conditions. Experiments investigated the formation of alluvial cover from a bare bed, relationships between equilibrium cover characteristics and sediment supply rate, and the evolution of an initial uniform cover of varying thickness. A stable partially‐alluviated state is achieved in both the straight and sinuous channels for a range of sediment supply rates. The areal extent and stored mass of the cover increase progressively with supply rate, and the rate of increase is higher in the straight channel. While alluvial cover develops from isolated patches in the straight channel, cover in the sinuous channel develops as well‐defined bars, with deposition on the inside of bends and expanding outwards along the channel as cover area increases. Artificially emplaced cover quickly adjusts to a cover extent within 4–20% of that formed from a bare bed at the same feed rate, with initial cover thickness only influencing the final cover in the sinuous channel. Neither the sinuous nor the straight channel can sustain an alluvial cover in the absence of upstream sediment supply. This study can inform the management of semi‐alluvial channels because it highlights the primary roles of sediment supply and planform geometry in maintaining an alluvial cover in natural and engineered channels.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.132
GPT teacher head0.366
Teacher spread0.234 · 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

Citations13
Published2020
Admission routes2
Has abstractyes

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