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Assessment of a rapid method for quantitative reach-scale estimates of deposited fine sediment in rivers

Assessment of a rapid method for quantitative reach-scale estimates of deposited fine sediment in rivers
Assessment of a rapid method for quantitative reach-scale estimates of deposited fine sediment in rivers
Despite increasing concerns about the negative effects that increased loads of fine-grained sediment are having on freshwaters, the need is clear for a rapid and cost-effective methodology that gives precise estimates of deposited sediment across all river types and that are relevant to morphological and ecological impact. To date few attempts have been made to assess the precision of techniques used to assemble data on fine sediment storage in river channels. Accordingly, we present an investigation into the sources of uncertainty associated with estimates of deposited fine-grained sediment in rivers using a sediment resuspension technique, an approach that provides an instantaneous measure of deposited fine sediment (surface and subsurface) in terms of quantity and quality. We investigated how variation associated with river type, spatial patchiness within rivers, sampling, and individual operators influenced estimates of deposited fine sediment using this approach and compared the precision with that of visual estimates of river bed composition — a commonly applied technique in rapid river surveys. We have used this information to develop an effective methodology for producing reach-scale estimates with known confidence intervals.

By using a spatially-focussed sampling strategy that captured areas of visually high and low deposition of fine-grained sediment, the dominant aspects of small-scale spatial variability were controlled and a more precise instantaneous estimate of deposited fine sediment derived. The majority of the remaining within-site variance was attributable to spatial and sampling variability at the smallest (patch) scale. The method performed as well as visual estimates of percentage of the river bed comprising fines in its ability to discriminate between rivers but, unlike visual estimates, was not affected by operator bias.

Confidence intervals for reach-scale measures of deposited fine-grained sediment were derived for the technique, and these can be applied elsewhere.
0169-555X
37-50
Duerdoth, C.P.
ef15369b-edc4-445c-8ca5-af77b5405d79
Arnold, A.
f4dc0184-547e-4775-99a9-15083657a171
Murphy, J.F.
6f230e5a-143a-4563-953f-57a5eddd7797
Naden, P.S.
94009f2b-9d27-4341-9fdd-daffc281d76d
Scarlett, P.
e2b53db4-b01c-426e-845c-286f2c1b68a0
Collins, A.L.
eb72a479-2336-4268-a837-79d926239de3
Sear, D.A.
ccd892ab-a93d-4073-a11c-b8bca42ecfd3
Jones, J.I.
9acb09cb-4a0d-4fcd-99cc-9bf198d9d564
Duerdoth, C.P.
ef15369b-edc4-445c-8ca5-af77b5405d79
Arnold, A.
f4dc0184-547e-4775-99a9-15083657a171
Murphy, J.F.
6f230e5a-143a-4563-953f-57a5eddd7797
Naden, P.S.
94009f2b-9d27-4341-9fdd-daffc281d76d
Scarlett, P.
e2b53db4-b01c-426e-845c-286f2c1b68a0
Collins, A.L.
eb72a479-2336-4268-a837-79d926239de3
Sear, D.A.
ccd892ab-a93d-4073-a11c-b8bca42ecfd3
Jones, J.I.
9acb09cb-4a0d-4fcd-99cc-9bf198d9d564

Duerdoth, C.P., Arnold, A., Murphy, J.F., Naden, P.S., Scarlett, P., Collins, A.L., Sear, D.A. and Jones, J.I. (2015) Assessment of a rapid method for quantitative reach-scale estimates of deposited fine sediment in rivers. Geomorphology, 230, 37-50. (doi:10.1016/j.geomorph.2014.11.003).

Record type: Article

Abstract

Despite increasing concerns about the negative effects that increased loads of fine-grained sediment are having on freshwaters, the need is clear for a rapid and cost-effective methodology that gives precise estimates of deposited sediment across all river types and that are relevant to morphological and ecological impact. To date few attempts have been made to assess the precision of techniques used to assemble data on fine sediment storage in river channels. Accordingly, we present an investigation into the sources of uncertainty associated with estimates of deposited fine-grained sediment in rivers using a sediment resuspension technique, an approach that provides an instantaneous measure of deposited fine sediment (surface and subsurface) in terms of quantity and quality. We investigated how variation associated with river type, spatial patchiness within rivers, sampling, and individual operators influenced estimates of deposited fine sediment using this approach and compared the precision with that of visual estimates of river bed composition — a commonly applied technique in rapid river surveys. We have used this information to develop an effective methodology for producing reach-scale estimates with known confidence intervals.

By using a spatially-focussed sampling strategy that captured areas of visually high and low deposition of fine-grained sediment, the dominant aspects of small-scale spatial variability were controlled and a more precise instantaneous estimate of deposited fine sediment derived. The majority of the remaining within-site variance was attributable to spatial and sampling variability at the smallest (patch) scale. The method performed as well as visual estimates of percentage of the river bed comprising fines in its ability to discriminate between rivers but, unlike visual estimates, was not affected by operator bias.

Confidence intervals for reach-scale measures of deposited fine-grained sediment were derived for the technique, and these can be applied elsewhere.

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More information

Accepted/In Press date: 6 November 2014
e-pub ahead of print date: 15 November 2014
Published date: 1 February 2015
Organisations: Geography & Environment

Identifiers

Local EPrints ID: 389602
URI: http://eprints.soton.ac.uk/id/eprint/389602
ISSN: 0169-555X
PURE UUID: eb760c38-ef66-4ab9-82f6-25156884675e
ORCID for D.A. Sear: ORCID iD orcid.org/0000-0003-0191-6179

Catalogue record

Date deposited: 09 Mar 2016 13:35
Last modified: 15 Mar 2024 02:47

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Contributors

Author: C.P. Duerdoth
Author: A. Arnold
Author: J.F. Murphy
Author: P.S. Naden
Author: P. Scarlett
Author: A.L. Collins
Author: D.A. Sear ORCID iD
Author: J.I. Jones

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