A comprehensive method to estimate flood levels of rivers subject to ice jams: A case study of the Chaudière River, Québec, Canada
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The main difference between an open-water (regular) flood and an ice jam flood is that it is normally the whole river length that is overtopped whereas an ice jam flood is localized to where the jam is located. Comparatively, the regular flood analysis can use the value of the extreme discharge as the main input parameter for a long river section, an ice jam flood needs to account for the probability of jams of various lengths and intensities occurring at specific locations under significantly variable discharges while having several mechanical ice parameters to be considered. Through the case study of the Chaudière River, the methodology presented in this paper demonstrates how to statistically characterize four significant inputs (jam location, jam length, jam properties and river discharge during jam event) into the widely used numerical river water model (HEC-RAS) and how Monte–Carlo simulations are generated to estimate probable ice jam floods along a whole river reach. The purpose of this article is to propose a robust methodology through a case study and asses the sensitivity that historical and mechanical parameters have as to why specific locations along the reach have higher 1:100 AEP ice-induced water levels as to 1:100 AEP open-water levels.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it