The Impact of Ice Sheet Geometry on Meltwater Ingress and Reactive Solute Transport in Sedimentary Basins
Bibliographic record
Abstract
Abstract We investigate the effect of ice sheet geometry on groundwater flow patterns and meltwater ingress in a hypothetical sedimentary basin. The simulation results indicate that meltwater ingress is much greater in 3D domains with a relatively narrow ice sheet extent compared to a wide ice sheet, or a simplified 2D model. In high permeability units (HPUs), the simulated meltwater penetration depth can reach up to 750 m in 3D domains compared to 400 m in a comparable 2D domain. In low permeability units (LPUs), very limited meltwater penetration occurs, indicating that ice sheet geometry and model dimensionality do not substantially affect water flow in these units. A conservative tracer, with a source located at a depth of 500 m in both HPUs and LPUs, illustrates that solutes can be transported to greater depths in HPUs for a narrow ice lobe scenario, in comparison to a wide ice sheet or the 2D approach. Tracer transport in LPUs is unaffected by ice sheet geometry. Similarly, simulation results indicate that the ingress of dissolved oxygen (O2) into HPUs is most substantial below a narrow ice lobe, while O2 ingress into LPUs is not affected by ice sheet geometry. The numerical experiments indicate that 3D analysis will give more comprehensive results for flow patterns and reactive solute transport subjected to glaciation/deglaciation cycles in the case of a narrow ice lobe, but also suggest that a 2D approach might provide an adequate representation for the case of a relatively wide ice sheet.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".