Defrosting river banks: morphodynamics and sediment flux
Notice bibliographique
Résumé
Climate warming is projected to impact hydrology and change ice-cover periods within river channels in polar and permafrost regions. These changes will impact the duration of freezing, frozen, thawing and unfrozen periods, and will affect sediment transport fluxes, notably through riverbank erosion. However, at present, it is difficult to quantify the long-term combined impacts of soil moisture dynamics, changing ambient air, water and ground temperatures and the subsequent rates of thawing and freezing on the fluvial bank erosion processes. Herein we present a series of 130 laboratory experiments conducted in a novel cryolab morphology facility using a small-scale Friedkin channel. These cryolab flume experiments aim to assess the influence of flow velocity, soil moisture content and temperature of the sediment on riverbank stability with varying ambient air and water temperatures and flow discharges. The riverbank characteristics in the experiments, including sediment grain size, soil moisture and soil temperature, are based on observations from the sub-artic River Pulmankijoki (Finland) during different seasons. The sediment bank blocks (2 cm high) were prepared for each experiment the day before and kept in the cryolab facility overnight to match ambient air temperatures. The topography was measured before and after each experiment, using an array of images collected via a semi-automatic Canon camera. Surface models were produced with structure from motion and volumetric changes were calculated. GoPro cameras filmed videos of bank evolution to determine higher temporal records of bank edge retreat through the experiments. Buoyant sequins were seeded at the start and end of each experiment in order to calculate the surface flow velocities using a particle tracking velocimetry method. A FLIR A655 infrared thermal camera was used to aid understanding the thermal transfers between the flow and the bank. Results show that the water level had more impact on bank erosion than flow velocities, as at low discharges the full bank height of the channel was less exposed to flow shear. Most critically, the volumetric erosion rate was found to have a non-linear correlation with the air temperature, being highest with an air temperature of 7.0°C (water temperature 7.2°C) and second highest with an air temperature of -2.1°C (water temperature 3.2°C). Conversely the lowest erosion rates occurred at an ambient temperature of -15°C. Erosion occurred as chucks at +1.7 – +3.2°C water temperatures, if the moisture content was high enough, i.e. 18.9% or more, for the sediment block to be frozen. High moisture contents also slowed the heating effect of the flowing water, which propagated through the bank at a lower rate. With the lower soil moisture conditions of 1.1–10.0%, there was not sufficient water within the block to allow it to freeze as a unit. Under such conditions the block acts as loose sediment, and as a consequence water and ambient temperatures have less influence on the erosion rate. These findings have a suite of implications for morphodynamic responses of river channels across defrosting landscapes, which will alter hydrology and sediment fluxes in highly sensitive environments as climate warms into the future.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».