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Record W3168248865 · doi:10.5194/egusphere-egu21-10160

Effects of episodic sediment supply on experimental step-pool channel morphology, bedload transport and channel stability

2021· article· en· W3168248865 on OpenAlexaff
Jiamei Wang, Marwan A. Hassan, Matteo Saletti, Xingyu Chen, Xudong Fu, Hongwei Zhou, Xing-guo Yang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBed loadFlumeGeologySedimentErosionAggradationChannel (broadcasting)Sediment transportHydrology (agriculture)GeomorphologyGrain sizeHyperconcentrated flowMagnitude (astronomy)Flow (mathematics)Geotechnical engineeringMechanicsFluvialPhysics

Abstract

fetched live from OpenAlex

Steep step-pool streams are often coupled to adjacent hillslope, directly receiving episodic sediment supply from mass movement processes such as landslides and debris flows. The response of step-pool channels to the variations in sediment supply remains largely unexplored. We conducted flume experiments with a poorly sorted grain-size distribution in an 8%-steep, 5-m long flume with variable width at the University of British Columbia, to study the effects of episodic sediment supply on channel evolution. After a conditioning phase with no feed, the channel was subjected to sediment pulses of different magnitude and frequency under constant flow discharge. High-resolution data of hydraulics, bedload transport, bed surface grain size, and channel morphology were collected every 10-20 minutes and an additional time at the end of each pulse. In response to sediment pulses, we recorded an increase in bedload transport rates, channel aggradation, bed surface fining, and continuous step formation and collapse. In between pulses, bedload rates dropped by several orders of magnitude, net erosion occurred, the bed surface gradually coarsened, and steps became more stable. The small-magnitude high-frequency pulses caused smaller but more frequent spikes in bedload transport, bed surface evolution, and thus step stability. Instead, the large-magnitude low-frequency pulses cause larger changes but provided a longer time for the channel to recover. This suggests that in step-pool channels pulse magnitude is a key control on channel rearrangement, while pulse frequency controls how fast and strong the recovery is. The frequency and stability of steps varied as a function of local channel width, showing that channel geometry is a primary control on step formation and stability even under episodic sediment supply conditions. Instead, the effect of sediment pulses is less important because the total number and average survival time of steps were similar among runs with different pulses. The critical Shields stress decreased following sediment pulses, then increased immediately after, and fluctuated until the next pulse. The variations in sediment supply caused cycles in bedload transport rate, surface and bedload texture, thus controlling the variability in the threshold for motion. Our results indicate that episodic sediment supply is a primary control on the evolution of step-pool channels, with sediment feed magnitude affecting mostly morphological changes, and sediment feed frequency controlling channel stability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2021
Admission routes1
Has abstractyes

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