Wet Weather Performance of an Extensive Vegetated Roof in Waterloo, Ontario
Bibliographic record
Abstract
Vegetated roof technologies are increasingly being adopted as treatment measures to mitigate the effects of urban stormwater. A mass balance approach was used to assess the wet weather performance of a vegetated roof on the top of city hall in Waterloo, Ontario. Vegetated and control roof sections were instrumented to measure precipitation inputs, storage and outflow for 18 storm events from June to October, 2006. Concentrations of suspended solids (SS), total phosphorus (TP), soluble reactive phosphorus (SRP), copper (Cu), zinc (Zn), chromium (Cr) and cadmium (Cd) in precipitation and roof (vegetated and control) runoff were measured. A total of 155.6 mm of rain fell during the study period. The vegetated roof retained 64.5 mm (41.5%) of the total rainfall while the control roof retained ~ 5.1 mm (3.3 %). For individual rain events, the vegetated roof retained an average of 3.5 mm (47.6 %) while the control roof retained ~ 0.3 mm (4.7 %). Water retention varied with storm size, season and was influenced by wetting history. The vegetated roof retained 80.6 % of precipitation for light storm events (≤ 3.5 mm) and 34.9 % for large storm events (> 3.5 mm). The control roof retained 7.6 % light storm events and 3.7 % for large storm events. Water quality from the vegetated roof did not show significant improvement as only Zn concentrations in runoff from the vegetated roof were significantly lower than that measured in runoff from the control roof. Concentrations of SS, Cu, Cr and Cd in vegetated roof runoff were relative to concentrations in rainfall and control roof runoff and TP and SRP concentrations were significantly higher than that in rainfall or control roof runoff. Results gained from this study may assist people in planning and stormwater management by providing insight into the monitoring, development and application of new stormwater controls.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".