Character, spatial and temporal variation of turbidity currents on a source-to-sink scale.
Notice bibliographique
Résumé
<p>Seafloor avalanches of sediment called turbidity currents are one of the principle mechanisms for moving sediments across our planet. However, turbidity currents are notoriously difficult to monitor directly in action, and we still mainly depend on their sedimentary deposits as well as physical and numerical models to understand their temporal and spatial evolution. In recent years, multiple studies have successfully made direct measurements within active turbidity currents at multiple sites along their pathway. However, these direct measurements are often limited to the upper reaches of submarine systems, only cover relatively short (few months to a couple of years) time scales, or have very few measurement stations (<3). To capture the full range of turbidity current types and recurrence times we need to combine direct monitoring with longer-term archives in sedimentary deposits. Here we present an unusual data set that extends from the submarine channel on the delta, to the final deposits in the deep basin. The dataset combines short-term (< 1 year) direct measurements of flows with long-term sediment deposits (dating back to about 100 years). This combination of data types allows us to understand turbidity current frequencies, runouts, heights and characteristics along an entire submarine system.  </p><p>We analyse data from Bute Inlet, which is a fjord in British Colombia, Canada. The entire turbidity current system stretches out for 80 km, with an incised submarine channel extending for 45 km. 46 Cores have been collected between 2015 and 2018. Simultaneously, direct measurements of the currents have been obtained in 2016 and 2018 using Acoustic Doppler Current Profilers (ADCPs) in the submarine channel.</p><p>Our objective is two-fold. First, we look at flow frequency over time and space. Visual logs of the sediment cores, as well as sediment accumulation rates for a selection of cores, are used to infer flow frequencies. We then use the ADCP data to understand more frequent and recent flows at 6 places along the channel. These ADCP measurements are used to infer frequencies which are not necessarily recorded in the deposits, and give additional insights into current-day activity. This allows us to reconstruct the change in frequency over space and time.</p><p>Second, we consider the variation in turbidity current character to understand how flows evolve along the channel. Facies determination and grain size data are used to infer turbidity current character. Cores along the channel, on terraces and in the deep basin are used to understand the spatial variation. Finally, comparison of deposits and monitoring (ADCP) data shows how submarine flows are recorded by their deposits.</p>
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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) | 0,005 | 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 tête enseignante, 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 ».