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Record W1972175039 · doi:10.4296/cwrj3201059

Anatomy of an Extreme Event: The July 14–15, 2004 Peterborough Rainstorm

2007· article· en· W1972175039 on OpenAlexvenueaboutno aff
J. M. Buttle, Peter M. Lafleur

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Drought Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryEvent (particle physics)ArchaeologyGeography

Abstract

fetched live from OpenAlex

The July 14−15, 2004 rainstorm in Peterborough, Ontario, produced the largest 24 hour total rainfall depth (>220 mm) on record for southern Ontario. The storm was localized over the city for much of this period and rainfall depths and peak rainfall intensities dropped markedly with distance from the city. Peak intensity for 0.5 hour duration at the Trent Weather Station (TWS) in the north end of the city was 93 mm h−1, while peak intensity for one hour duration was 87 mm h−1. Even greater intensities may have occurred in other parts of the city. These intensities exceeded the corresponding 100−year return period values (81 and 53 mm h−1, respectively) estimated from the 1971 to 2002 record at the Peterborough Airport (PA) station, southwest of the city. Another critical characteristic of the July 14−15, 2004 storm was the distinctive shape of its intensity−duration−frequency curve relative to that for the PA. The TWS intensities for the July 14−15, 2004 storm showed a more protracted decline with increasing duration compared to the PA 100−year return period values. The storm produced the largest instantaneous peak flow on record for Jackson Creek, which flows through Peterborough's downtown area. Peak rainfall intensities exceeded the infiltration capacities of artificial surfaces as well as many nominally−pervious surfaces in Peterborough and the ensuing surface runoff contributed to widespread flooding in the city. These results strongly suggest that such storm properties, and their influence on surface runoff generation in urban areas, need to be considered when planning engineering structures such as storm sewer networks and storm water retention ponds in the Peterborough region.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.874
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.217
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2007
Admission routes2
Has abstractyes

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