Reference Time of Concentration Estimation for Ungauged Catchments
Why this work is in the frame
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Bibliographic record
Abstract
Accurate modelling of flood flow hydrographs in ungauged catchments is a challenging task due to large errors in the estimation of its response time using existing empirical equations. The time of concentration (Tc) is a key catchment response time parameter needed for forecasting of the peak discharge rate and the timing of the flood event. At least eight different definitions have been presented in the literature for the time of concentration. In this study, a new definition of “Reference Tc” is presented along with a practical procedure for its estimation using readily available basin catchment characteristic parameters with the aim of standardizing this key parameter for practitioners. Nine different empirical models were calibrated and tested on nine catchments of the Credit River watershed, Ontario, Canada to determine which method would provide the most accurate prediction of the Reference Tc. The NRCS velocity method (1986) proved once again to be the most reliable and an accurate method. This study shows that the main reason for the higher accuracy of the NRCS velocity method predictions compared to the empirical equations is attributed to the inclusion of the Manning's roughness coefficient.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| 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 | 0.001 |
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 it