Monitoring sediment transport in morphologically complex and labile channels remains a difficult task, even at the laboratory scale. To address this challenge, a fully automated imagery technique for continuously mapping the spatial and temporal variability of bedload transport is proposed. This method uses differentiated time-lapse imagery taken from a fixed camera to detect bed variations induced by grain displacement. The technique is not based on tracking the individual particles; rather, it evaluates macroscopic colour changes within a region that contains several grains, which depend on the occurrence and intensity of the bedload transport. Image-derived data were compared with the sediment flux measured during four flume experiments, and produced good correspondence. The method provides continuous tracking of the location of the transporting channels, and enables estimation of local variations in the magnitude of the bedload flux. Moreover, the spatial extent of the monitoring area offers an unprecedented opportunity to aggregate spatially dense and continuous data at the reach scale, as needed to properly capture the full range of variability of morphologically complex and rapidly evolving gravel-bed rivers. Despite being limited to laboratory-scale physical experiments, the method provides useful data to investigate fundamental morphodynamic processes such as bar migration, bank erosion, anabranches opening/closure, and the associate spatial and temporal scales. Further, the data obtained have the potential to enhance numerical model calibration and improve our understanding of the complex dynamics of real-world settings.

Capturing the spatiotemporal variability of bed load transport: a time-lapse imagery technique / Redolfi, Marco; Guidorizzi, L.; Tubino, Marco; Bertoldi, Walter. - In: EARTH SURFACE PROCESSES AND LANDFORMS. - ISSN 0197-9337. - 42:(2017), pp. 1140-1147. [10.1002/esp.4126]

Capturing the spatiotemporal variability of bed load transport: a time-lapse imagery technique

Redolfi, Marco;
2017

Abstract

Monitoring sediment transport in morphologically complex and labile channels remains a difficult task, even at the laboratory scale. To address this challenge, a fully automated imagery technique for continuously mapping the spatial and temporal variability of bedload transport is proposed. This method uses differentiated time-lapse imagery taken from a fixed camera to detect bed variations induced by grain displacement. The technique is not based on tracking the individual particles; rather, it evaluates macroscopic colour changes within a region that contains several grains, which depend on the occurrence and intensity of the bedload transport. Image-derived data were compared with the sediment flux measured during four flume experiments, and produced good correspondence. The method provides continuous tracking of the location of the transporting channels, and enables estimation of local variations in the magnitude of the bedload flux. Moreover, the spatial extent of the monitoring area offers an unprecedented opportunity to aggregate spatially dense and continuous data at the reach scale, as needed to properly capture the full range of variability of morphologically complex and rapidly evolving gravel-bed rivers. Despite being limited to laboratory-scale physical experiments, the method provides useful data to investigate fundamental morphodynamic processes such as bar migration, bank erosion, anabranches opening/closure, and the associate spatial and temporal scales. Further, the data obtained have the potential to enhance numerical model calibration and improve our understanding of the complex dynamics of real-world settings.
2017
42
1140
1147
Capturing the spatiotemporal variability of bed load transport: a time-lapse imagery technique / Redolfi, Marco; Guidorizzi, L.; Tubino, Marco; Bertoldi, Walter. - In: EARTH SURFACE PROCESSES AND LANDFORMS. - ISSN 0197-9337. - 42:(2017), pp. 1140-1147. [10.1002/esp.4126]
Redolfi, Marco; Guidorizzi, L.; Tubino, Marco; Bertoldi, Walter
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1317312
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