Moment-independent regional sensitivity analysis: Application to an environmental model

Through several decades of development, global sensitivity analysis has been developed as a very useful guide tool for assessing scientific models and has gained pronounced attention in environmental science. However, standard global sensitivity analysis aims at measuring the contribution of input variables to model output uncertainty on average by investigating their full distribution ranges, but does not investigate the contribution of specific ranges. To deal with this problem, researchers have developed several regional sensitivity analysis techniques such as the contribution to sample mean and variance (CSM and CSV) plots. In this paper, a moment-independent regional sensitivity analysis technique called contribution to delta indices (CDI) plot is developed for assessing the effect of a specific range of an individual input to the uncertainty of model output. The CDI plot can be obtained with the same set of samples used for computing the CSM and CSV. Compared with the CSM and CSV, the CDI plot uses the probability density function shift of model output to describe the uncertainty instead of the mean and variance, thus it is moment-independent. An analytical linear model, the Ishigami function and an environmental model are employed to test the proposed RSA technique.