Regional Sustainability of the Chateauguay River Aquifers
Bibliographic record
Abstract
A steady increase in groundwater use in the Chateauguay River watershed has led to potential conflicts between various groundwater users. This study summarizes the quantity and sustainability estimations of the groundwater resources within this basin. Regional sustainability is defined with simulated drawdowns from uniform withdrawal scenarios compared to water levels obtained without any withdrawal. Three sustainable conditions are defined: sustainable withdrawal, withdrawal with increased drawdown, and unsustainable withdrawal. The current withdrawal rate of 34 Mm3/yr results in a median drawdown of 1.5 m, compared to pre-development conditions. This drawdown is well within the range considered sustainable, an indication that regional aquifers are not currently overexploited. A hypothetical pumping rate of 48 Mm3/yr, resulting in an average drawdown of 2.2 m, is the estimated sustainable limit. Increasing exploitation from 48 to 122 Mm3/yr would need tight control and planning. Withdrawal rates beyond 122 Mm3/yr are judged not sustainable as the regional median drawdown would exceed 8 m. The water levels in recharge areas are the most sensitive to groundwater extraction. The combination of aquifer sensitivity to recharge variations, simulated drawdown maps, and aquifer vulnerability to surface contamination reveals the most sensitive areas of the regional aquifers, areas that would need particular attention and protection by groundwater managers.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".