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

Valentina Noacco; Fanny Sarrazin; Francesca Pianosi; Thorsten Wagener

doi:10.1016/j.mex.2019.09.033

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

Valentina Noacco, Fanny Sarrazin, Francesca Pianosi, Thorsten Wagener

Research output: Contribution to journal › Article (Academic Journal) › peer-review

35 Citations (Scopus)

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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 language	English
Pages (from-to)	2258-2280
Number of pages	23
Journal	MethodsX
Volume	6
DOIs	https://doi.org/10.1016/j.mex.2019.09.033
Publication status	Published - 30 Sept 2019

Research Groups and Themes

Water and Environmental Engineering

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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Improving the understanding and consideration of uncertainty in the (re)insurance industry
Noacco, V. (Principal Investigator)
1/11/17 → 31/10/22
Project: Research

Cite this

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

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{\textquoteright}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.",

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author = "Valentina Noacco and Fanny Sarrazin and Francesca Pianosi and Thorsten Wagener",

year = "2019",

month = sep,

day = "30",

doi = "10.1016/j.mex.2019.09.033",

language = "English",

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journal = "MethodsX",

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T1 - Matlab/R workflows to assess critical choices in Global Sensitivity Analysis using the SAFE toolbox

AU - Noacco, Valentina

AU - Sarrazin, Fanny

AU - Pianosi, Francesca

AU - Wagener, Thorsten

PY - 2019/9/30

Y1 - 2019/9/30

N2 - 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.

AB - 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.

KW - earth system modelling

KW - sensitivity analysis

KW - input variability

KW - reproducibility

KW - uncertainty 14 analysis

KW - output metric

KW - sample size

KW - input interactions

KW - simulation performance

KW - screening

U2 - 10.1016/j.mex.2019.09.033

DO - 10.1016/j.mex.2019.09.033

M3 - Article (Academic Journal)

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SN - 2215-0161

VL - 6

SP - 2258

EP - 2280

JO - MethodsX

JF - MethodsX

ER -

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

Abstract

Research Groups and Themes

Keywords

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Improving the understanding and consideration of uncertainty in the (re)insurance industry

Cite this