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Record W2949709690 · doi:10.2166/wqrj.2019.002

Numerical investigation on the impact of wind-induced hydraulics on dissolved oxygen characteristics in a shallow stormwater pond

2019· article· en· W2949709690 on OpenAlexafffund
Li-Yu Chen, Patrick M. D’Aoust, Colin D. Rennie, Alexandre J. Poulain, Frances R. Pick, Ru Wang, Robert Delatolla

Bibliographic record

VenueWater Quality Research Journal · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scienceWind speedCurrent (fluid)UpwellingWater qualityStormwaterStratification (seeds)Water columnHydraulicsFlow (mathematics)Hydrology (agriculture)Atmospheric sciencesGeologyOceanographySurface runoffMechanicsGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Stormwater ponds (SWPs) are widely utilized for flood and water quality control. Low-flow rates are common in SWPs, sometimes causing wind-driven currents to become the dominant hydrodynamic force during ice-free periods. Hence, it is essential to understand the influence of the wind-induced flow on stratification and dissolved oxygen (DO) concentrations in shallow SWPs to predict the performance and water quality of these systems. The objective of this study is to evaluate the influence of wind-driven circulation on the spatial distribution of DO in an SWP using a numerical model. A bottom-mounted acoustic Doppler current profiler (ADCP) was utilized to measure small wind-induced currents and to validate a hydrodynamic model, which suggested that a wind-dominated circulation was generated even with the moderate wind speed. Countercurrents opposite in the direction to surface wind-generated flow were also present. The DO model demonstrated that complete mixing can be produced by higher wind speed, leading to fully oxic conditions throughout the water column (7.00 mg/L DO or higher), wherein low DO water at depth was carried to the surface by upwelling circulation and was possibly replenished during the surface transportation. This sheds some light on the impact of wind-induced mixing on the water quality in shallow SWPs.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 integrity0.0000.001
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 head0.116
GPT teacher head0.349
Teacher spread0.233 · 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.

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

Citations8
Published2019
Admission routes2
Has abstractyes

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