Bibliographic record
Abstract
3-D Hydrodynamic Modelling of Lower Fraser River Shaheli Masoom and Li Gu Environmental Management and Quality Control Division, Liquid Waste Services Department, Metro Vancouver, Burnaby B.C., Canada Email: shaheli.masoom@metrovancouver.org; li.gu@metrovancouver.org Abstract Lower Fraser River, the largest fresh water inflow into the Salish Sea, receives discharges from the urban area of the Metro Vancouver region, along with treated effluent from three of Metro Vancouver Regional District’s (MVRD) wastewater treatment plants. The complex dynamics of this estuarine river plays a crucial role in the fate and effect of these liquid discharges. In particular, the mixing of fresh river water with dense saline ocean water results in flow stratification and a dynamic salt wedge, necessitating a three dimensional computational modeling approach to predict the fate and effect of treatment plant effluent and emergency sewer overflow discharges into the river. This paper describes the development of a three dimensional (3-D) hydrodynamic and transport model for the Lower Fraser River, using Danish Hydraulic Institute’s MIKE3 FM software. The domain extends from Mission to Sand Head with about 30,000 flexible mesh elements horizontally with refined meshes in zones of interest. A combination of sigma and z-layer is used for vertical discretization. The model was calibrated and validated successfully using measurements of water level, buoy measured current-salinity and river discharges from ADCP transects. For all the calibration and validation runs, the predicted flow split of 12-13% to North Arm located at Fraser bifurcation was well within the published values of 10-15%. The preliminary model results provide an improved understanding of the salt wedge dynamics with variable tide and river conditions. The prediction of tracer dye (Rhodamine) transport from Annacis Island Wastewater Treatment Plant indicates that the plume is well mixed vertically not far downstream from the edge of the initial dilution zone and has a tendency to move in a narrow band hugging the north shore of the river channel, consistent with previous field observations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".