TY  - JOUR
A1  - Baroni, Gabriele
A1  - Francke, Till
T1  - An effective strategy for combining variance- and distribution-based global sensitivity analysis
JF  - Environmental modelling & software with environment data news
N2  - We present a new strategy for performing global sensitivity analysis capable to estimate main and interaction effects from a generic sampling design. The new strategy is based on a meaningful combination of varianceand distribution-based approaches. The strategy is tested on four analytic functions and on a hydrological model. Results show that the analysis is consistent with the state-of-the-art Saltelli/Jansen formula but to better quantify the interaction effect between the input factors when the output distribution is skewed. Moreover, the estimation of the sensitivity indices is much more robust requiring a smaller number of simulations runs. Specific settings and alternative methods that can be integrated in the new strategy are also discussed. Overall, the strategy is considered as a new simple and effective tool for performing global sensitivity analysis that can be easily integrated in any environmental modelling framework.
KW  - global sensitivity analysis
KW  - variance
KW  - distribution
KW  - generic sampling
KW  - design
Y1  - 2020
U6  - https://doi.org/10.1016/j.envsoft.2020.104851
SN  - 1364-8152
SN  - 1873-6726
VL  - 134
PB  - Elsevier
CY  - Oxford
ER  -