Assessment of Modelling Structure and Data Availability Influence on Urban Flood Damage Modelling Uncertainty

摘要

In modelling application, different model structures may be equally reliable in terms of calibration ability but they may produce different uncertainty levels; moreover, available data during model calibration may influence the uncertainty linked to the predictions of the same modelling structure. In the present paper, Bayesian model-averaging was applied to several flood damage estimation models in order to identify the best model combination for urban flooding distribution analysis in Palermo city center (Italy). During the analysis, was taken into account the effect of the available data growth on the model uncertainty with respect to the different combination of models outputs.