Promoting Sustainable Ice-Jam Flood Management along the Peace River and Peace-Athabasca Delta
Bibliographic record
Abstract
The regulation of rivers has always been a controversial issue, with potential benefits but also environmental impacts. In western Canada, the construction of W.A.C. Bennett Dam in the headwaters of the Peace River has raised concerns over the ecological health of the Peace-Athabasca Delta (PAD), a socioeconomically and ecologically important delta with national and international significance. The major concern is the reduced frequency of ice-jam floods, which are particularly effective in replenishing the high-elevation basins of the PAD. Previous studies have suggested that releasing water at opportune times from the dam could promote ice-jam flooding of the delta; however, ice-jam flood events can also be severe and devastating to riverside communities and economies. Thus, a critical and challenging question is how to promote flooding in the downstream deltaic ecosystem where it is essential without necessarily increasing the flood risk in upstream communities of the Peace River. This study reviews previous approaches and explores possible reservoir operation schemes with an integrated hydrologic and hydraulic river ice modeling framework to minimize flood risk and maximize flood potential at desired locations. It is demonstrated that by increasing reservoir release in the breakup period, it is possible to increase the likelihood of ice-jam flooding in the PAD without necessarily causing ice-jam floods in the upstream communities. However, the timing of the flow release, taking into account the receding ice front and local hydrometeorological conditions, is critical.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".