Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-4873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
06 Dec 2018
Model evaluation paper |
| 06 Dec 2018
| 06 Dec 2018
Global sensitivity analysis of parameter uncertainty in landscape evolution models
Christopher J. Skinner
CORRESPONDING AUTHOR
School of Environmental Sciences, University of Hull, Hull, UK
Tom J. Coulthard
School of Environmental Sciences, University of Hull, Hull, UK
Wolfgang Schwanghart
Institute of Earth and Environmental Science, Potsdam University,
Potsdam-Golm, Germany
Marco J. Van De Wiel
Centre for Agroecology, Water and Resilience, Coventry University,
Coventry, UK
Greg Hancock
University of Newcastle, Callaghan, Australia
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31 citations as recorded by crossref.
- Testing the sensitivity of the CAESAR-Lisflood landscape evolution model to grid cell size C. Skinner & T. Coulthard 10.5194/esurf-11-695-2023
- Modelling headwater channel response and suspended sediment yield to in-channel large wood using the Caesar-Lisflood landscape evolution model P. Walsh et al. 10.1016/j.geomorph.2020.107209
- Inverting Topography for Landscape Evolution Model Process Representation: 2. Calibration and Validation K. Barnhart et al. 10.1029/2018JF004963
- Influence of different sources of topographic data on flood mapping: urban area São Vendelino municipality, southern Brazil F. Zambrano et al. 10.1590/2318-0331.252020190108
- An assessment of short–medium-term interventions using CAESAR-Lisflood in a post-earthquake mountainous area D. Wang et al. 10.5194/nhess-23-1409-2023
- The impact of sediment flux and calibre on flood risk in the Kathmandu Valley, Nepal S. Thapa et al. 10.1002/esp.5731
- Introducing Iterative Model Calibration (IMC) v1.0: a generalizable framework for numerical model calibration with a CAESAR-Lisflood case study C. Banerjee et al. 10.5194/gmd-18-803-2025
- Inverting Topography for Landscape Evolution Model Process Representation: 1. Conceptualization and Sensitivity Analysis K. Barnhart et al. 10.1029/2018JF004961
- Testing the Prediction Ability of LEM-Derived Sedimentary Budget in an Upland Catchment of the Southern Apennines, Italy: A Source to Sink Approach D. Gioia & M. Lazzari 10.3390/w11050911
- On the main components of landscape evolution modelling of river systems M. Nones 10.1007/s11600-020-00401-8
- Assessment of the geomorphic effectiveness of controlled floods in a braided river using a reduced-complexity numerical model L. Ziliani et al. 10.5194/hess-24-3229-2020
- Predicting gully erosion using landform evolution models: Insights from mining landforms G. Hancock & G. Willgoose 10.1002/esp.5234
- Hillslope and catchment scale landform evolution – Predicting catchment form and surface properties W. Welivitiya & G. Hancock 10.1016/j.envsoft.2023.105725
- The Coastline Evolution Model 2D (CEM2D) V1.1 C. Leach et al. 10.5194/gmd-14-5507-2021
- Impact of vegetation cover on hydro-sedimentary fluxes in the marly badlands of the Southern Alps (Draix-Bléone Critical Zone Observatory, SE France) R. Bunel et al. 10.1016/j.geomorph.2025.109726
- Study on the habitat evolution after dam removal in a habitat-alternative tributary of large hydropower station Z. Wang et al. 10.1016/j.jenvman.2024.121155
- A Shear Reynolds Number-Based Classification Method of the Nonuniform Bed Load Transport G. Török et al. 10.3390/w11010073
- Assessing the hydrological and geomorphic behaviour of a landscape evolution model within a limits‐of‐acceptability uncertainty analysis framework J. Wong et al. 10.1002/esp.5140
- Hydro-geomorphological modelling of leaky wooden dam efficacy from reach to catchment scale with CAESAR-Lisflood 1.9j J. Wolstenholme et al. 10.5194/gmd-18-1395-2025
- Landscape evolution of the Wenchuan earthquake-stricken area in response to future climate change C. Li et al. 10.1016/j.jhydrol.2020.125244
- Climate Change Impacts on Sediment Yield and Debris‐Flow Activity in an Alpine Catchment J. Hirschberg et al. 10.1029/2020JF005739
- Modelling the long-term geomorphic response to check dam failures in an alpine channel with CAESAR-Lisflood J. Ramirez et al. 10.1016/j.ijsrc.2022.04.005
- How does landslide debris grain size control sediment transport and dynamics? J. Xie et al. 10.1016/j.geomorph.2023.109050
- Increased erosion in a pre-Alpine region contrasts with a future decrease in precipitation and snowmelt T. Cache et al. 10.1016/j.geomorph.2023.108782
- Constraining Plateau Uplift in Southern Africa by Combining Thermochronology, Sediment Flux, Topography, and Landscape Evolution Modeling J. Stanley et al. 10.1029/2020JB021243
- Temperature effects on the spatial structure of heavy rainfall modify catchment hydro-morphological response N. Peleg et al. 10.5194/esurf-8-17-2020
- Effects of climate variability changes on runoff and erosion in the Western European Loess Belt region (NW, France) R. Bunel et al. 10.1016/j.scitotenv.2023.166536
- Modeling the impact of dam removal on channel evolution and sediment delivery in a multiple dam setting R. Poeppl et al. 10.1016/j.ijsrc.2019.06.001
- Basin analysis palaeo‐landscape modelling: Testing the critical controls using experimental design constrained by a real 3D geological model, Gippsland Basin, Australia X. Yang et al. 10.1111/bre.12710
- Paleotopography-constrained numerical modeling of loess landform evolution Y. Wang et al. 10.1016/j.geomorph.2023.108725
- Modeling Short-Term Landscape Modification and Sedimentary Budget Induced by Dam Removal: Insights from LEM Application D. Gioia & M. Schiattarella 10.3390/app10217697
Latest update: 14 May 2025
Short summary
Landscape evolution models are computer models used to understand how the Earth’s surface changes over time. Although designed to look at broad changes over very long time periods, they could potentially be used to predict smaller changes over shorter periods. However, to do this we need to better understand how the models respond to changes in their set-up – i.e. their behaviour. This work presents a method which can be applied to these models in order to better understand their behaviour.
Landscape evolution models are computer models used to understand how the Earth’s surface...
