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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 12
Geosci. Model Dev., 11, 4873-4888, 2018
https://doi.org/10.5194/gmd-11-4873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 11, 4873-4888, 2018
https://doi.org/10.5194/gmd-11-4873-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model evaluation paper 06 Dec 2018

Model evaluation paper | 06 Dec 2018

Global sensitivity analysis of parameter uncertainty in landscape evolution models

Christopher J. Skinner1, Tom J. Coulthard1, Wolfgang Schwanghart2, Marco J. Van De Wiel3, and Greg Hancock4 Christopher J. Skinner et al.
  • 1School of Environmental Sciences, University of Hull, Hull, UK
  • 2Institute of Earth and Environmental Science, Potsdam University, Potsdam-Golm, Germany
  • 3Centre for Agroecology, Water and Resilience, Coventry University, Coventry, UK
  • 4University of Newcastle, Callaghan, Australia

Abstract. The evaluation and verification of landscape evolution models (LEMs) has long been limited by a lack of suitable observational data and statistical measures which can fully capture the complexity of landscape changes. This lack of data limits the use of objective function based evaluation prolific in other modelling fields, and restricts the application of sensitivity analyses in the models and the consequent assessment of model uncertainties. To overcome this deficiency, a novel model function approach has been developed, with each model function representing an aspect of model behaviour, which allows for the application of sensitivity analyses. The model function approach is used to assess the relative sensitivity of the CAESAR-Lisflood LEM to a set of model parameters by applying the Morris method sensitivity analysis for two contrasting catchments. The test revealed that the model was most sensitive to the choice of the sediment transport formula for both catchments, and that each parameter influenced model behaviours differently, with model functions relating to internal geomorphic changes responding in a different way to those relating to the sediment yields from the catchment outlet. The model functions proved useful for providing a way of evaluating the sensitivity of LEMs in the absence of data and methods for an objective function approach.

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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...
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