Abstract :
[en] Failures of dams and dikes often lead to devastating consequences in protected areas. Numerical models are crucial tools to assess flood risk and guide emergency plans, but numerous sources of uncertainty exist. Identifying uncertain model input parameters that induce high uncertainties in model outputs is essential. In this paper, the focus was set on two specific model outputs: the maximum breach discharge and the lag time to reach this peak. Using our implementation of the simplified physically based dam breaching model developed by Wu (2016), a sensitivity analysis was conducted based on Sobol indices of total order in twenty-seven configurations at both laboratory and field -scales. In each case, 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 parameters uncertainties with the largest impact on output variability were extremely different, so was the amplitude of output uncertainties. In this work, we demonstrated that sensitivity analysis results obtained for a specific dam breaching case cannot be generalized to any configuration. Finally, sensitivity and uncertainty analysis results were combined in a decision tree to determine which input parameter uncertainty is the most critical in a given configuration and what standard deviation in the selected output variables should be expected.
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