Articles | Volume 13, issue 1
https://doi.org/10.5194/esurf-13-191-2025
https://doi.org/10.5194/esurf-13-191-2025
Research article
 | 
07 Feb 2025
Research article |  | 07 Feb 2025

Investigating uncertainty and parameter sensitivity in bedform analysis by using a Monte Carlo approach

Julius Reich and Axel Winterscheid

Related subject area

Physical: Geomorphology (including all aspects of fluvial, coastal, aeolian, hillslope and glacial geomorphology)
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
Geomorphic imprint of high-mountain floods: insights from the 2022 hydrological extreme across the upper Indus River catchment in the northwestern Himalayas
Abhishek Kashyap, Kristen L. Cook, and Mukunda Dev Behera
Earth Surf. Dynam., 13, 147–166, https://doi.org/10.5194/esurf-13-147-2025,https://doi.org/10.5194/esurf-13-147-2025, 2025
Short summary
A numerical model for duricrust formation by water table fluctuations
Caroline Fenske, Jean Braun, François Guillocheau, and Cécile Robin
Earth Surf. Dynam., 13, 119–146, https://doi.org/10.5194/esurf-13-119-2025,https://doi.org/10.5194/esurf-13-119-2025, 2025
Short summary
Width evolution of channel belts as a random walk
Jens M. Turowski, Fergus McNab, Aaron Bufe, and Stefanie Tofelde
Earth Surf. Dynam., 13, 97–117, https://doi.org/10.5194/esurf-13-97-2025,https://doi.org/10.5194/esurf-13-97-2025, 2025
Short summary
Evidence of slow millennial cliff retreat rates using cosmogenic nuclides in coastal colluvium
Rémi Bossis, Vincent Regard, Sébastien Carretier, and Sandrine Choy
Earth Surf. Dynam., 13, 71–79, https://doi.org/10.5194/esurf-13-71-2025,https://doi.org/10.5194/esurf-13-71-2025, 2025
Short summary

Cited articles

Adekitan, A. I.: Monte Carlo Simulation, ResearchGate, https://doi.org/10.13140/RG.2.2.15207.16806, 2014. 
BfG: Sedimentologisch-Morphologische Untersuchung des Niederrheins, BfG 1768, 32, 2011. 
Carling, P., Gölz, E., Orr, H., and Radecki-Pawlik, A.: The morphodynamics of fluvial sand dunes in the River Rhine, near Mainz, Germany, I, Sedimentology and morphology, Sedimentology, 47, 227–252, https://doi.org/10.1046/j.1365-3091.2000.00290.x, 2006. 
Cisneros, J., Best, J., van Dijk, T., Almeida, R. P. D., Amsler, M., and Boldt, J.: Dunes in the world's big rivers are characterized by low-angle lee-side slopes and a complex shape, Nat. Geosci., 13, 156–162, https://doi.org/10.1038/s41561-019-0511-7, 2020. 
Claude, N., Rodrigues, S., Bustillo, V., Bréhéret, J., Macaire, J., and Jugé, P.: Estimating bedload transport in a large sand–gravel bed river from direct sampling, dune tracking and empirical formulas, Geomorphology, 179, 40–57, https://doi.org/10.1016/j.geomorph.2012.07.030, 2012. 
Download
Short summary
Analyzing the geometry and the dynamics of riverine bedforms (so-called dune tracking) is important for various fields of application and contributes to sound and efficient river and sediment management. We developed a workflow that enables a robust estimation of bedform characteristics and with which comprehensive sensitivity analyses can be carried out. Using a field dataset, we show that the setting of input parameters in bedform analyses can have a significant impact on the results.

Share