Patterns of bedload entrainment and transport in forested headwater streams of the Columbia Mountains, Canada
Bibliographic record
Abstract
Abstract We monitor bedload transport and water discharge at six stations in two forested headwater streams of the Columbia Mountains, Canada. The nested monitoring network is designed to examine the effects of channel bed texture, and the influence of alluvial (i.e. step pools and riffle pools) and semialluvial morphologies (i.e. boulder cascades and forced step pools) on bedload entrainment and transport. Results indicate that dynamics of bedload entrainment are influenced by differences in flow resistance attributable to morphology. Scaled fractional analysis shows that in reaches with high form resistance most bedload transport occurs in partial mobility fashion relative to the available bed material, while calibers finer than 16 mm attain full mobility during bankfull flows. Equal mobility transport for a wider range of grain sizes is achieved in reaches exhibiting reduced form resistance. Our findings confirm that the Shields value for mobilization of the median surface grain size depends on channel gradient and relative submergence; however, we also find that these relations vary considerably for cobble and gravel bed channels due to proportionality between dimensionless shear stress and grain size. Exponents of bedload rating curves across sites correlate most with the D90s of the mobile bed, however, where grain effects are controlled (i.e. along individual streams), differences in form resistance across morphologies exert a primary control on bedload transport dynamics. Application of empirical formulae developed for use in steep alpine channels present variable success in predicting transport rates in forested snowmelt streams. Formulae that explicitly account for reductions in mobile bed area and high morphological resistance associated with woody debris provide the best approximation to observed empirical data. Copyright © 2014 John Wiley & Sons, Ltd.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".