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Matlab/R workflows to assess critical choices in Global Sensitivity Analysis using the SAFE toolbox
Valentina Noacco1, Fanny Sarrazin1,2, Francesca Pianosi1
1Department of Civil Engineering, University of Bristol, Bristol, BS8 1TR, UK.
Methodsx
|November 1, 2019
Summary
This study introduces practical workflows for Global Sensitivity Analysis (GSA), a method for understanding model input uncertainties. These workflows enhance GSA implementation quality and reproducibility in scientific research.
Area of Science:
- Environmental modeling
- Computational science
- Statistical analysis
Background:
- Global Sensitivity Analysis (GSA) quantifies input uncertainty effects on mathematical model outputs.
- Effective GSA is crucial for developing, evaluating, and refining complex models, particularly in earth system science.
- Previous work reviewed GSA's value; this paper focuses on practical implementation.
Purpose of the Study:
- To provide actionable workflow scripts for implementing Global Sensitivity Analysis (GSA).
- To guide users in making critical choices during GSA execution.
- To improve the quality and reproducibility of GSA applications.
Main Methods:
- Development of adaptable workflow scripts for GSA implementation.
- Demonstration of workflow usage with a rainfall-runoff model.
- Implementation within the open-source SAFE toolbox (MATLAB and R).
Main Results:
- Workflows facilitate interpretation of GSA outcomes based on user choices.
- Methods allow for revision of choices to enhance GSA quality.
- The proposed workflows are documented and reusable.
Conclusions:
- The workflows promote best practices in GSA applications.
- They contribute to robust and reproducible computational science.
- Users can adopt and adapt these workflows for various GSA methods.
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