Articles | Volume 11, issue 4
https://doi.org/10.5194/esurf-11-695-2023
https://doi.org/10.5194/esurf-11-695-2023
Research article
 | 
28 Jul 2023
Research article |  | 28 Jul 2023

Testing the sensitivity of the CAESAR-Lisflood landscape evolution model to grid cell size

Christopher J. Skinner and Thomas J. Coulthard

Related authors

Localised geomorphic response to channel-spanning leaky wooden dams
Joshua M. Wolstenholme, Christopher J. Skinner, David J. Milan, Robert E. Thomas, and Daniel R. Parsons
EGUsphere, https://doi.org/10.5194/egusphere-2024-3001,https://doi.org/10.5194/egusphere-2024-3001, 2024
This preprint is open for discussion and under review for Earth Surface Dynamics (ESurf).
Short summary
Hydro-geomorphological modelling of leaky wooden dam efficacy from reach to catchment scale with CAESAR-Lisflood 1.9j
Joshua M. Wolstenholme, Christopher J. Skinner, David J. Milan, Robert E. Thomas, and Daniel R. Parsons
EGUsphere, https://doi.org/10.5194/egusphere-2024-2132,https://doi.org/10.5194/egusphere-2024-2132, 2024
Short summary
Flash Flood!: a SeriousGeoGames activity combining science festivals, video games, and virtual reality with research data for communicating flood risk and geomorphology
Chris Skinner
Geosci. Commun., 3, 1–17, https://doi.org/10.5194/gc-3-1-2020,https://doi.org/10.5194/gc-3-1-2020, 2020
Short summary
Temperature effects on the spatial structure of heavy rainfall modify catchment hydro-morphological response
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020,https://doi.org/10.5194/esurf-8-17-2020, 2020
Short summary
Taking a Breath of the Wild: are geoscientists more effective than non-geoscientists in determining whether video game world landscapes are realistic?
Rolf Hut, Casper Albers, Sam Illingworth, and Chris Skinner
Geosci. Commun., 2, 117–124, https://doi.org/10.5194/gc-2-117-2019,https://doi.org/10.5194/gc-2-117-2019, 2019
Short summary

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
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
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

Cited articles

Bates, P. D., Horritt, M. S., and Fewtrell, T. J.: A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling, J. Hydrol., 387, 33–45, https://doi.org/10.1016/j.jhydrol.2010.03.027, 2010. 
Beven, K. and Kirkby, M.: A physically based, variable contributing area model of basin hydrology/Un modèèle à base physique de zone d'appel variable de l'hydrologie du bassin versant, Hydrolog. Sci. J., 24, 37–41 https://doi.org/10.1080/02626667909491834, 1979. 
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Model. Softw., 22, 1509–1518, https://doi.org/10.1016/j.envsoft.2006.10.004, 2007. 
Claessens, L., Heuvelink, G. B. M., Schoorl, J. M., and Veldkamp, A.: DEM resolution effects on shallow landslide hazard and soil redistribution modelling, Earth Surf. Proc. Land., 30, 461–477, https://doi.org/10.1002/esp.1155, 2005. 
Coulthard, T. J.: CAESAR-Lisflood 1.9b SOURCE.zip, CAESAR-Lisflood Files, SourceForge, https://sourceforge.net/projects/caesar-lisflood/files/CAESAR-lisflood 1.9b SOURCE.zip/download (last access: 24 July 2023), 2016. 
Download
Short summary
Landscape evolution models allow us to simulate the way the Earth's surface is shaped and help us to understand relevant processes, in turn helping us to manage landscapes better. The models typically represent the land surface using a grid of square cells of equal size, averaging heights in those squares. This study shows that the size chosen by the modeller for these grid cells is important, with larger sizes making sediment output events larger but less frequent.
Share