Matlab/R workflows to assess critical choices in Global Sensitivity Analysis using the SAFE toolbox

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Abstract

Global Sensitivity Analysis (GSA) is a set of statistical techniques to investigate the effects of the uncertainty in the input factors of a mathematical model on the model’s outputs. The value of GSA for the construction, evaluation, and improvement of earth system models is reviewed in a companion paper by Wagener and Pianosi [2019]. The present paper focuses on the implementation of GSA and provides a set of workflow scripts to assess the critical choices that GSA users need to make before and while executing GSA. The workflows proposed here can be adopted by GSA users and easily adjusted to a range of GSA methods. We demonstrate how to interpret the outcomes resulting from these different choices and how to revise the choices to improve GSA quality, using a simple rainfall runoff model as an example. We implement the workflows in the SAFE toolbox, a widely used open source software for GSA available in MATLAB and R.

• The workflows aim to contribute to the dissemination of good practice in GSA applications.
• The workflows are well-documented and reusable, as a way to ensure robust and reproducible computational science.
Original languageEnglish
Pages (from-to)2258-2280
Number of pages23
JournalMethodsX
Volume6
DOIs
Publication statusPublished - 30 Sep 2019

Keywords

  • earth system modelling
  • sensitivity analysis
  • input variability
  • reproducibility
  • uncertainty 14 analysis
  • output metric
  • sample size
  • input interactions
  • simulation performance
  • screening

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