Impact of heat advection on the thermal regime of roads built on permafrost
Bibliographic record
Abstract
Abstract In northern regions, transportation infrastructure can experience severe structural damages due to permafrost degradation. Water infiltration and subsurface water flow under an embankment affect the energy balance of roadways and underlying permafrost. However, the quantification of the processes controlling these changes and a detailed investigation of their thermal impacts remain largely unknown due to a lack of available long‐term embankment temperature data in permafrost regions. Here, we report observations of heat advection linked to surface water infiltration and subsurface flow based on a 9‐year (from 2009 to 2017) thermal monitoring at an experimental road test site built on ice‐rich permafrost conditions in southwestern Yukon, Canada. Our results show that snowmelt water infiltration in the spring rapidly increases temperature in the upper portion of the embankment. The earlier disappearance of snow deposited at the embankment slope increases the thawing period and the temperature gradient in the embankment compared with the natural ground. Infiltrated summer rainfall water lowered the near‐surface temperatures and subsequently warmed embankment fill materials down to 3.6‐m depth. Heat advection caused by the flow of subsurface water produced warming rates at depth in the embankment subgrade up to two orders of magnitude faster than by atmospheric warming (heat conduction). Subsurface water flow promoted permafrost thawing under the road embankment and led to an increase in active layer thickness. We conclude that the thermal stability of roadways along the Alaska Highway corridor is not maintainable in situations where water is flowing under the infrastructure unless mitigation techniques are used. Severe structural damages to the highway embankment are expected to occur in the next decade.
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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 | 0.000 | 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".