DrEICH algorithm 

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, 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 dataset 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; GeoNet 2.0; a contour curvature technique proposed by Pelletier [2013]; 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 the field-mapped channel heads. Of the four methods assessed, Pelletier’s [2013] tangential curvature method 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 meters and 34, 3, 12 and −58 meters 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.

Clubb, Fiona; Mudd, Simon; Milodowski, David; Hurst, Martin; Slater, Louise. (2014). DrEICH algorithm, 2012-2013 [Dataset]. University of Edinburgh. School of GeoSciences. http://dx.doi.org/10.7488/ds/3.