Image processing to study the evolution of channel slope and water depth in bimodal sediment mixtures - Université Jean-Monnet-Saint-Étienne Access content directly
Conference Papers Year : 2015

Image processing to study the evolution of channel slope and water depth in bimodal sediment mixtures

Traitement d'images pour l'étude de l'évolution de la pente du lit et de la hauteur d'eau dans des mélanges bimodaux de sédiments

Abstract

Bedload transport is the sediment load transported in contact with the bed of a river channel. Empirical relations are often used to predict sediment transport rates. However, these predictions usually lack accuracy. Consequently, a more detailed comprehension of the physical processes is required. For example, we require an improved understanding on how fine sediment inputs to river channels influence sediment transport, channel stability, ecology and stratigraphy. In this context, an experimental investigation was undertaken in a laboratory flume equipped with controlled water and sediment supplies to create bimodal mixtures of coarse and fine spherical glass beads. The flume experiments were recorded using a high frequency camera. We propose a new image analysis chain dedicated to automatically detect the water free surface and the bed elevation for a sequence of images. This method is based on a combination of morphological operations, gradient calculations and watershed transformations. The detections allowed the measurement of important physical quantities such as water depth, slope and their evolution over time. By making comparisons for varying sizes of fine sediment, we have highlighted several phenomena which permit a better understanding of bedload mobility, specifically related to the influence of grain size ratio.
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Dates and versions

ujm-01277397 , version 1 (22-02-2016)

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Hugo Lafaye de Micheaux, Ashley Dudill, Philippe Frey, Christophe Ducottet. Image processing to study the evolution of channel slope and water depth in bimodal sediment mixtures. 10th Pacific Symposium on Flow Visualization and Image Processing, Jun 2015, Naples, Italy. pp.id43. ⟨ujm-01277397⟩
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