This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1002/eco.1710. This is version 1 of this Preprint.
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Abstract
Large wood in rivers and logjams are linked to the presence of varied riverine morphologies and increased abundance and diversity of aquatic biota. Current research into the ecohydrological, morphological and geochemical effects of logjams is restricted by difficulties in comparing findings between river systems. The problem is exacerbated by a lack of standardised metrics for recording and reporting logjams and a scale dependence of logjam effects with river size.
In this paper a new method for analysing logjams is presented based on a set of seven dimensionless metrics of structure and morphological effects. These metrics are used along with a cluster analysis to identify key logjam types within a study river. The analysis framework is applied to data from a small forest river in the UK and identifies that 73% of logjams in this system can be grouped into eight distinct classes. Of these classes, two are logjams which only partly fill the channel and six are channel spanning. The individual classes are differentiated from each other principally by the degree of lateral and vertical erosion found in association with the logjams.
The dimensionless metrics are also applied qualitatively to a range of logjams described in the literature and show the potential for the method to be applied as a standard survey and analysis
framework for logjams across diverse river environments. The potential to link logjam form with function, and therefore provision of specific habitats, has wide applicability to the design and monitoring of river restoration schemes.
DOI
https://doi.org/10.31223/osf.io/e4gt7
Subjects
Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Sciences, Geomorphology, Hydrology, Natural Resources Management and Policy, Physical Sciences and Mathematics, Sedimentology, Water Resource Management
Keywords
fluvial geomorphology, Cluster analysis, logjams, classification system, large wood
Dates
Published: 2017-11-01 13:36
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