Overview of water level, discharge and ice in the St. Lawrence Seaway at Montreal
Bibliographic record
Abstract
Unlike in most other countries, rivers in Canada freeze during the colder months of the year. Hence, in addition to flooding events in open water, which are a challenge on their own, those involving ice introduce an additional set of issues which are also difficult to foresee and prepare against, given the acknowledged complexity of river ice dynamics. The purpose of this report is to examine the influence of surface ice on water levels in the St. Lawrence River, with the premise that an improved understanding of related phenomena would ultimately increase the reliability of the well-known stage-discharge relationships in winter conditions and provide additional insights into floods induced by ice. Fundamental to any endeavor aimed at monitoring water levels are basic principles in hydrology and hydraulics, including the various field methods used to gather these data – these are summarized. The basis for the relationship between stage and discharge is the Manning formulation. When ice is present, however, that relationship is no longer reliable. Instead, the presence of ice can lead to very high-water levels at relatively low discharge, which is caused by channel constriction by ice keels below the water surface. Lake St. Louis, a river segment along the St. Lawrence Seaway next to Montreal, is the target area for a site-specific analysis presented in this report. Historical stage and discharge data for up to 50 years were downloaded from ECCC’s website – these were generated at two hydrological stations: Pointe-Claire and Lasalle. Indirect evidence of the influence of ice on stage is indicated by the difference in daily water level patterns: they fluctuate more in the winter than in the summer. Discharge, which is derived from water levels, is also more stable in the summer than in the winter (bearing in mind it is considered unreliable for icy conditions). A full-ice cover is associated with low water levels, which may be caused by non-uniform flow, leading to a variation of water depths in the flow direction observed between the two stations. This is consistent with observed discrepancies in water levels at the stations. Additional insights could be obtained with more detailed information about the ice cover and its dynamic behavior, as well as about discharge from the Ottawa River and that resulting from dam operations.
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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 | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".