Critical review of the evolution of the design storm event concept
Bibliographic record
Abstract
A critical review of the literature and practice indicates that design storm events, which have been used in specific fields of Canadian and US engineering practice for more than 100 years, can be ascribed to six basic attributes: (a) design return period, (b) storm duration, (c) intensity–duration–frequency (idf) relations (representing a summary of historical rainfall data, with some extrapolation for longer return periods), (d) temporal distribution (design hyetograph), (e) areal reduction factor, and (f) antecedent moisture conditions. Concerns about climate change (or variability) and the need to adapt to the associated climatic conditions prompted many agencies, and particularly municipalities, to revisit the design storm event issue, particularly in connection with drainage design. It would appear that this analysis has mostly focused on a single property of design storms — idf relations and projected increases in rainfall intensities. The review concludes that the design practice would be well served by adopting a comprehensive approach considering all design storm event characteristics and their sensitivity to climate change and inherent uncertainties in the existing idf relations as well as hydraulic design of sewer networks.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".