Global sensitivity and uncertainty analysis of a coastal morphodynamic model using Polynomial Chaos Expansions. (February 2023)

• Record Type: Journal Article
• Authors: Jamous, Mohammad; Marsooli, Reza; Ayyad, Mahmoud
• Is Part Of: Environmental modelling & software. Volume 160(2023)
• Publication Date: 2023-02
• Subjects: Sensitivity -- Uncertainty -- Polynomial Chaos Expansions -- Coastal erosion -- Sediment transport -- X-Beach; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105611
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: 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. Highlights: Sensitivity of XBeach model to its input parameters is investigated. Sensitivity is quantified using Non-Intrusive Polynomial Chaos Expansions method. Effect of interactions among input parameters on model behavior is quantified. Effects of boundary conditions and site characteristics on sensitivity are quantified.