Toward More Resilient Urban Stormwater Management Systems—Bridging the Gap From Theory to Implementation
Bibliographic record
Abstract
Many publications include references to reliability, risk and resilience, specifically within the context of climate change and rapid urbanization. However, there is a considerable gap between theory and actual implementation by drainage professionals. As such, most drainage professionals will not have an appreciation of a drainage system's response to events in excess of its original design event. This gap is compounded by the desire toward evaluating components such as “critical infrastructure” for events significantly more severe than ever contemplated. This paper, reflecting the combined wisdom and thoughts of various drainage professionals across Canada involved with the creation of the Canadian drainage standards (CSA W204 and W210), provides a treatise of risk and resilience based on the application of the dual drainage principle. It provides a discussion of key factors including climate change; densification; shape, intensity, duration and spatial extent of storm events, as a function of the normalized capacity or drain down/emptying time of the various components of the drainage system. Commentaries are offered, highlighting the role of appropriate setbacks and freeboard, and focusing on those aspects that have historically been ignored. Avenues to increase system resilience are presented including an evolution in passive and active flow controls, the potential beneficial role of natural systems and low impact development practices as a function of system sensitivity, discussing how options may vary across Canada.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".