This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
Downloads
Supplementary Files
Authors
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 [n.d.]. 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.
DOI
https://doi.org/10.31223/osf.io/pu83z
Subjects
Applied Mathematics, Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Physical Sciences and Mathematics, Risk Analysis, Statistics and Probability
Keywords
uncertainty analysis, Sensitivity analysis, reproducibility, Earth system modelling, input interactions, input variability, output metric, sample size, screening, simulation performance
Dates
Published: 2019-04-05 03:40
There are no comments or no comments have been made public for this article.