Sensitivity analysis: A discipline coming of age

• Published in: Environmental modelling & software : with environment data news 2021-12, Vol.146, p.105226, Article 105226
• Main Authors: Saltelli, Andrea, Jakeman, Anthony, Razavi, Saman, Wu, Qiongli
• Format: Article
• Language: English
• Subjects: Environment models; Environmental modeling; Evidence based policy; Growth stage; Learning algorithms; Machine learning; Scientific papers; Sensitivity analysis; Uncertainty analysis; Validation and verification of mathematical models
• ISSN: 1364-8152; 1873-6726
• DOI: 10.1016/j.envsoft.2021.105226

Sensitivity analysis (SA) as a ‘formal’ and ‘standard’ component of scientific development and policy support is relatively young. Many researchers and practitioners from a wide range of disciplines have contributed to SA over the last three decades, and the SAMO (sensitivity analysis of model output) conferences, since 1995, have been the primary driver of breeding a community culture in this heterogeneous population. Now, SA is evolving into a mature and independent field of science, indeed a discipline with emerging applications extending well into new areas such as data science and machine learning. At this growth stage, the present editorial leads a special issue consisting of one Position Paper on “The future of sensitivity analysis” and 11 research papers on “Sensitivity analysis for environmental modelling” published in Environmental Modelling & Software in 2020–21. •Advances of science and policy has deep but informal roots in sensitivity analysis.•Modern sensitivity analysis is now evolving into a formal and independent discipline.•New areas such data science and machine learning benefit from sensitivity analysis.•Challenges, methodological progress, and outlook are outlined in this special issue.