Evaluating Climate Change Impact on Low-Volume Roads in Southern Canada
Bibliographic record
Abstract
Information extracted from global climate models suggests that average temperatures and annual precipitation will increase over the next several decades, with potential implications for pavement performance and design. With Canadian data from the Long-Term Pavement Performance program, the Mechanistic-Empirical Pavement Design Guide was used to quantify the impacts of projected climatic changes on pavement performance of low-volume roads at six sites. A series of analyses was conducted to assess the impact of pavement structure, material characteristics, traffic loads, and changes in climate on incremental and terminal pavement deterioration and performance. Results suggest that rutting (asphalt, base, and subbase layers) and both longitudinal and alligator cracking will be exacerbated by climate change, with transverse cracking becoming less of a problem. In general, maintenance, rehabilitation, and reconstruction will be required earlier in the design life; however, the effects of climate change were found to be modest relative to effects of regional baseline climate differences and increased future traffic. For road authorities, key adaptations will relate to when and how to modify current design and maintenance practices. Pavement engineers should be encouraged to develop a protocol for considering potential climate change in the development and evaluation of future designs and maintenance programs. Incorporating other climate-related road infrastructure issues– for instance those associated with concrete pavements; surface-treated roads; and airfields bridges, and culverts–would be beneficial. At a minimum, long time series of historic climatic and road weather observations (e.g., >30 years) should be incorporated into analyses of pavement deterioration and assignment of performance graded materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".