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Record W2321776470 · doi:10.2166/wcc.2012.125

Trends in rainfall intensity for stormwater designs in Ontario

2012· article· en· W2321776470 on OpenAlexafffundabout
Božica Vasiljević, Edward A. McBean, Bahram Gharabaghi

Bibliographic record

VenueJournal of Water and Climate Change · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStormwaterStormEnvironmental scienceStormwater managementHydrology (agriculture)MeteorologyIntensity (physics)Surface runoffClimatologyGeographyGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.102
GPT teacher head0.264
Teacher spread0.162 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2012
Admission routes3
Has abstractyes

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