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. Changes in the steepness of river profiles or abrupt verticalsteps (i.e. waterfalls) are thought to be indicative of changes in erosionrates, lithology or other factors that affect landscape evolution. Thesechanges are referred to as knickpoints or knickzones and are pervasive inbedrock river systems. Such features are thought to reveal information aboutlandscape evolution and patterns of erosion, and therefore their locationsare often reported in the geomorphic literature. It is imperative thatstudies reporting knickpoints and knickzones use a reproducible method ofquantifying their locations, as their number and spatial distribution play animportant role in interpreting tectonically active landscapes. In thiscontribution we introduce a reproducible knickpoint and knickzone extractionalgorithm that uses river profiles transformed by integrating drainage areaalong channel length (the so-called integral or χ method). The profileis then statistically segmented and the differing slopes and step changesin theelevations of these segments are used to identify knickpoints, knickzonesand their relative magnitudes. The output locations of identified knickpointsand knickzones compare favourably with human mapping: we test the method onSanta Cruz Island, CA, using previously reported knickzones and also test themethod against a new dataset from the Quadrilatero Ferrifero inBrazil. The algorithm allows for the extraction of varying knickpoint morphologies,including stepped, positive slope-break (concave upward) and negativeslope-break knickpoints. We identify parameters that most affect theresulting knickpoint and knickzone locations and provide guidance for bothusage and outputs of the method to produce reproducible knickpoint datasets.

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