Global Sensitivity Analysis of a Dam Breaching Model: To Which Extent Is Parameter Sensitivity Case-Dependent?

Failure of dams and dikes often leads to devastating consequences in protected areas. Numerical models are instrumental tools to assess flood risk and guide emergency management, but numerous uncertainties affect model outcomes. Identifying uncertain model input parameters that induce high uncertainties in model outputs is essential. This paper focuses on two model outputs: the maximum breach discharge and the time to reach this peak. Using our implementation of a simplified physically based dam breaching model developed by Wu (2016), a global sensitivity analysis was conducted based on Sobol indices of total order. Unlike in most previous studies, many different configurations (twenty-seven), both at laboratory and field scales, were considered. For each of them, input variables were ranked according to the significance of the contribution of their uncertainty to the output variability, and the dependency between reference configurations and sensitivity analysis results was highlighted. Depending on the considered case study, input parameter uncertainties with the largest impact on output variability were different, and so was the magnitude of output uncertainties. We demonstrate that sensitivity analysis results obtained for a specific configuration cannot be transferred as it to other configurations. Finally, sensitivity and uncertainty quantification results were combined in a decision tree to determine which input parameter uncertainty is the most critical in each configuration and what standard deviation in the output variables is expected. The global sensitivity analysis procedure presented here may apply to a wide variety of models in environmental sciences.