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A waterbody typology derived from catchment controls using self-organising maps
journal contribution
posted on 2020-03-05, 09:01 authored by Eleanore L. Heasley, James D. A. Millington, Nicholas Clifford, Michael A. ChadwickMultiple catchment controls contribute to the geomorphic functioning of river systems at the reach-level, yet only a limited number are usually considered by river scientists and managers. This study uses multiple morphometric, geological, climatic and anthropogenic catchment characteristics to produce a single national typology of catchment controls in England and Wales. Self-organising maps, a machine learning technique, are used to reduce the complexity of the GIS-derived characteristics to classify 4485 Water Framework Directive waterbodies into seven types. The waterbody typology is mapped across England and Wales, primarily reflecting an upland to lowland gradient in catchment controls and secondarily reflecting the heterogeneity of the catchment landscape. The seven waterbody types are evaluated using reach-level physical habitat indices (including measures of sediment size, flow, channel modification and diversity) extracted from River Habitat Survey data. Significant differences are found between each of the waterbody types for most habitat indices suggesting that the GIS-derived typology has functional application for reach-level habitats. This waterbody typology derived from catchment controls is a valuable tool for understanding catchment influences on physical habitats. It should prove useful for rapid assessment of catchment controls for river management, especially where regulatory compliance is based on reach-level monitoring.
Funding
Natural Environmental Research Council (NERC), grant number NE/L002485/1
History
School
- Social Sciences
Department
- Geography and Environment
Published in
WaterVolume
12Issue
1Publisher
MDPI AGVersion
- VoR (Version of Record)
Rights holder
© The authorsPublisher statement
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Acceptance date
2019-12-18Publication date
2019-12-24Copyright date
2019eISSN
2073-4441Publisher version
Language
- en
Depositor
Prof Nicholas Clifford. Deposit date: 4 March 2020Article number
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