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The shape of fluvial bedload gravels: A large, high-quality dataset of active-channel deposits. | LitMetric

The shape of fluvial bedload gravels: A large, high-quality dataset of active-channel deposits.

Data Brief

Department of Archaeology, The University of Sydney, Sydney, New South Wales 2006, Australia.

Published: June 2022

Isotropic bedload gravels from an active fluvial system were collected from seven stations along the length of the Sabeto River of western Viti Levu, Fiji. Sampling was confined to clasts of Navilawa Monzonite, an intrusive rock that crops out only along the upper reaches of the river. The sampled gravels consisted of stream-bed surface material obtained from transects normal to the active channel. An additional sample was collected from an outcrop of fresh Navilawa Monzonite undergoing active physical breakdown on the side of the bedrock channel immediately adjacent to the river. A total of 883 clasts, ranging in diameter (-axis) from 12 to 337 mm, was collected. The long (), intermediate () and short () axis of each clast was measured, along with the diameter of the sharpest corner of the maximum projection outline ( ) and the diameter of the maximum inscribed circle ( ). At six of the stations, the mass of each clast was recorded. Measurements were also made of the density of fresh Navilawa Monzonite. The dataset includes measurements of Navilawa Monzonite density and determinations of the Modified Wentworth Roundness, Maximum Projection Sphericity and Oblate-Prolate Index of each clast. At six of the stations the volume of each particle was estimated using measurements of particle mass and rock density. The repository, in Mendeley Data [1], provides a large, high-quality dataset of the shape of isotropic bedload gravels from an active fluvial system, affording information on the downstream evolution of particle shape. The dataset will be useful for sedimentologists, fluvial geomorphologists, hydraulic engineers and those concerned with fluvial bedload transport.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8960898PMC
http://dx.doi.org/10.1016/j.dib.2022.108028DOI Listing

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