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Record W2135889800 · doi:10.2166/wqrj.2004.048

A Modelling Analysis of Urban Stormwater Flow Regimes and their Implication for Stream Erosion

2004· article· en· W2135889800 on OpenAlexaffabout
Celia Fan, James Li

Bibliographic record

VenueWater Quality Research Journal · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStormwaterUrbanizationWatershedHydrology (agriculture)Environmental scienceErosionDetention basinUrban streamSurface runoffFlow (mathematics)StreamflowDrainage basinWater qualityGeographyGeologyGeomorphologyComputer scienceEcologyGeotechnical engineeringMathematicsCartography

Abstract

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Abstract Stream erosion is a major issue in stormwater management. The objectives of this research are to investigate by means of computer modelling: (a) the flow-duration characteristics of a receiving stream before and after urbanization; (b) the implication of flow regime changes on stream erosion potential with and without control measures (e.g., extended detention basins and source control); and (c) the maximum degree of urbanization, for which stream erosion may be unavoidable regardless of the stormwater control measures applied. The U.S. EPA Stormwater Management Model was used in the analysis of flowduration characteristics of a small northern Ontario watershed. It was found that flow-duration characteristics of the stream could change significantly after urbanization. Although no stream erosion was modelled in this investigation, the change in flow regimes after urbanization may indicate potential stream bed and/or channel erosion. Extended detention basins with short detention times (24-h) could control flow-duration characteristics at low flow rates better than those with long detention times (48-h). Both extended detention basins and source control measures should be applied in order to bring the flow duration curve after urbanization back to its original position. If the watershed were to be urbanized beyond 40% of imperviousness, it may not be possible to bring the flow duration curve back to its original position in spite of the various source control measures and detention basins used. The optimal location of detention ponds for erosion control depends upon the range of flows, which control the stability of the stream.

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)0.003
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.350
Teacher spread0.268 · 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 designBench or experimental
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

Citations9
Published2004
Admission routes2
Has abstractyes

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