Selecting geomorphic variables for automatic river segmentation: Trade-offs between information gained and effort required

Martínez Fernández, Vanesa and Gonzalez Del Tanago Del Rio, Marta and Garcia De Jalon Lastra, Diego (2019). Selecting geomorphic variables for automatic river segmentation: Trade-offs between information gained and effort required. "Geomorphology", v. 329 ; pp. 248-258. ISSN 0169-555X. https://doi.org/10.1016/j.geomorph.2019.01.005.

Description

Title: Selecting geomorphic variables for automatic river segmentation: Trade-offs between information gained and effort required
Author/s:
  • Martínez Fernández, Vanesa
  • Gonzalez Del Tanago Del Rio, Marta
  • Garcia De Jalon Lastra, Diego
Item Type: Article
Título de Revista/Publicación: Geomorphology
Date: 2019
ISSN: 0169-555X
Volume: 329
Subjects:
Freetext Keywords: River segmentation; Geomorphic variables; Multi-response-permutation procedures; Flow regulation
Faculty: E.T.S.I. Montes, Forestal y del Medio Natural (UPM)
Department: Sistemas y Recursos Naturales
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Identifying river segments with apparently distinct geomorphic characteristics but relatively homogeneous internal features may be critically helpful in designing network analysis for characterization, environmental assessment and river management. Automatic segmentation procedures using geographic tools and statisticalmethods provide objective and replicable results. In particular, multivariate procedures may be appropriated for different purposes such as coping with themultiple dimensionality of river systems. Although there is an increasing number of studies dealing with segmentation using different sets of morphological variables, the influence that the selected variables have on segmentation results is rarely assessed. In this context, we defined five combinations of frequently used geomorphic variables (i.e., channel slope, active channel width, valley bottomwidth, channel confinement and specific streampower), and compared the obtained segmentation results. We study the upper Esla River network, covering a total length of 294 km,with the largest two rivers regulated by large dams. Variables were measured at successive river sections 200mapart. Five segmentation results were obtained in whichwe compared the number and characteristics of the segments, and the internal variability and the suitability of predicting river dynamics (i.e., occurrence of bare and vegetated gravel bars). The number of segments per kilometer of river and their average length were different among segmentations but variedmuchmore across rivers than across segmentations. In general, segmentations including channel slope and active channel width performed better in predicting the occurrence of bare gravel bars than segmentations based on stream power or valley confinement. When splitting the initial data set into regulated and non-regulated segments, differences in predicting the occurrence of gravel bars were found, with better results in the case of non-regulated rivers. Channel slope and active channel width showed a reduced explanatory power for the regulated reaches. Finally, we conclude that primary geomorphic variables such as channel slope and active channelwidth were more efficient than secondary variables such as stream power,whichmay encompassmore information but needed additional data and the use of empirical models,with greater effort andmuch uncertainty. In the case of regulated rivers, automatic segmentation including the affected variables (e.g., active channel width) may help in detecting differences in geomorphic sensitivity to river adjustments across the resulting segments downstream from the dams. Our results offer valuable insights into the selection of geomorphic variables for river segmentation analysis, in which trade-offs between the information gained and the effort required must be considered according to the respective research targets.

Funding Projects

TypeCodeAcronymLeaderTitle
FP7282656REFORMSTICHTING DELTARESREstoring rivers FOR effective catchment Management

More information

Item ID: 64200
DC Identifier: http://oa.upm.es/64200/
OAI Identifier: oai:oa.upm.es:64200
DOI: 10.1016/j.geomorph.2019.01.005
Official URL: https://www.sciencedirect.com/science/article/pii/S0169555X19300054?via%3Dihub
Deposited by: Memoria Investigacion
Deposited on: 10 Nov 2020 10:40
Last Modified: 10 Nov 2020 10:40
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