Modelling wastewater spills and mapping areas most vulnerable to groundwater quality deterioration in northeast British Columbia
Bibliographic record
Abstract
This study utilized numerical modelling of spills and leaks of natural gas production wastewater into the shallow subsurface to identify areas most vulnerable to groundwater quality deterioration in Northeast British Columbia. Modelling was conducted using the flow and transport code TOUGH2. The models were designed to address three main factors identified from the DRASTIC method for vulnerability assessment: (1) Depth to water, (2) Impact of vadose zone, and (3) Conductivity of the aquifer materials. Models show that dense saline wastewater will migrate further and faster through highly permeable materials. Lower permeability materials attenuate the wastewater migration resulting in smaller plumes with locally higher brine concentrations. A sensitivity analysis reveals that the vadose zone permeability and depth to water table are significant controls on wastewater migration and footprint. Overall, the vulnerability in the region is relatively low, with some exceptions near river valleys, mountainous regions, and areas with shallow water tables.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".