A comparison of one-dimensional methods for estimating discharge capacity of straight compound channels
Bibliographic record
Abstract
A series of experiments was carried out in a two-stage flume having a smooth main channel and smooth or rough floodplains to investigate the reliability and performance of four different one-dimensional methods for computing the discharge capacity of compound channels, namely, the single-channel method (SCM), the divided-channel method (DCM), the exchange discharge method (EDM), and the Ackers method (AM). Additional data from fixed- and mobile-bed compound laboratory channels with smooth and roughened floodplains and of a prototype compound river channel were also used in the computations. The boundary roughness and scale effects associated with the performance of the four methods are also examined. The results show that the EDM and the AM are able to simulate the measured discharge values more accurately than those of the traditional methods, namely, the DCM and the SCM. Although the error in discharge estimation produced by both the AM and the EDM was generally lower than 10% for both smooth and fixed boundaries, it increased up to 20% for mobile boundaries. Overall, the average relative error in discharge estimations using the AM and the EDM was about 5.4% and 7.1%, respectively, with a standard deviation of 6.7% and 6.8%, respectively. Key words: compound channel flow, stage-discharge relationship, one-dimensional methods.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".