Journal metrics

Journal metrics

  • IF value: 3.176 IF 3.176
  • IF 5-year value: 3.108 IF 5-year 3.108
  • CiteScore value: 3.06 CiteScore 3.06
  • SNIP value: 0.978 SNIP 0.978
  • SJR value: 1.421 SJR 1.421
  • IPP value: 2.88 IPP 2.88
  • h5-index value: 13 h5-index 13
  • Scimago H index value: 13 Scimago H index 13
Volume 4, issue 3 | Copyright
Earth Surf. Dynam., 4, 757-771, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 30 Sep 2016

Research article | 30 Sep 2016

The sensitivity of landscape evolution models to spatial and temporal rainfall resolution

Tom J. Coulthard and Christopher J. Skinner
Related authors
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. Discuss.,,, 2017
Revised manuscript accepted for GMD
Flood modeling can make a difference: Disaster risk-reduction and resilience-building in urban areas
Jorge A. Ramirez, Umamaheshwaran Rajasekar, Dhruvesh P. Patel, Tom J. Coulthard, and Margreth Keiler
Hydrol. Earth Syst. Sci. Discuss.,,, 2016
Publication in HESS not foreseen
Climate, tectonics or morphology: what signals can we see in drainage basin sediment yields?
T. J. Coulthard and M. J. Van de Wiel
Earth Surf. Dynam., 1, 13-27,,, 2013
Related subject area
Physical: Landscape Evolution: modelling and field studies
A lattice grain model of hillslope evolution
Gregory E. Tucker, Scott W. McCoy, and Daniel E. J. Hobley
Earth Surf. Dynam., 6, 563-582,,, 2018
On the Holocene evolution of the Ayeyawady megadelta
Liviu Giosan, Thet Naing, Myo Min Tun, Peter D. Clift, Florin Filip, Stefan Constantinescu, Nitesh Khonde, Jerzy Blusztajn, Jan-Pieter Buylaert, Thomas Stevens, and Swe Thwin
Earth Surf. Dynam., 6, 451-466,,, 2018
Scaling and similarity of a stream-power incision and linear diffusion landscape evolution model
Nikos Theodoratos, Hansjörg Seybold, and James W. Kirchner
Earth Surf. Dynam. Discuss.,,, 2018
Revised manuscript accepted for ESurf
Morphological effects of vegetation on the fluvial-tidal transition in Holocene estuaries
Ivar Lokhorst, Lisanne Braat, Jasper R. F. W. Leuven, Anne W. Baar, Mijke van Oorschot, Sanja Selaković, and Maarten G. Kleinhans
Earth Surf. Dynam. Discuss.,,, 2018
Revised manuscript accepted for ESurf
Numerical modelling of landscape and sediment flux response to precipitation rate change
John J. Armitage, Alexander C. Whittaker, Mustapha Zakari, and Benjamin Campforts
Earth Surf. Dynam., 6, 77-99,,, 2018
Cited articles
Andréassian, V., Perrin, C., Michel, C., Usart-Sanchez, I., and Lavabre, J.: Impact of imperfect rainfall knowledge on the efficiency and the parameters of watershed models, J. Hydrol., 250, 206–223,, 2001.
Andréassian, V., Le Moine, N., Perrin, C., Ramos, M.-H., Oudin, L., Mathevet, T., Lerat, J., and Berthet, L.: All that glitters is not gold: the case of calibrating hydrological models, Hydrol. Process., 26, 2206–2210,, 2012.
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,, 2010.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36,, 2006.
Beven, K. and Hornberger, G.: Assessing the Effect of Spatial Pattern of Precipitation in Modeling Stream Flow Hydrographs1, Water Resour. Bull., 18, 823–829,, 1982.
Publications Copernicus
Short summary
Landscape evolution models are driven by climate or precipitation data. We show that higher-resolution data lead to greater basin sediment yields (> 100 % increase) despite minimal changes in hydrological outputs. Spatially, simulations over 1000 years show finer-resolution data lead to a systematic bias of more erosion in headwater streams with more deposition in valley floors. This could have important implications for the long-term predictions of past and present landscape evolution models.
Landscape evolution models are driven by climate or precipitation data. We show that...