Uncertainty quantification and sensitivity analysis applied to the wind wave model SWAN. (September 2017)

• Record Type: Journal Article
• Authors: Nikishova, Anna; Kalyuzhnaya, Anna; Boukhanovsky, Alexander; Hoekstra, Alfons
• Is Part Of: Environmental modelling & software. Volume 95(2017)
• Page Start: 344
• Page End: 357
• Publication Date: 2017-09
• Subjects: Uncertainty quantification -- Sensitivity analysis -- Wind wave model -- SWAN -- Baltic sea -- Unstructured mesh; 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.2017.06.030
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: We report on measuring uncertainty in the computational results of the wind wave model SWAN (Simulating WAves Nearshore) on an unstructured mesh and exploring the sources of this uncertainty. We considered an area in the vicinity of the Saint Petersburg Flood Prevention Facility Complex and treat the results as risks on using the model results for the Facility gate operation. We found that model response uncertainty is significant for small waves ( H s < 0.3 m ), and the results variability is moderate ( ≈ 10 % ) for the extreme values of the model prediction. Thus the risk on the use of model results to predict flood threats is low together with visible uncertainty about the prediction of flood start time. Uncertainty in wind velocity has a substantial influence on the model response. In addition, uncertainty in the bathymetry, water level, and breaker index affects model output. Therefore, result uncertainty can be decreased obtaining more certain values of these model inputs. Highlights: Uncertainty quantification was applied to the results of the wind wave model SWAN for the area near the Saint Petersburg Flood Prevention Facility. Extreme values of the model outcome contain about 10 % uncertainty. Variability of the model predictions of small waves is high. Sensitivity analysis indicates that uncertainty in wind directions affects significantly the model output. Uncertainty in the breaker index, bathymetry and water level contributes to the model response uncertainty in some coastal areas.