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Abstract
We present a statistical technique for analyzing longitudinal channel profiles. Our technique is based on the integral approach to channel analysis: Drainage area is integrated over flow distance to produce a transformed coordinate, χ, which has dimensions of length. Assuming that profile geometry is conditioned by the stream power law, defined as E = KAmSn where E is erosion rate, K is erodibility, A is drainage area, S is channel gradient, and m and n are constants, the slope of a transformed profile in χelevation space should reflect the ratio of erosion rate to channel erodibility raised to a power 1/n; this quantity is often referred to as the channel steepness and represents channel slope normalized for drainage area. Our technique tests all possible contiguous segments in the channel network to identify the most likely locations where channel steepness changes and also identifies the most likely m/n ratio. The technique identifies locations where either erodibility or erosion rates are most likely to be changing. Tests on a simulated landscape demonstrate that the technique can accurately retrieve both the m/n ratio and the correct number and location of segments eroding at different rates where model assumptions apply. Tests on natural landscapes illustrate how the method can distinguish between spurious channel convexities due to incorrect selection of the m/n ratio from those which are candidates for changing erodibility or erosion rates. We also show how, given erosion or uplift rate constraints, the method can be used to constrain the slope exponent, n.
Original language  English 

Pages (fromto)  138–152 
Journal  Journal of Geophysical Research: Earth Surface 
Volume  119 
Issue number  2 
Early online date  10 Dec 2013 
DOIs  
Publication status  Published  17 Mar 2014 
Keywords
 bedrock channels;topographic analysis;landscape evolution
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Dive into the research topics of 'A statistical framework to quantify spatial variation in channel gradients using the integral method of channel profile analysis'. Together they form a unique fingerprint.Projects
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Simon Mudd
 School of Geosciences  Personal Chair in Earth Surface Processes
Person: Academic: Research Active