Influence of permafrost distribution on groundwater flow in the context of climate‐driven permafrost thaw: Example from Yukon Flats Basin, Alaska, United States
Bibliographic record
Abstract
Understanding the role of permafrost in controlling groundwater flow paths and fluxes is central in studies aimed at assessing potential climate change impacts on vegetation, species habitat, biogeochemical cycling, and biodiversity. Recent field studies in interior Alaska show evidence of hydrologic changes hypothesized to result from permafrost degradation. This study assesses the hydrologic control exerted by permafrost, elucidates modes of regional groundwater flow for various spatial permafrost patterns, and evaluates potential hydrologic consequences of permafrost degradation. The Yukon Flats Basin (YFB), a large (118,340 km2) subbasin within the Yukon River Basin, provides the basis for this investigation. Model simulations that represent an assumed permafrost thaw sequence reveal the following trends with decreasing permafrost coverage: (1) increased groundwater discharge to rivers, consistent with historical trends in base flow observations in the Yukon River Basin, (2) potential for increased overall groundwater flux, (3) increased spatial extent of groundwater discharge in lowlands, and (4) decreased proportion of suprapermafrost (shallow) groundwater contribution to total base flow. These trends directly affect the chemical composition and residence time of riverine exports, the state of groundwater‐influenced lakes and wetlands, seasonal river‐ice thickness, and stream temperatures. Presently, the YFB is coarsely mapped as spanning the continuous‐discontinuous permafrost transition that model analysis shows to be a critical threshold; thus, the YFB may be on the verge of major hydrologic change should the current permafrost extent decrease. This possibility underscores the need for improved characterization of permafrost and other hydrogeologic information in the region via geophysical techniques, remote sensing, and ground‐based observations.
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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 | 0.000 |
| 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 | 0.000 |
| 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".