Global sensitivity and uncertainty analysis of a coastal morphodynamic model using Polynomial Chaos Expansions

Predicting coastal erosion requires an accurate morphodynamic model. XBeach has been widely adopted to simulate storm-induced coastal erosion. Because of the large number of model input parameters and their uncertainties, sensitivity analysis is a crucial step toward reliable results. This requires running a large number of computationally expensive simulations. Here, we adopt a computationally cost-effective approach based on the Non-Intrusive Polynomial Chaos Expansion method to quantify the sensitivity of XBeach to its input parameters. The method is applied to the coastal erosion event caused by Hurricane Sandy along the barrier islands of New Jersey in the United States. The results show a spatial variation of the model sensitivity with increasing boundary conditions. Parameters' interaction is found to decrease as the magnitude of boundary conditions increases, causing a reduction in the nonlinearity of the model behavior, and consequently leading to a reduction in the uncertainty of the model output.

Automated summary

Predicting coastal erosion requires an accurate morphodynamic model, such as XBeach. Sensitivity analysis is conducted using a computationally cost-effective approach based on the Non-Intrusive Polynomial Chaos Expansion method. Applied to Hurricane Sandy-induced coastal erosion in New Jersey, the results demonstrate the spatial variation of model sensitivity and the reduction of parameter interaction with increasing boundary conditions, leading to a reduction in uncertainty of model output.