Numerical modelling of permafrost-impacted groundwater flow systems in the context of a deep geological repository
Bibliographic record
Abstract
Numerical modelling of a hypothetical geosphere setting in the Canadian Shield is employed to assess the impact of permafrost growth and decay cycles on groundwater flow and thermal conditions relevant to the near and far-field environment of a deep geological repository (DGR).This study aims to examine how transient events linked to long-term climate change and glacial cycles may affect the evolution of a deep groundwater flow system.Simplified conceptual models on relevant spatial and time scales are developed in part from field data and insights gained from a northern research site located near Umiujaq, in Nunavik, Quebec, Canada.Future climate transitions are based on the past 1 million years of air temperature data, which are considered an analogue for future changes.Simulated processes include coupled groundwater flow, heat and mass (brine) transport, with freeze/thaw, latent heat and ice-fraction dependent relative permeability.Initial simulations have shown how permafrost cycles can affect deep groundwater pathways, leading to the formation of a transient barrier that restricts groundwater flow and brine transport between the geosphere and biosphere, potentially leading to longer flow and transport pathways and increased groundwater residence times.However, the formation of below-lake taliks lakes can also maintain hydraulic connections between the geosphere and biosphere, creating transient groundwater pathways even during glacial periods.The findings of this research will provide valuable insights into the impact of future glaciations on the long-term safety of DGRs.1
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".