Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6962525 | Environmental Modelling & Software | 2016 | 19 Pages |
Abstract
Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be attributed to variations of its input factors. SA is increasingly being used in environmental modelling for a variety of purposes, including uncertainty assessment, model calibration and diagnostic evaluation, dominant control analysis and robust decision-making. In this paper we review the SA literature with the goal of providing: (i) a comprehensive view of SA approaches also in relation to other methodologies for model identification and application; (ii) a systematic classification of the most commonly used SA methods; (iii) practical guidelines for the application of SA. The paper aims at delivering an introduction to SA for non-specialist readers, as well as practical advice with best practice examples from the literature; and at stimulating the discussion within the community of SA developers and users regarding the setting of good practices and on defining priorities for future research.
Related Topics
Physical Sciences and Engineering
Computer Science
Software
Authors
Francesca Pianosi, Keith Beven, Jim Freer, Jim W. Hall, Jonathan Rougier, David B. Stephenson, Thorsten Wagener,