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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union

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Earth Surf. Dynam., 5, 821-839, 2017
https://doi.org/10.5194/esurf-5-821-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
07 Dec 2017
Bumps in river profiles: uncertainty assessment and smoothing using quantile regression techniques
Wolfgang Schwanghart1 and Dirk Scherler2,3 1University of Potsdam, Institute of Earth and Environmental Science, 14476 Potsdam-Golm, Germany
2GFZ German Research Centre for Geosciences, Earth Surface Geochemistry, 14473 Potsdam, Germany
3Freie Universität Berlin, Institute for Geological Sciences, 12249 Berlin, Germany
Abstract. The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms – quantile carving and the CRS algorithm – that rely on quantile regression to enable hydrological correction and the uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12 m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.

Citation: Schwanghart, W. and Scherler, D.: Bumps in river profiles: uncertainty assessment and smoothing using quantile regression techniques, Earth Surf. Dynam., 5, 821-839, https://doi.org/10.5194/esurf-5-821-2017, 2017.
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Short summary
River profiles derived from digital elevation models are affected by errors. Here we present two new algorithms – quantile carving and the CRS algorithm – to hydrologically correct river profiles. Both algorithms preserve the downstream decreasing shape of river profiles, while CRS additionally smooths profiles to avoid artificial steps. Our algorithms are able to cope with the problems of overestimation and asymmetric error distributions.
River profiles derived from digital elevation models are affected by errors. Here we present two...
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