Increased hydropower potential at Niagara: a scenario-based analysis
Bibliographic record
Abstract
Research often ranges from incremental innovations of existing approaches to the development of novel methodologies. The current study seeks to combine both paradigms through consideration of a legacy hydro system. Stretched along the border between Canada and the US and regulated by a 1950 treaty, the Niagara River currently provides almost 5000 MW of renewable power. This paper develops a HEC-ResSim representation of the existing reservoir (power) system and uses this model to explore a variety of possible future scenarios. These possibilities will ultimately include considering the sensitivity of the system to climate change, reducing tourist flows, and exploring using additional storage to augment operational flows, although the current paper particularly details the scenario involving increased power diversion by somewhat relaxing treaty restrictions. Such an arrangement is shown to potentially increase monthly hydro discharges by 16% relative to the current baseline, and thus to permit an additional 1050 GWh of annual generation on the Canadian side alone. This preliminary exploratory study simply evaluates the potential hydro benefits by assessing the interplay between various system constraints if treaty provisions were ever to be reconsidered, and thus sets the stage for considering a variety of other scenarios.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".