TY - JOUR
T1 - Global sensitivity and uncertainty analysis of a coastal morphodynamic model using Polynomial Chaos Expansions
AU - Jamous, Mohammad
AU - Marsooli, Reza
AU - Ayyad, Mahmoud
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/2
Y1 - 2023/2
N2 - 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.
AB - 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.
KW - Coastal erosion
KW - Polynomial Chaos Expansions
KW - Sediment transport
KW - Sensitivity
KW - Uncertainty
KW - X-Beach
UR - http://www.scopus.com/inward/record.url?scp=85145711624&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85145711624&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2022.105611
DO - 10.1016/j.envsoft.2022.105611
M3 - Article
AN - SCOPUS:85145711624
SN - 1364-8152
VL - 160
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
M1 - 105611
ER -