Efficient tools for global sensitivity analysis based on high-dimensional model representation

Models used in Systems Engineering and Earth System Science are continuously evolving to include more processes and interactions at higher resolutions. This increase in complexity can also lead to an increase in the number of uncertain parameters. Parameter optimization methods can be used to constrain model parameters against observations. However, in most cases the large number of uncertain parameters leads to an underdetermined and ill-posed problem. It is therefore crucial to first identify the most important parameters in complex modeling systems by applying global sensitivity analysis methods. Here, we demonstrate the effectiveness of high-dimensional model representation (HDMR) methods, which are not only able to calculate sensitivity indices but also able to visualize the effect of each parameter on the model output over its whole uncertainty range. We introduce the graphical user interface (GUI)-HDMR software package and highlight its capabilities. A number of case studies from a wide range of applications are presented to underline the usefulness of the GUI-HDMR software and its ability to identify the most important parameters and their interactions in highly nonlinear complex modeling systems.