Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Technical note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty
AU - Page, Trevor
AU - Smith, Paul
AU - Beven, Keith
AU - Pianosi, Francesca
AU - Sarrazin, Fanny
AU - Almeida, Susana
AU - Holcombe, Liz
AU - Freer, Jim
AU - Chappell, Nick
AU - Wagener, Thorsten
PY - 2023/7/11
Y1 - 2023/7/11
N2 - There is a general trend toward the increasing inclusion of uncertainty estimation in the environmental modelling domain. We present the Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE) Uncertainty Estimation (CURE) toolbox, an open-source MATLABTM toolbox for uncertainty estimation aimed at scientists and practitioners who 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 utilize 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 with respect to applying the methods included. Best practice with respect to 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.
AB - There is a general trend toward the increasing inclusion of uncertainty estimation in the environmental modelling domain. We present the Consortium on Risk in the Environment: Diagnostics, Integration, Benchmarking, Learning and Elicitation (CREDIBLE) Uncertainty Estimation (CURE) toolbox, an open-source MATLABTM toolbox for uncertainty estimation aimed at scientists and practitioners who 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 utilize 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 with respect to applying the methods included. Best practice with respect to 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.
KW - General Earth and Planetary Sciences
KW - General Environmental Science
U2 - 10.5194/hess-27-2523-2023
DO - 10.5194/hess-27-2523-2023
M3 - Journal article
VL - 27
SP - 2523
EP - 2534
JO - Hydrology and Earth System Sciences
JF - Hydrology and Earth System Sciences
SN - 1027-5606
IS - 13
ER -