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Record W1975170535 · doi:10.4296/cwrj2504343

Prediction of Pollutant Load in Stormwater Runoff from an Urban Residential Area

2000· article· en· W1975170535 on OpenAlexvenueaboutno aff
David W. LeBoutillier, James A. Kells, Gordon Putz

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsSurface runoffEnvironmental sciencePollutantStormwaterFirst flushHydrology (agriculture)Drainage basinUrban runoffWater qualityTotal suspended solidsNonpoint source pollutionEnvironmental engineeringGeographyWastewaterChemical oxygen demandEcologyGeology

Abstract

fetched live from OpenAlex

The pollutant load in urban stormwater runoff has become a major concern with respect to the impact on the water quality of receiving streams and detention ponds. Common pollutants of concern in the runoff are suspended solids and nutrients (nitrogen and phosphorus). Past research efforts have attempted to use pollutant build-up equations to predict the increase in pollutant mass available for wash-off within a catchment. The total pollutant mass is generally expressed as a linear or exponential function of time between runoff events. Such functions are generally coupled with a wash-off equation, which predicts the varying extent to which a specific pollutant is transported out of the catchment during a runoff event. These simple models are not completely adequate, but they provide a reasonable starting point for further investigation into stormwater pollutant load generated from an urban residential catchment.In this paper, statistical models are proposed to predict the total mass of specific pollutants removed with stormwater runoff from an urban residential catchment. The statistical models are based upon analysis of data collected during an on-going research program in Saskatoon, Saskatchewan. In this program, a small, primarily-residential urban catchment was monitored and sampled for six summers (1994–1999). Stormwater outflow from the catchment and rainfall intensity at three locations in and around the catchment were recorded during rainfall events. Also, during each event, a timed series of water samples was withdrawn from the catchment outflow and analyzed for suspended solids and nutrient concentrations.Various input parameters to the statistical models were tested to assess their significance. These parameters included variables describing the precipitation event generating the runoff, the antecedent precipitation event, and the dry period between current and antecedent events. The proposed models were formulated with the most significant input parameters and calibrated using the existing data set. At present, individual water quality parameter models result in prediction errors ranging from 2.3–88% of the observed pollutant load.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.182
Teacher spread0.168 · 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 designNot applicable
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

Citations31
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Water Resources Journal / Revue canadienne des ressources hydriquesSame topicUrban Stormwater Management SolutionsFrench-language works237,207