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Record W2123007525 · doi:10.1002/hyp.10250

Hydrologic changes resulting from urban cover in seasonally snow‐covered catchments

2014· article· en· W2123007525 on OpenAlexafffundabout
M. Catherine Eimers, Ethan C. McDonald

Bibliographic record

VenueHydrological Processes · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsImpervious surfaceUrban streamEnvironmental scienceSTREAMSBaseflowHydrology (agriculture)SnowmeltStreamflowLand coverHydrographSpring (device)Physical geographySnowGeographyLand useDrainage basinEcologyGeologyMeteorology

Abstract

fetched live from OpenAlex

Abstract There are few multibasin analyses of the effects of urban land cover on seasonal stream flow patterns within northern watersheds where winter snow cover is the norm. In this study, the effects of urban cover on stream flow were evaluated at nine catchments in southern Ontario, Canada, which vary greatly in urban impervious cover (1–84%) but cluster into two groups having ≥54% urban impervious area (‘urban’) and ≤11% impervious cover (‘rural’), respectively. Annual and seasonal run‐off totals (millimetres) were similar between the rural and urban groups and were relatively insensitive to urban cover. Instead, urban streams had significantly greater high flow frequency, flow variability and quickflow and lower baseflow compared with rural streams. Furthermore, differences in high flow frequency between urban and rural stream groups were largest in the summer and fall and less extreme in the winter and spring, perhaps because of the homogenizing effect of winter snow cover, frozen ground and spring melt on surface imperviousness. Although the clear clustering of streams into urban and rural groups precluded the identification of a threshold above which urban cover is the primary cause of flow differences, relatively high extreme flow frequency and flow variability in the two most urbanized of the rural streams (10–11% impervious) suggest that it may lie close to this range. Furthermore, whereas total run‐off volumes were not affected by urban cover, increases in stream flashiness and a greater frequency of high flow events particularly during the summer and fall may negatively impact stream biota and favour the transfer of surface‐deposited pollutants to urban streams. Copyright © 2014 John Wiley & Sons, Ltd.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.017
GPT teacher head0.217
Teacher spread0.200 · 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; both teacher heads agree on what is shown here.

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

Citations20
Published2014
Admission routes3
Has abstractyes

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