Global Sensitivity Analysis of environmental models

TL;DR: Criteria to quantify the convergence of sensitivity indices, of ranking and of screening, based on a bootstrap approach is defined and investigated and it is demonstrated that convergence of screening and ranking can be reached before sensitivity estimates stabilize.

Abstract: We address two critical choices in Global Sensitivity Analysis (GSA): the choice of the sample size and of the threshold for the identification of insensitive input factors. Guidance to assist users with those two choices is still insufficient. We aim at filling this gap. Firstly, we define criteria to quantify the convergence of sensitivity indices, of ranking and of screening, based on a bootstrap approach. Secondly, we investigate the screening threshold with a quantitative validation procedure for screening results. We apply the proposed methodologies to three hydrological models with varying complexity utilizing three widely-used GSA methods (RSA, Morris, Sobol'). We demonstrate that convergence of screening and ranking can be reached before sensitivity estimates stabilize. Convergence dynamics appear to be case-dependent, which suggests that "fit-for-all" rules for sample sizes should not be used. Other modellers can easily adopt our criteria and procedures for a wide range of GSA methods and cases. We propose criteria to measure the convergence for screening, ranking and indices.We investigate the screening threshold with a quantitative validation procedure.We test those procedures for three widely-used GSA methods.Screening/ranking convergence can be reached before sensitivity indices stabilize.Convergence dynamics are case-dependent, which precludes generic rules.