A three-dimensional groundwater flow simulation of Granger Basin, Yukon, Canada
Bibliographic record
Abstract
Groundwater flow and exfiltration (discharge) in Arctic and Subarctic mountain regimes is poorly understood yet plays an important role in areas underlain by continuous and discontinuous permafrost. Permafrost, ground with a perennial temperature below 0°C, acts as an impermeable barrier to groundwater flow and influences hydrogeologic connectivity and storage. The Arctic is warming at twice the global average rate, leading to rapid permafrost thaw with unclear consequences for groundwater systems. In this study, we develop a numerical groundwater model of the Granger Basin, Yukon, to further our understanding of the influence of permafrost and thaw on groundwater flow in basins impacted by climate change. Granger Basin is a 7.6 km2 headwater catchment located within the Wolf Creek Research Basin, Yukon, Canada. It is representative of a subarctic-continental mountain environment with already observable climate change impacts. To date, there has been limited hydrogeology monitoring or numerical modeling at this site. To investigate cryohydrogeologic processes within the basin, we integrate existing field data, including 30 years of hydrometeorological records and geophysical data into a three-dimensional numerical model with saturated-unsaturated groundwater flow. We use the SUTRA-ice numerical model that couples groundwater flow and energy transport with dynamic freeze-thaw processes. The model incorporates both time-dependent thermal and hydrological surface boundary conditions and is used parametrically to understand the generation of groundwater baseflow in this setting. We will present initial results that will evaluate the impact of different hydrogeologic properties on the generation of groundwater streamflow in Wolf Creek, how permafrost in transition affects the groundwater system, and provide the framework for future research directions.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".