Modelling of groundwater age under variable permafrost and environmental conditions
Bibliographic record
Abstract
Groundwater discharge age is a useful metric for retracing flowpaths, and is essential to estimate an aquifer’s renewability and vulnerability. As permafrost thaws in cold regions, supra-permafrost aquifers will expand, which will cause new pathways to develop and potentially alter the spatiotemporal distribution, quantity, and age of groundwater discharge. While numerous modelling studies have analysed the shift in groundwater discharge magnitude and patterns in permafrost regions, the associated changes to groundwater age have been largely overlooked. Using heat-transfer and solute-transport numerical models for cold regions, we recreated various archetypical conceptual models of permafrost-groundwater distributions. The object is to use different environmental conditions to evaluate which setting could result in a pronounced shift in groundwater discharge age and to identify the most significant parameters driving alterations to groundwater discharge age. In general, the results show that groundwater discharge is expected to become gradually older with permafrost thaw. Continuous permafrost settings exhibit very small changes in groundwater age until the lowering permafrost table allows for the formation of a supra-permafrost talik. The biggest shift occurs when taliks evolve from closed to open by connecting supra- and sub-permafrost aquifers. These insights are useful to determine the potential vulnerability and renewability of newly formed aquifers in permafrost settings.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".