Storm Drainage System Modeling of Edmonton's Clareview and Pilot Sound Storm Basins
Bibliographic record
Abstract
The City of Edmonton operates and maintains over 5,000 km of sewer pipes.The collection system is made up of about 42% storm sewers, 39% sanitary sewers and 19% combined sewers.Storm drainage is captured and discharged to the North Saskatchewan River.Flows from the combined sewer area and the sanitary sewerage system are collected and discharged to the Gold Bar Wastewater Treatment Plant.This chapter presents the development and applications of the Clareview and Pilot Sound Storm Drainage Model.The study area is approximately 1350 ha and located on the north east side of the City servicing a population of about 18,000 mainly residential with portions of commercial, community services and industrial.A storm model was developed using DHI's Mike Urban and Mike Flood to represent approximately 69 km of 1,200 pipes and 370 sub-basins within the study boundary.Pipe diameters vary from 200 mm to 2250 mm.The model also includes a pump station, five stormwater detention facilities and a number of flow diversion control structures.The main components of the study include development of model parameters and the drainage network, calibration and verification of the model, assessment of the capacity constraints of the existing system under various storm events, evaluation of the performance of the stormwater detention facilities under severe storm 177
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".