Operational Monitoring of Urban Stormwater Management Facilities and Receiving Subwatersheds in Richmond Hill, Ontario
Bibliographic record
Abstract
Abstract Untreated stormwater discharge has been found to have major impacts on urban watercourses. Despite the acknowledgement of the importance of adopting broader-scale approaches to managing stormwater, there is limited information describing the subwatershed benefits of implementing numerous best management practices (BMPs). Operational monitoring of stormwater management facilities (SWMFs) and streams in three subwatersheds undergoing urbanization was undertaken over a five-year period to measure potential changes in suspended solids concentrations, hydrology and temperature. SWMFs at construction sites had elevated total suspended solids (TSS) discharges relative to facilities in stable catchments, but reduced TSS discharges in comparison to uncontrolled construction sites. The discharge from single facilities was found to have the potential to increase downstream watercourse TSS concentrations in headwater areas, but increases were often not detectable further downstream. TSS discharges from SWMFs in stable catchments were similar to published ranges, and were a useful tool to identify facilities that were not functioning as designed. Based upon the current subwatershed imperviousness levels, water quality impacts from cumulative SWMF discharges appear to be less likely to be significant than some other factors, such as the changes in the subwatershed hydrological response. No increase in peakflow or duration of midbankfull flow for the 25-mm and 2-year storm event and no trend in baseflow or water temperature were detectable over the study period, despite the increase in imperviousness due to watershed urbanization. The findings from this operational monitoring study suggest that implementation of BMPs may help to mitigate urban impacts at the subwatershed level.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".