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Record W2565676891 · doi:10.1002/2016wr019460

Experiment on temporal variation of bed load transport in response to changes in sediment supply in streams

2016· article· en· W2565676891 on OpenAlexafffund
Maria A. Elgueta‐Astaburuaga, Marwan A. Hassan

Bibliographic record

VenueWater Resources Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlumeSedimentSediment transportBedformGeologyBed loadSTREAMSSoil scienceHydrology (agriculture)Grain sizeEnvironmental scienceGeomorphologyGeotechnical engineeringFlow (mathematics)Mechanics

Abstract

fetched live from OpenAlex

Abstract A flume experiment was conducted to study channel adjustment to episodic sediment supply in mountain streams. The bulk sediment used for the bed and feed included grain sizes 0.5–64 mm with geometric mean D of 5.7 mm. Water discharge was held constant for 40 h, and 300 kg of sediment was supplied through a range of scenarios. Bed slope, sediment storage, sediment transport, and bed surface texture responded to sediment supply. During the first of seven runs, bed slope decreased from 0.022 m m (flume slope) to 0.018 m m due to sediment starvation. Bed slope increased beginning in the second run as the bed aggraded due to preferential storage of grains >8 mm. Transport rate and bed‐surface particle size were significantly affected by magnitude‐frequency of sediment feed. Under constant feed, transport rate increased gradually and D ranged between 12 and 15 mm. Instead, sediment pulses caused a pronounced increase in sediment transport rate and surface fining, trends that were inverted as sediment evacuated. At the run scale, sediment transport and storage behaved as with constant feed if pulse relaxation time exceeded time between pulses. The increase in transport rate and surface fining were proportional to pulse size. After the 300 kg pulse, transport rate reached and D was <10 mm. After 75 kg pulses, transport rate reached and D was >12 mm. Textural differences on the initial bed surface influenced the patterns of sediment transport. Channel adjustment was controlled by magnitude‐frequency of sediment feed and not by total feed.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0020.000

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 head0.027
GPT teacher head0.296
Teacher spread0.269 · 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

Citations35
Published2016
Admission routes2
Has abstractyes

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