Drone based quantification of channel response to an extreme flood for a piedmont stream

Heritage, G and Entwistle, NS ORCID: https://orcid.org/0000-0002-5799-0506 2019, 'Drone based quantification of channel response to an extreme flood for a piedmont stream' , Remote Sensing, 11 (17) , p. 2031.

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The influence of extreme floods on the form and functioning of upland systems has concentrated on the erosive impact of these flows. They are seen to be highly competent with coarse sediment transport rates limited by upstream supply and moderated by the ‘blanketing’ effect of an armour layer. This study investigates the effect of extreme events on the upland sediment cascade subjected to a recent extreme rainfall-induced flood event. The drone-based survey generated orthophotography and a DEM surface, which was compared with historic LiDAR data. This allowed erosion and deposition to be quantified and the surface micro-variation used to characterise stable and mobile sediment. The idealised model of sediment residence time increasing downstream is questioned by the findings of this study as relatively little coarse bedload sediment appears to have been transferred downstream in favour of initial local channel erosion (moderated by legacy large sediment), mid-reach palaeo-channel reactivation, sub-channel infilling and downstream deposition of the majority of mobilised sediment across berm and bar surfaces within the active inset channel margins. Channel margin erosion was largely limited to fine sediment stripping moderated by the re-exposure of post-glacial sediment. Only a weak relationship was found between local channel slope and deposition, with storage linked more to the presence of inset berm and bar areas within the inset active channel. Downstream fining of sediment is apparent as is a strong contrast between coarser active sub-channels and finer bar and berm areas.

Item Type: Article
Schools: Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Journal or Publication Title: Remote Sensing
Publisher: MDPI
ISSN: 2072-4292
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Depositing User: USIR Admin
Date Deposited: 19 Aug 2019 08:02
Last Modified: 16 Feb 2022 02:32
URI: http://usir.salford.ac.uk/id/eprint/52136

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