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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Discussion papers | Copyright
https://doi.org/10.5194/esurf-2018-67
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 27 Sep 2018

Research article | 27 Sep 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Earth Surface Dynamics (ESurf).

A segmentation approach for the reproducible extraction and quantification of knickpoints from river long profiles

Boris Gailleton1, Simon M. Mudd1, Fiona J. Clubb2, Daniel Peifer3, and Martin D. Hurst3 Boris Gailleton et al.
  • 1School of GeoSciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, UK
  • 2Institute of Earth and Environmental Science, University of Potsdam, 14476 Potsdam-Golm, Germany
  • 3School of Geographical and Earth Sciences, University of Glasgow, University Avenue, Glasgow G12 8QQ, UK

Abstract. Changes in the steepness of river profiles or abrupt vertical steps (i.e. waterfalls) are thought to be indicative of changes in erosion rates, lithology, or other factors that affect landscape evolution. These changes are referred to as knickpoints or knickzones and are pervasive in bedrock river systems. Such features are thought to reveal information about landscape evolution and patterns of erosion, and therefore their locations are often reported in the geomorphic literature. It is imperative that studies reporting knickpoints and knickzones use a reproducible method of quantifying their locations, as their number and spatial distribution play an important role in interpreting tectonically active landscapes. In this contribution we introduce a reproducible knickpoint and knickzone extraction algorithm that uses river profiles transformed by integrating drainage area along channel length (the so-called integral or χ method). The profile is then statistically segmented and the differing slopes and step changes in elevations of these segments are used to identify knickpoints and knickzones, and their relative magnitudes. The output locations of identified knickpoints and knickzones compare favourably with human mapping: we test the method on Santa Cruz Island, CA, using previously reported knickzones and also test the method against a new dataset from the Quadrilátero Ferrífero in Brazil. The algorithm allows extraction of varying knickpoint morphologies, including stepped, positive slope-breaks (concave upward) and negative slope-break knickpoints. We identify parameters that most affect the resulting knickpoint and knickzone locations, and provide guidance for both usage and outputs of the method to produce reproducible knickpoint datasets.

Boris Gailleton et al.
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Boris Gailleton et al.
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Short summary
The shape of landscapes is influenced by climate changes, faulting or the nature of the rocks under its surface. One of the most sensitive part of the landscape to these changes is the river system that eventually adapt to such changes by adapting its slope, the most extreme example being a waterfall. We here present an algorithm that extract changes in river slope over large areas from satellite data in the aim of investigate climatic, tectonic or geologic changes in the landscape.
The shape of landscapes is influenced by climate changes, faulting or the nature of the rocks...
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