Objective extraction of channel heads from high-resolution topographic data

Clubb, Fiona J.; Mudd, Simon M.; Milodowski, David T.; Hurst, Martin D.; Slater, Louise J.. 2014 Objective extraction of channel heads from high-resolution topographic data. Water Resources Research, 50 (5). 4283-4304.

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Fluvial landscapes are dissected by channels, and at their upstream termini are channel heads. Accurate reconstruction of the fluvial domain is fundamental to understanding runoff generation, storm hydrology, sediment transport, biogeochemical cycling, and landscape evolution. Many methods have been proposed for predicting channel head locations using topographic data, yet none have been tested against a robust field data set of mapped channel heads across multiple landscapes. In this study, four methods of channel head prediction were tested against field data from four sites with high-resolution DEMs: slope-area scaling relationships; two techniques based on landscape tangential curvature; and a new method presented here, which identifies the change from channel to hillslope topography along a profile using a transformed longitudinal coordinate system. Our method requires only two user-defined parameters, determined via independent statistical analysis. Slope-area plots are traditionally used to identify the fluvial-hillslope transition, but we observe no clear relationship between this transition and field-mapped channel heads. Of the four methods assessed, one of the tangential curvature methods and our new method most accurately reproduce the measured channel heads in all four field sites (Feather River CA, Mid Bailey Run OH, Indian Creek OH, Piedmont VA), with mean errors of −11, −7, 5, and −24 m and 34, 3, 12, and −58 m, respectively. Negative values indicate channel heads located upslope of those mapped in the field. Importantly, these two independent methods produce mutually consistent estimates, providing two tests of channel head locations based on independent topographic signatures.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 00431397
Date made live: 08 Aug 2014 09:06 +0 (UTC)

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