Global sensitivity analysis workflows and rankings: A practical comparison for researchers.
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| Title: | Global sensitivity analysis workflows and rankings: A practical comparison for researchers. |
|---|---|
| Authors: | Newman, Ken B.1,2 (AUTHOR) ken.newman@bioss.ac.uk, Naha, Shaini3 (AUTHOR), Jackson-Blake, Leah A.4 (AUTHOR), Topp, Cairistiona5 (AUTHOR), Glendell, Miriam3 (AUTHOR), Butler, Adam1 (AUTHOR) |
| Source: | Environmental Modelling & Software. May2026, Vol. 200, pN.PAG-N.PAG. 1p. |
| Subject Terms: | Sensitivity analysis, Computer simulation, Regression trees, Workflow management |
| Abstract: | Global sensitivity analysis (GSA) is a recommended step in the use of computer simulation models. GSA quantifies the relative importance of model inputs on outputs (Factor Ranking), identifies inputs that could be fixed, thus simplifying model calibration (Factor Fixing), and pinpoints areas for future data collection (Factor Prioritization). Given the wide variety of GSA methods, choosing between methods can be challenging. We provide a practitioner-focused guide for non-GSA experts that compares both widely and less commonly used GSA methods, discuss implementation and interpretation issues, and propose a workflow. We assess the degree of similarity in Factor Ranking based on a study of three simulators of differing complexity. A critical issue for all methods is specification of parameter ranges. Factor Rankings were generally quite similar based on Kendall's W. Sobol' first order and total sensitivity indices were easy to interpret and informative with regression trees providing additional insight into interactions. • Provides a practitioner-focused framework for conducting Global Sensitivity Analysis. • Clarifies implementation choices, interpretation, and limitations. • Presents a ten-step workflow for non-specialists. • Applies several GSA methods to three real world simulators of varying complexity. • Factor rankings across methods were highly similar. [ABSTRACT FROM AUTHOR] |
| Copyright of Environmental Modelling & Software is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
| FullText | Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 192692640 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Global sensitivity analysis workflows and rankings: A practical comparison for researchers. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Newman%2C+Ken+B%2E%22">Newman, Ken B.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> ken.newman@bioss.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Naha%2C+Shaini%22">Naha, Shaini</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jackson-Blake%2C+Leah+A%2E%22">Jackson-Blake, Leah A.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Topp%2C+Cairistiona%22">Topp, Cairistiona</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Glendell%2C+Miriam%22">Glendell, Miriam</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Butler%2C+Adam%22">Butler, Adam</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Environmental+Modelling+%26+Software%22">Environmental Modelling & Software</searchLink>. May2026, Vol. 200, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+trees%22">Regression trees</searchLink><br /><searchLink fieldCode="DE" term="%22Workflow+management%22">Workflow management</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Global sensitivity analysis (GSA) is a recommended step in the use of computer simulation models. GSA quantifies the relative importance of model inputs on outputs (Factor Ranking), identifies inputs that could be fixed, thus simplifying model calibration (Factor Fixing), and pinpoints areas for future data collection (Factor Prioritization). Given the wide variety of GSA methods, choosing between methods can be challenging. We provide a practitioner-focused guide for non-GSA experts that compares both widely and less commonly used GSA methods, discuss implementation and interpretation issues, and propose a workflow. We assess the degree of similarity in Factor Ranking based on a study of three simulators of differing complexity. A critical issue for all methods is specification of parameter ranges. Factor Rankings were generally quite similar based on Kendall's W. Sobol' first order and total sensitivity indices were easy to interpret and informative with regression trees providing additional insight into interactions. • Provides a practitioner-focused framework for conducting Global Sensitivity Analysis. • Clarifies implementation choices, interpretation, and limitations. • Presents a ten-step workflow for non-specialists. • Applies several GSA methods to three real world simulators of varying complexity. • Factor rankings across methods were highly similar. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Environmental Modelling & Software is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.envsoft.2026.106956 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Sensitivity analysis Type: general – SubjectFull: Computer simulation Type: general – SubjectFull: Regression trees Type: general – SubjectFull: Workflow management Type: general Titles: – TitleFull: Global sensitivity analysis workflows and rankings: A practical comparison for researchers. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Newman, Ken B. – PersonEntity: Name: NameFull: Naha, Shaini – PersonEntity: Name: NameFull: Jackson-Blake, Leah A. – PersonEntity: Name: NameFull: Topp, Cairistiona – PersonEntity: Name: NameFull: Glendell, Miriam – PersonEntity: Name: NameFull: Butler, Adam IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 13648152 Numbering: – Type: volume Value: 200 Titles: – TitleFull: Environmental Modelling & Software Type: main |
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