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Record W4207058988 · doi:10.32920/16859974

Performance Modeling of Right-of-Way Stormwater LID Practices-Exfiltration System

2021· preprint· en· W4207058988 on OpenAlexaffabout
Krishna Khadka

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStormwaterSurface runoffEnvironmental scienceCombined sewerInflowLow-impact developmentHydrology (agriculture)Infiltration (HVAC)DrainageStormDrainage system (geomorphology)PopulationStormwater managementBioretentionEnvironmental engineeringMeteorologyEngineeringGeotechnical engineeringGeography

Abstract

fetched live from OpenAlex

Rapid population growth and ever-growing urbanizations are posing a significant challenge to stormwater management in urban communities. An exfiltration system (ES), one of the innovative low impact development (LID) techniques, principally similar to the Etobicoke Exfiltration System (EES), was constructed in Mosaik Glenway Homes, residential subdivision, Newmarket, as a stormwater management facility. This typical ES is the simple addition to the conventional storm sewer system, and consists of a filter fabric encased granular stone trench with embedded perforated PVC pipe beneath the storm sewer at a very gentle slope (0.5%). In order to assess the hydrologic performance of the exfiltration system (ES), the monitored ES inflow and overflow time series data were analyzed. Both continuous and event-based monitoring data analysis depicts that the ES has a significant impact on the water balance, reducing the surface runoff by 84% and achieving a substantial reduction of peak flow, thereby maintaining the contemporary stormwater management goals (post-development infiltration volume to predevelopment level). This typical ES can store up to 123 m3 of runoff volume and exfiltrates to the surrounding soils. The average ES exfiltration rate ranged from 0.76 to 1.05 mm/hr over four observed complete drainage periods (full capacity to empty), indicates that the system is draining at a much slower rate than that was assumed when designing the exfiltration system (7.7mm/hr). As a consequence, it causes the system to require a much longer period to achieve complete drainage (drawdown) than the estimated 78 hours. PCSWMM model was developed to analyze the annual water balance cycle and determine suitable alternative measures to control the ES overflow. Eight meaningful events were selected to calibrate and validate the model, most sensitive parameters such as hydraulic conductivity and imperviousness of subwatershed were calibrated to fit simulated ES inflow with observed inflow whereas orifice discharge coefficient and hydraulic conductivity of storage trench were calibrated for ES-overflow. Rainfall events larger than 24mm exceeded the storage capacity of the granular trench and caused overflow from the exfiltration system (ES2). Model results indicate that ES2 overflow could be easily avoided by diverting some amount of ES2 inflow to the underutilized upstream exfiltration system (ES1) by constructing diversion storm sewer to drain flow accumulated at manhole 5 (MH5) to manhole 4 (MH4).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.034
GPT teacher head0.239
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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