Experimental modelling of coastal permafrost weathering in two different setup : a wave flume and a static water tank.
Bibliographic record
Abstract
Permafrost in high latitudes has been particularly affected by global warming. Its extent is decreasing rapidly, and that can have a significant effect on coastal communities. Because of the ice mixed with sediments, those coasts are affected by important erosive processes, differing from those affecting lower latitudes (Lantuit et al., 2012). The number of studies on coastline dynamics is significant, however the majority have been completed using remote sensing data. Over the last decade numerical models have also been developed (Barnhart et al., 2014) but few studies have tried physical modelling of coastal permafrost (Korte et al., 2020). Physical modelling allows for the observance of the erosional processes during the experiments in the controlled environment. The purpose of this study was to use experimental modelling to improve the knowledge on the processes and the main parameters involved in coastal permafrost weathering.For a first set of experiments, permafrost blocks were created in the M2C cold rooms (Caen University, France) using a cubic box made of Polyvinyl chloride (PVC). The blocks were 30 cm high and 50 cm wide. They were placed in the M2C wave flume (17 m long and 50 cm wide). For the experiments presented here, only regular wave conditions were used. While the block was degrading, it was monitored with several instruments to document its morphological and thermal evolution, along with the hydrodynamic conditions. Their purpose is to observe the changes in permafrost erosion under different experimental configurations (wave height, water height, water temperature, sediment type) to quantify the influence of each parameter on the erosion process. As predicted by different models (Dupeyrat et al., 2011; White et al., 1980) the water temperature remains the critical parameter for the erosion rate, but the granulometry, linked to the porosity and ice structure also has an important impact. Coarser blocks erode at a slower rate. As the block degrades, a cone of loose sediments is formed alongside the receding frozen part. Wave action tends to lower the cone’s slope angle and increase the frequency of gravity-driven processes, as well as creating scallop patterns on the exposed permafrost surface.These experiments were compared to a complementary study carried out in a cubic static water tank. The permafrost blocks were smaller (30 cm high and 30 cm wide) and allowed for the testing of the influence of salinity on the degradation of the blocks. The results in the static water tank could then be compared with the wave flume tests. This comparison allowed for the quantification of the mechanical component of the erosion process while also expanding the test series to include the influence of water temperature and salinity. Salinity seems to only have a small impact on the block’s erosion rate in our setup, compared to the water temperature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".