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A multi-resolution method to map and identify locations of future gully and channel incision

Walker, Simon; Wilkinson, Scott N.; Van Dijk, Albert; Hairsine, Peter

Description

While channel erosion is recognised as a major, often-dominant, source of river sediment, channel geometry and its change remain impractical to measure for anything but small experimental watersheds. Designing remediation strategies in landscapes affected by channel erosion requires information on the extent and location of current incised channel features, as well as a method to determine locations where incision may occur in the future. We present a multi-resolution algorithm that uses...[Show more]

dc.contributor.authorWalker, Simon
dc.contributor.authorWilkinson, Scott N.
dc.contributor.authorVan Dijk, Albert
dc.contributor.authorHairsine, Peter
dc.date.accessioned2020-07-14T05:26:13Z
dc.identifier.issn0169-555X
dc.identifier.urihttp://hdl.handle.net/1885/206154
dc.description.abstractWhile channel erosion is recognised as a major, often-dominant, source of river sediment, channel geometry and its change remain impractical to measure for anything but small experimental watersheds. Designing remediation strategies in landscapes affected by channel erosion requires information on the extent and location of current incised channel features, as well as a method to determine locations where incision may occur in the future. We present a multi-resolution algorithm that uses topographic information to concurrently map both existing incised landform elements and areas at risk of future incision. The former uses elevation, slope and profile curvature to identify topographic signatures of incised landform elements, and the latter uses landscape position, topographic wetness index and stream power index to isolate areas likely susceptible to future incision. We aimed to develop a computationally efficient method capable of operating across a broad range of landscapes. The algorithm was tested in three contrasting environments in eastern Australia with promising results. Sensitivity analysis indicates the method performs reasonably consistently across landscapes, but that outputs become more sensitive as the average slope of the landscape increases. A comparison between cleared and uncleared hillsides suggested that areas indicated at risk of future incision are plausible, and that cleared areas were more susceptible to channel incision. The only required input is a digital elevation model, and outputs can provide a rapid visual assessment of landscapes affected by incisional erosion. This technique enables the identification of gully erosion and the planning of remediation works across landscapes of thousands of square kilometres. It may assist in prioritisation of works and further insights into the processes associated with channel incision.
dc.description.sponsorshipFunding for this research was supported by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and also by the Australian Government's National Environment Science Program (NESP) Tropical Water Quality Hub (Projects 2.1.4 and 5.9). Simon Walker also receives a scholarship under the Australian Government Research Training Program (AGRTP) to support his PhD program.
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherElsevier
dc.rights© 2020 Crown
dc.sourceGeomorphology
dc.subjectGully Erosion
dc.subjectDigital Elevation Model
dc.subjectMulti-Resolution Algorithm
dc.subjectLiDAR
dc.titleA multi-resolution method to map and identify locations of future gully and channel incision
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume358
dcterms.dateAccepted2020-02-21
dc.date.issued2020-02-28
local.identifier.absfor040601 - Geomorphology and Regolith and Landscape Evolution
local.identifier.ariespublicationu1055894xPUB230
local.type.statusPublished Version
local.contributor.affiliationWalker, Simon, College of Science, ANU
local.contributor.affiliationWilkinson, Scott N, CSIRO Land and Water
local.contributor.affiliationVan Dijk, Albert, College of Science, ANU
local.contributor.affiliationHairsine, Peter, College of Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage16
local.identifier.doi10.1016/j.geomorph.2020.107115
local.identifier.absseo961202 - Rehabilitation of Degraded Farmland, Arable Cropland and Permanent Cropland Environments
dc.date.updated2020-03-23T21:44:51Z
CollectionsANU Research Publications

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