The future of sensitivity analysis: An essential discipline for systems modeling and policy support
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society.
Date Issued
2021-03
Date Acceptance
2020-12-10
Citation
Environmental Modelling & Software, 2021, 137, pp.1-22
ISSN
1364-8152
Publisher
Elsevier BV
Start Page
1
End Page
22
Journal / Book Title
Environmental Modelling & Software
Volume
137
Copyright Statement
© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S1364815220310112?via%3Dihub
Subjects
Environmental Engineering
Publication Status
Published
Date Publish Online
2020-12-15