Articles | Volume 5, issue 3
https://doi.org/10.5194/esurf-5-557-2017
https://doi.org/10.5194/esurf-5-557-2017
Research article
 | 
14 Sep 2017
Research article |  | 14 Sep 2017

Deriving principal channel metrics from bank and long-profile geometry with the R package cmgo

Antonius Golly and Jens M. Turowski

Related authors

Differential climate impacts for policy-relevant limits to global warming: the case of 1.5 °C and 2 °C
Carl-Friedrich Schleussner, Tabea K. Lissner, Erich M. Fischer, Jan Wohland, Mahé Perrette, Antonius Golly, Joeri Rogelj, Katelin Childers, Jacob Schewe, Katja Frieler, Matthias Mengel, William Hare, and Michiel Schaeffer
Earth Syst. Dynam., 7, 327–351, https://doi.org/10.5194/esd-7-327-2016,https://doi.org/10.5194/esd-7-327-2016, 2016
Short summary

Related subject area

Physical: Geomorphology (including all aspects of fluvial, coastal, aeolian, hillslope and glacial geomorphology)
Haloturbation in the northern Atacama Desert revealed by a hidden subsurface network of calcium sulfate wedges
Aline Zinelabedin, Joel Mohren, Maria Wierzbicka-Wieczorek, Tibor Janos Dunai, Stefan Heinze, and Benedikt Ritter
Earth Surf. Dynam., 13, 257–276, https://doi.org/10.5194/esurf-13-257-2025,https://doi.org/10.5194/esurf-13-257-2025, 2025
Short summary
An evaluation of flow-routing algorithms for calculating contributing area on regular grids
Alexander B. Prescott, Jon D. Pelletier, Satya Chataut, and Sriram Ananthanarayan
Earth Surf. Dynam., 13, 239–256, https://doi.org/10.5194/esurf-13-239-2025,https://doi.org/10.5194/esurf-13-239-2025, 2025
Short summary
Geometric constraints on tributary fluvial network junction angles
Jon D. Pelletier, Robert G. Hayes, Olivia Hoch, Brendan Fenerty, and Luke A. McGuire
Earth Surf. Dynam., 13, 219–238, https://doi.org/10.5194/esurf-13-219-2025,https://doi.org/10.5194/esurf-13-219-2025, 2025
Short summary
Automatic detection of floating instream large wood in videos using deep learning
Janbert Aarnink, Tom Beucler, Marceline Vuaridel, and Virginia Ruiz-Villanueva
Earth Surf. Dynam., 13, 167–189, https://doi.org/10.5194/esurf-13-167-2025,https://doi.org/10.5194/esurf-13-167-2025, 2025
Short summary
Investigating uncertainty and parameter sensitivity in bedform analysis by using a Monte Carlo approach
Julius Reich and Axel Winterscheid
Earth Surf. Dynam., 13, 191–217, https://doi.org/10.5194/esurf-13-191-2025,https://doi.org/10.5194/esurf-13-191-2025, 2025
Short summary

Cited articles

Ackerman, P. E. C. T.: HEC-GeoRAS GIS Tools for Support of HEC-RAS using ArcGIS User's Manual, USArmy Corps of Engineers, Davis, California, p. 244, 2011.
Amit: Estimating river Channel Width using Python/ArcGIS/MATLAB/R?, available at: http://gis.stackexchange.com/questions/164169/estimating-river-channel-width-using-python-arcgis-matlab-r (last access: 14 March 2017), 2015.
Asterics: Software-Handbuch ASTERICS, Version 4.1, 1–120, available at: http://www.fliessgewaesserbewertung.de/downloads/ASTERICS_Softwarehandbuch_Version4.pdf (last access: 13 September 2017), 2013.
Cook, K. L., Turowski, J. M., and Hovius, N.: River gorge eradication by downstream sweep erosion, Nat. Geosci., 7, 682–686, https://doi.org/10.1038/ngeo2224, 2014.
Dilts, T. E.: Polygon to Centerline Tool for ArcGIS, University of Nevada, Reno, available at: http://www.arcgis.com/home/item.html?id=bc642731870740aabf48134f90aa6165 (last access: 15 March 2017), 2015.
Download
Short summary
Researchers of fluvial geomorphology require reliable information on channel width and its change in space and time. For example, to study bank erosion rates we need the local position of channel banks before and after a high flood event. Although deriving these metrics seems simple, researchers often use manual or arbitrary approaches that are not objective and reproducible. Here, we present an open-source software tool cmgo (R package) that meets the requirements of academic research.
Share