Preprints
https://doi.org/10.5194/hess-2022-349
https://doi.org/10.5194/hess-2022-349
 
17 Nov 2022
17 Nov 2022
Status: this preprint is currently under review for the journal HESS.

Technical Note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty

Trevor Page1, Paul Smith1,2, Keith Beven1, Francesca Pianosi3, Fanny Sarrazin4, Susana Almeida5, Liz Holcombe3, Jim Freer6, and Thorsten Wagener7 Trevor Page et al.
  • 1Lancaster Environment Centre, Lancaster University, Lancaster, UK
  • 2Waternumbers, Lancaster, UK
  • 3Department of Civil Engineering, Bristol University, Bristol, UK
  • 4Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
  • 5Atkins Global, Bristol, UK
  • 6School of Geographical Sciences, Bristol University, UK and Global Institute for Water Security, University of Saskatchewan, Canada
  • 7Institute for Environmental Science and Geography, University of Potsdam, Germany

Abstract. There is a general trend for increasing inclusion of uncertainty estimation in the environmental modelling domain. We present the CREDIBLE Uncertainty Estimation (CURE) Toolbox, an open source MATLABTM toolbox for uncertainty estimation aimed at scientists and practitioners that are not necessarily experts in uncertainty estimation. The toolbox focusses on environmental simulation models and hence employs a range of different Monte Carlo methods for forward and conditioned uncertainty estimation. The methods included span both formal statistical and informal approaches, which are demonstrated using a range of modelling applications set up as workflow scripts. The workflow scripts provide examples of how to utilise toolbox functions for a variety of modelling applications and hence aid the user in defining their own workflow: additional help is provided by extensively commented code. The toolbox implementation aims to increase the uptake of uncertainty estimation methods within a framework designed to be open and explicit, in a way that tries to represent best practice in applying the methods included. Best practice in the evaluation of modelling assumptions and choices, specifically including epistemic uncertainties, is also included by the incorporation of a condition tree that allows users to record assumptions and choices made as an audit trail log.

Trevor Page et al.

Status: open (until 12 Jan 2023)

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Trevor Page et al.

Model code and software

CURE Uncertainty Estimation Toolbox Trevor Page, Paul Smith, Keith Beven, Francesca Pianosa, Fanny Sarrazin, Susana Almeida https://www.lancaster.ac.uk/lec/sites/qnfm/credible/default.htm

Trevor Page et al.

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Short summary
This Technical Note provides an introduction to the Cedible UnceRtainty Estimation Toolbox (CURE) that provides workflows for a variety of uncertainty estimation methods. One of its most important features is the requirement to define all the assumptions on which a workflow analysis depends. This facilitates the communication with potential users of an analysis. An audit trail log is produced automatically from a workflow for future reference.