Trends in rainfall intensity for stormwater designs in Ontario
Bibliographic record
Abstract
The intensities of short-duration rainfall events are fundamental inputs to the design of stormwater management infrastructure. However, since stormwater infrastructure must function as designed for many decades, if there are long-term trends in rainfall intensities, design storms need to be modified. Evidence demonstrates, using data from 13 rain gauges in Ontario, that storm intensities relevant to urban stormwater (5 year) appear to have changed over the last 30 years. The results show, for example, statistical significance at 80% confidence that the 5-year storm has increased, and 85% that the 2-year storm has increased, for the 1 h storm in Waterloo, using partial duration series (PDS) data. The PDS data indicate intensities are increasing at a rate of 1–3% per year. Results show, for example, that a 5-year recurrence storm for PDS for the period 1970–1984 is now very close in magnitude to a 2-year recurrence storm for the period 1985–2003 for Waterloo, Ontario. The implications for a case study demonstrate that 5 out of 12 storm sewer pipes in a subdivision would need to be increased in diameter to obtain the same level of stormwater performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".