Receiving Water Response to a Master Plan for Wet Weather Flow Management Developed for the City of Toronto
Bibliographic record
Abstract
Abstract The City of Toronto has development a Wet Weather Flow Management Master Plan incorporating a new philosophy in wet weather flow management where rainwater is recognized as a resource. Wet weather flows are to be managed on a watershed basis, and a hierarchical approach to wet weather flow management is to be used, starting with at source, followed by conveyance and finally end-of-pipe control measures. The study area extended across the City of Toronto, encompassing six major watersheds and the waterfront. The Plan development followed the planning principles of Ontario's Environmental Assessment Act and incorporated broad public and agency consultation. A series of 13 objectives was identified and grouped into four major categories: water quality, water quantity, natural areas and wildlife, and sewer system. An innovative approach was used which integrated hydrologic, hydraulic and water quality predictions from land-based, watershed and lake models, respectively, to assess the effectiveness of various strategies. The receiving water response indicated that source controls and conveyance controls were insufficient to achieve the receiving water objectives of the Plan. This was only possible through the implementation of a comprehensive set of measures consisting of: source controls, conveyance controls, end-of-pipe controls, basement flooding protection works, stream restoration works, shoreline management, enhanced municipal operations and an enhanced public education and community outreach program. Overall benefits expected through the Plan include: swimmable waterfront beaches, control of combined sewer overflows in compliance with legislative requirements, basement flooding protection, protection of the City's infrastructure from stream erosion, restoration of degraded local streams and aquatic habitat and the reduction of algal growth along the waterfront, and improved stream water quality in area watercourses. The cost of the Plan over the 25 years is estimated to be $1.047 billion with an additional $233 million in operational and maintenance costs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".