A new CT scan methodology to characterize a small aggregation gravel clast contained in a soft sediment matrix - INRA - Institut national de la recherche agronomique Accéder directement au contenu
Article Dans Une Revue Earth Surface Dynamics Année : 2017

A new CT scan methodology to characterize a small aggregation gravel clast contained in a soft sediment matrix

Résumé

Over the past decades, X-ray computed tomography (CT) has been increasingly applied in the geosciencescommunity. CT scanning is a rapid, non-destructive method allowing the assessment of relative densityof clasts in natural archives samples. This study focuses on the use of this method to explore instantaneousdeposits as major contributors to sedimentation of high-elevation lakes in the Alps, such as the Lake Lauvitelsystem (western French Alps). This lake is located within a very steep valley prone to episodic flooding andfeatures gullies ending in the lake. This variety of erosion processes leads to deposition of sedimentary layerswith distinct clastic properties. We identified 18 turbidites and 15 layers of poorly sorted fine sediment associatedwith the presence of gravels since AD 1880. These deposits are respectively interpreted as being inducedby flood and wet avalanche. This constitutes a valuable record from a region where few historical records exist.This CT scan approach is suitable for instantaneous deposit identification to reconstruct past evolution and maybe applicable to a wider variety of sedimentary archives alongside existing approaches
Fichier principal
Vignette du fichier
esurf-5-199-2017.pdf (5.19 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01878839 , version 1 (27-10-2020)

Licence

Paternité

Identifiants

Citer

Laurent Fouinat, Pierre Sabatier, Jérôme Poulenard, Jean-Louis Reyss, Xavier Montet, et al.. A new CT scan methodology to characterize a small aggregation gravel clast contained in a soft sediment matrix. Earth Surface Dynamics, 2017, 5 (1), pp. 199 - 209. ⟨10.5194/esurf-5-199-2017⟩. ⟨hal-01878839⟩
199 Consultations
72 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More