Articles | Volume 7, issue 2
https://doi.org/10.5194/esurf-7-591-2019
https://doi.org/10.5194/esurf-7-591-2019
Research article
 | 
26 Jun 2019
Research article |  | 26 Jun 2019

A coupled soilscape–landform evolution model: model formulation and initial results

W. D. Dimuth P. Welivitiya, Garry R. Willgoose, and Greg R. Hancock

Related authors

Introducing Iterative Model Calibration (IMC) v1.0: a generalizable framework for numerical model calibration with a CAESAR-Lisflood case study
Chayan Banerjee, Kien Nguyen, Clinton Fookes, Gregory Hancock, and Thomas Coulthard
Geosci. Model Dev., 18, 803–818, https://doi.org/10.5194/gmd-18-803-2025,https://doi.org/10.5194/gmd-18-803-2025, 2025
Short summary
Catchment-scale drought: capturing the whole drought cycle using multiple indicators
Abraham J. Gibson, Danielle C. Verdon-Kidd, Greg R. Hancock, and Garry Willgoose
Hydrol. Earth Syst. Sci., 24, 1985–2002, https://doi.org/10.5194/hess-24-1985-2020,https://doi.org/10.5194/hess-24-1985-2020, 2020
Short summary
Using paleoclimate reconstructions to analyse hydrological epochs associated with Pacific decadal variability
Lanying Zhang, George Kuczera, Anthony S. Kiem, and Garry Willgoose
Hydrol. Earth Syst. Sci., 22, 6399–6414, https://doi.org/10.5194/hess-22-6399-2018,https://doi.org/10.5194/hess-22-6399-2018, 2018
Short summary
Global sensitivity analysis of parameter uncertainty in landscape evolution models
Christopher J. Skinner, Tom J. Coulthard, Wolfgang Schwanghart, Marco J. Van De Wiel, and Greg Hancock
Geosci. Model Dev., 11, 4873–4888, https://doi.org/10.5194/gmd-11-4873-2018,https://doi.org/10.5194/gmd-11-4873-2018, 2018
Short summary
Development and evaluation of a stochastic daily rainfall model with long-term variability
A. F. M. Kamal Chowdhury, Natalie Lockart, Garry Willgoose, George Kuczera, Anthony S. Kiem, and Nadeeka Parana Manage
Hydrol. Earth Syst. Sci., 21, 6541–6558, https://doi.org/10.5194/hess-21-6541-2017,https://doi.org/10.5194/hess-21-6541-2017, 2017
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

Agrawal, Y. C., Mikkelsen, O. A., and Pottsmith, H.: Grain size distribution and sediment flux structure in a river profile, measured with a LISST-SL Instrument, Sequoia Scientific, Inc. Report, 2012. 
Ahnert, F.: Some comments on the quantitative formulation of geomorphological processes in a theoretical model, Earth Surf. Process., 2, 191–201, https://doi.org/10.1002/esp.3290020211, 1977. 
Arya, L. M. and Paris, J. F.: A physicoempirical model to predict the soil moisture characteristic from particle-size distribution and bulk density data, Soil Sci. Soc. Am. J., 45, 1023–1030, 1981. 
Behrens, T. and Scholten, T.: Digital soil mapping in Germany – a review, J. Plant Nut. Soil Sci., 169, 434–443, https://doi.org/10.1002/jpln.200521962, 2006. 
Benites, V. M., Machado, P. L. O. A., Fidalgo, E. C. C., Coelho, M. R., and Madari, B. E.: Pedotransfer functions for estimating soil bulk density from existing soil survey reports in Brazil, Geoderma, 139, 90–97, https://doi.org/10.1016/j.geoderma.2007.01.005, 2007. 
Download
Short summary
The paper describes a model that simultaneously evolves both the soil profile and the landform, creating a coupled soilscape–landscape evolution model. The physics in the model is presented and justified from physical processes. The behaviour of the model is then explored for a variety of process formulations for a one-dimensional hillslope consisting of a flat upslope, steep midslope, and flat lowlands, exploring the erosion and deposition behaviour, and soil profile evolution over time.
Share