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Record W1974179980 · doi:10.2166/wcc.2014.121

Continuous simulations of urban stormwater runoff and total suspended solids loads: influence of varying climatic inputs and catchment imperviousness

2014· article· en· W1974179980 on OpenAlexaff
Matthias Borris, Anna‐Maria Gustafsson, Jiří Maršálek, Maria Viklander

Bibliographic record

VenueJournal of Water and Climate Change · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsSurface runoffEnvironmental scienceStormwaterHydrology (agriculture)Total suspended solidsClimate changeDrainage basinSuspended solidsEnvironmental engineeringGeologyGeographyEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Potential implications of climate change for future stormwater management were addressed by undertaking continuous simulations of runoff and total suspended solids (TSS) loads for three urban catchments, with imperviousness varying from 23 to 63%, which were exposed to five rainfall regimes during the snow-free part of the year: the current climate and four climate change scenarios projecting higher rainfalls. Simulated runoff volumes increased in all the future scenarios, particularly in the sub-arctic climate and the fixed uplift scenario (plus20) indicating appreciable rainfall increases. Simulated runoff volumes increased depending on the projected increases in rainfall and increasing runoff contributions from pervious areas when more intense future rainfalls exceeded hydrologic abstractions. The increased runoff volumes then contributed higher TSS loads, which were highly variable for the rainfall regimes tested. In cold climate regions, residues of solids from winter road maintenance may contribute to high initial accumulations of TSS on the catchment surface and high washed off loads. In general, the study suggests that intermediate design-life stormwater management facilities require flexible design allowing for future step-wise adaptation by gradually increasing design capacities and modifying treatment trains.

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)0.000
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 score0.079
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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