Where, when, and why do frozen landscapes erode faster than unfrozen ones?
Notice bibliographique
Résumé
A fundamental research question of periglacial geomorphology is whether and how ground ice interacts with surface water flow to change grain-scale sediment transport dynamics, and how those processes translate to the landscape-scale, potentially changing the timing and intensity of erosion events. Polar deserts in the Canadian High Arctic serve as ideal field laboratories to isolate the effects of ground ice on particle transport due to a lack of vegetation and by being largely undisturbed since the last glacial maximum.During the Summer 2024 field season at the Flying Squirrel polygon field on Devon Island, we observed a complex of pools interconnected by channelised polygon troughs and relatively steeper relict gravel deposits, as well as evidence of recent transport of gravel- and sand-sized particles. However, despite visiting during a storm event, we did not observe active transport and only limited surface water run-off. As such, the timing and magnitude(s) of the flow events that caused the gravel deposits are unclear, nor do we know the thermal state of the bed during the time of transport. To investigate this research gap, we conducted flume experiments with an initially frozen bed under rarefied transport conditions to investigate at what thermal state sediment transport is favoured and compare the bed behaviour to unfrozen experiments. Particle flux is maximised at the start of the frozen experiments before decaying to an approximate steady-state background flux similar to the unfrozen experiments, following a power law with the relationship . At early stages of the frozen experiments, hydraulic jumps develop in concert with variations of the local thaw depth, which result in enhanced particle entrainment and relatively rapid thawing downstream, as the hydraulic jumps migrate upstream. Beneath hydraulic jumps, we observe forced injections of water into the partially-frozen bed, which can spread laterally along an evolving thaw front. Depending on the thaw front depth, the combined effects of locally-intensified melting, increased pore pressure and mechanical disruption of the bed can enhance particle entrainment locally and increase the overall erosion rate compared to unfrozen experiments. Enhanced rates of particle entrainment continue until hydraulic jump activity diminishes and the injected surface water no longer penetrates to the thaw front. Accordingly, we develop a maximum injection depth, which is strongly dependent on the local permeability, as well as the jump height.Our experimental results show that the thermal state of the bed can have a strong influence on the local entrainment rate at the grain-scale with entrainment being promoted at a shallow thaw depth. We hypothesise that this sensitivity also translates to the landscape-scale, where all water has to travel as overland flow when the active layer is thin, whereas much of the water supply can be compensated as subsurface flow late in the summer, minimising particle entrainment. This could explain the lack of active erosion at the Flying Squirrel polygon field during the late summer when the active layer was approximately 1m deep.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».