Subsurface Porewater Flow Accelerates Talik Development Under the Alaska Highway, Yukon: A Prelude to Road Collapse and Final Permafrost Thaw?
Bibliographic record
Abstract
Abstract The presence of taliks (perennially unfrozen zones in permafrost areas) adversely affects the thermal stability of infrastructure in cold regions, including roads. The role of heat advection on talik development and feedback on permafrost degradation has not been quantified methodically in this context. We incorporate a surface energy balance model into a coupled groundwater flow and energy transport numerical model (SUTRA‐ice). The model, calibrated with long‐term observations (1997–2018 on the Alaska Highway), is used to investigate and quantify the role of heat advection on talik initiation and development under a road embankment. Over the 25‐year simulation period, the new model is driven by reconstructed meteorological data and has a good agreement with near surface soil temperatures. The model successfully reproduces the increasing depth to the permafrost table (mean absolute error <0.2 m), and talik development. The results demonstrate that heat advection provides an additional energy source that expedites the rate of permafrost thaw and roughly doubles the rate of permafrost table deepening, compared to purely conductive thawing. Talik initially formed and grew over time under the combined effect of water flow, snow insulation, road construction and climate warming. Talik formation creates a new thermal state under the road embankment, resulting in acceleration of underlying permafrost degradation, due to the positive feedback of heat accumulation created by trapped unfrozen water. In a changing climate, mobile water flow will play a more important role in permafrost thaw and talik development under road embankments, and is likely to significantly increase maintenance costs and reduce the long‐term stability of the infrastructure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".