Articles | Volume 5, issue 4
Research article
07 Dec 2017
Research article |  | 07 Dec 2017

Bumps in river profiles: uncertainty assessment and smoothing using quantile regression techniques

Wolfgang Schwanghart and Dirk Scherler

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Cited articles

Ahuja, R. K., Magnanti, T. L., and Orlin, J. B.: Network flows: theory, algorithms, and applications, Prentice Hall, New Jersey, 1993.
Aiken, S. J. and Brierley, G. J.: Analysis of longitudinal profiles along the eastern margin of the Qinghai-Tibetan Plateau, J. Mt. Sci., 10, 643–657,, 2013.
Baade, J. and Schmullius, C.: Uncertainties of a TanDEM-X derived Digital Surface Model: A case study from the Roda catchment, Germany, in: Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International, 4327–4330, 2014.
Bishop, P., Hoey, T. B., Jansen, J. D., and Artza, I. L.: Knickpoint recession rate and catchment area: the case of uplifted rivers in Eastern Scotland, Earth Surf. Process. Landf., 30, 767–778,, 2005.
Brardinoni, F. and Hassan, M. A.: Glacial erosion, evolution of river long profiles, and the organization of process domains in mountain drainage basins of coastal British Columbia, J. Geophys. Res., 111, F01013–F01013, 2006.
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.