Pulse Coherent Doppler Profiler Measurement of Bedload Transport
Bibliographic record
Abstract
Abstract Prior studies demonstrate that bottom velocity measurements from Doppler sonar systems are proportional to bedload transport rates. These observations suggest that acoustically based systems offer a capability for rapid sampling of bedload transport processes. Before these measurements can be fully utilized, validation and understanding of the sampling mechanism are essential. We explore the measurement mechanism through a series of laboratory trials with a field instrument, the multi‐frequency coherent Doppler profiler (MFDop). The MFDop system is a multi‐frequency (1.2–2.2 MHz), bistatic Doppler sonar that provides three‐component ensemble‐averaged velocity profiles over a ∼30 cm depth interval with up to 1 mm resolution at a rate of 50 profiles/sec. Tests of the MFDop system were carried out in the main flume in field‐scale conditions at the St. Anthony Falls Laboratory (SAFL) using 1 ms−1 mean flows over a mobile bed of sand with median grain size d50 = 0.4 mm. We find agreement between MFDop transport measurements and measurements based on bedform migration rates, and sediment traps built into the SAFL flume. Predictions using the Meyer‐Peter and Müller (1948) empirical equation closely match our observations while in contrast, predictions using the Nielsen (1992) equation are a factor of two higher.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".