Method of hierarchical global sensitivity analysis and its application in groundwater models

Objective Sensitivity analysis is an crucial tool in groundwater modelling for measuring the importance of various model inputs, enabling better allocation of limited funds and resources to reduce predictive uncertainty. Methods In this paper, we propose an enhanced hierarchical global sensitivity analysis method to quantify contribution of different types of input uncertainty to model outputs, and to assess the impact of each uncertain process on groundwater model predictions. To test and demonstrate the new method, a hypothetical case study of groundwater flow and contaminant transport is used to validate. Results The results indicate that model uncertainty is the main source of prediction uncertainty in this case, and uncertainty from the geological model is more important than that of other models. Conclusion The proposed method offers a more comprehensive sensitivity analysis for groundwater models. Compared with traditional parameter sensitivity analysis, the new method can consider more uncertain input factors, significantly improve computational efficiency, and provide more useful sensitivity information for model users and managers.