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Uncertainty Assessment

  • Richard E. Brazier
  • Tobias Krueger
  • John Wainwright
Chapter

Abstract

A number of traditional concerns as well as outside pressures on scientific understanding have led to the underplaying of uncertainty. Land-degradation studies are by no means alone in assuming that if the problem of uncertainty is ignored, it will go away. We demonstrate that such a head-in-the-sand approach is fallacious, as uncertainty underpins all our scientific activity. Field measurements and empirical observations are no less exempt than complicated numerical models. Uncertainty can be distinguished as being aleatory, or due to inherent variability, or epistemic, as a result of uncertain knowledge, although in reality both types are intimately related. Model parameters reflect the underpinning conceptual models in a discipline, and as those conceptual models change, parameter measurements may also need to change. Taking account of all of the sources of variability in measurement is critical, though, in ensuring that we do not reject models for the wrong reasons. A structure is presented for addressing uncertainty propagation in models using intervals, fuzzy membership functions and probability distributions in conjunction with stochastic simulation. The effects of model structural uncertainty are considered within a variety of Bayesian frameworks, and their relative strengths and weaknesses addressed. All aspects of uncertainty must be considered if we are to develop robust models of land degradation that incorporate ecogeomorphic feedbacks and human activity.

Keywords

Land Degradation Stochastic Simulation Fuzzy Membership Function Epistemic Uncertainty Data Uncertainty 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This chapter is a contribution to the book Patterns of Land Degradation in Drylands: Understanding Self-Organised Ecogeomorphic Systems, which is the outcome of an ESF-funded Exploratory Workshop – “Self-organized ecogeomorphic systems: confronting models with data for land degradation in drylands” – which was held in Potsdam, Germany, 7–10 June 2010. TK was supported by a UK Natural Environment Research Council Knowledge Exchange Fellowship (grant no. NE/J500513/1) during the writing of this chapter.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Richard E. Brazier
    • 1
  • Tobias Krueger
    • 2
  • John Wainwright
    • 3
  1. 1.Geography, College of Life and Environmental SciencesUniversity of ExeterExeterUK
  2. 2.School of Environmental SciencesUniversity of East AngliaNorwichUK
  3. 3.Department of GeographyUniversity of DurhamDurhamUK

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