Review Of Stormwater Management In Ontario And A Case Study On The Etobicoke Exfiltration System
Bibliographic record
Abstract
Stormwater management has transformed throughout the decades with the purpose of maintaining the pre-development hydrological cycle to protect humans and the environment. Despite the progress, Ontario’s water bodies have continued to degrade. This research discusses and recommends three essential modifications to stormwater management to increase environmental and human protection. These include: 1) management based on the four seasons, 2) management based on regional conditions such as local climate and receiving water body characteristics, and 3) updating current stormwater management objectives to provide detailed direction. The Etobicoke Exfiltration System is used as a case study to demonstrate some aspects of the proposed stormwater management modifications and to show the benefits of addressing the five stormwater characteristics (volume, peak flow, quality, duration, frequency) throughout the year. Modelling its performance under 2 to 100 year Chicago storms and use of previous EES studies show the wide range of objectives it can achieve. Future stormwater designs should look to the EES as insight into how stormwater can be properly managed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".