This paper proposes a framework for evaluation of the sources of uncertainty that can disrupt the flood emergency response process. During the flood response, flood emergency managers usually choose between several decision options under limited available lead-time, but they are often compelled with different sources of uncertainty. These sources can significantly affect the quality of decisions related to adequate response and rapid recovery of the affected system. The proposed framework considers efficient identification, integration, and quantification of system uncertainties related to the flood risk. Uncertainty analysis is performed from a decision-maker’s perspective and focused on the time period near and during the flood event. The major scope of proposed framework is to recognize and characterize sources of uncertainty which can potentially appear within the behavior of the observed system. Using a Bayesian network approach, a model is developed capable for quantification of different sources uncertainty in respect to their particular type. The proposed approach is validated on the Sava River case study, in the area of the city of Slavonski Brod, following the destructive 2014 flood event. The results indicate that, despite improvements of structural measures, the weir failure can still cause flooding of the approximately 1 km2
of otherwise safe area, resulting in the increased flood risk.
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