Hydraulic geometry of secondary channels of lower Fraser River, British Columbia, from acoustic Doppler velocimetry
Bibliographic record
Abstract
The hydraulics and morphology of secondary channels within the lower Fraser River gravel reach have been examined using data collected during the 2002 freshet utilising an acoustic Doppler current profiler with integrated GPS. A range of sub-reach types was sampled, corresponding to position within an individual secondary channel. Surface and sub-surface grain size distribution data were collected as well. Sub-reach averaged water surface width, mean hydraulic depth and mean velocity data generally conformed well (R2 > 0.9) to the form of classical at-a-station hydraulic geometry relations, at higher flow. Spatial and frequency distributions of near-bottom velocity and channel depth were examined. In general, sub-reach types stratified along gradients of width, depth, velocity and sedimentology, although there were exceptions. Additional data collected at high flow were used to generate bankfull scaling relations for secondary channels in the gravel reach. Again, the data conform well to a simple power law, up to and including data points from the main channel. The water surface width to discharge relation agrees with work by Bray (1973) in Alberta gravel bed rivers and with the more general trend of a one-half power relation. However, the mean hydraulic depth to discharge relation (and by continuity, the mean velocity to discharge relation) deviate from previous results. Data collection in the field was somewhat facilitated by the use of the acoustic Doppler current profiler but post-processing time requirements were high and, ultimately, the operating frequency led to certain sampling problems. Issues surrounding the use of these instruments in river channels are discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".