Socio-Environmental Systems Modelling (SESMO) will publish a special issue on sensitivity analysis of model output. SESMO is a not-for-profit, open-access only journal, and it does not charge any submission, article processing, or publication fees. SESMO is supported by the International Environmental Modelling & Software Society. 

SESMO Special Issue on “Sensitivity Analysis of Model Output”

This Special issue focuses on global sensitivity analysis and its impact on decisions with a scientific, social, and policy perspective. Sensitivity analysis contributes to model development, model calibration, model validation, reliability and robustness analysis, decision-making under uncertainty, quality-assurance, and model reduction. In recent years, the policymakers have required or recommended the use of sensitivity analysis in model testing and/or development, such as the Environmental Protection Agency, the Office of the Comptroller of the Currency (stress testing required by the Dodd-Frank Act), the US Nuclear Regulatory Commission, and the European Commission. The goal of this Special issue is to bring together researchers from engineering, physical and social sciences, mathematics and statistics, to create a forum for the latest research and applications of global sensitivity analysis.

How to submit to the Special issue:

1. Email an extended abstract to the Guest Editor, Giray Ökten (, by June 1, 2022. The Extended Abstracts are 1,000 words plus a bibliography that indicates the literature that the paper will build upon. The participants of the Tenth International Conference on Sensitivity Analysis of Model Output 2022 (SAMO) are especially encouraged to apply.
2. The authors will be notified of the outcome of the submission of their extended abstract by July 1, 2022.
3. The deadline for submission of full papers (around 10-12 journal pages long) for the selected authors is December 1, 2022. The article preparation guidelines can be found at The preferred file format is Word, but Latex is also acceptable. Word and Latex templates will be soon available on the journal webpage.
4. Authors are strongly encouraged to make model code and data underlying the findings described in their manuscript available under an appropriate Open Source licence.

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