Global Sensitivity Analysis of environmental models: Convergence and validation

Global Sensitivity Analysis of environmental models: Convergence and validation

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 boot...

Global Sensitivity Analysis of Dam Erosion Models

Windows TM Dam Analysis Modules (WinDAM) is a set of modular software components that can be used to analyze overtopped earthen embankments and internal erosion of embankment dams. These software components are being developed in stages. The initial computational modules address routing of floods through the reservoir with dam overtopping and evaluation of the potential for vegetation or riprap...

Sensitivity Analysis for Environmental Models and Monitoring Networks

Statistical sensitivity analysis is shown to be a useful technique for assessing both multivariate environmental computer models and environmental statistical spatio-temporal models in the perspective of risk assessment. Methods are reviewed and extended to cover with two applications which are reported as case studies. The rst, related to waste water bio lters for heavy metals, is aimed at ass...

Evaluation of Soil Liquefaction Potential by Sensitivity Analysis, Reliability and Data validation

In this study, it is attempted to analyze sensitivity and reliability in order to evaluate the liquefaction potential in soil layers in Tabriz. 62 boreholes that had possible conditions for liquefaction were selected. Seismic mapping was simulated using finite fault method and then the effect of soil layers on PGA was estimated. In continue, the liquefaction potential index was estimated and th...

Machine Learning for Sensitivity Analysis of Probabilistic Environmental Models