Probabilistic modeling of cascading failure risk in interdependent channel and road networks in urban flooding

Abstract

This paper presents a probabilistic model for assessing risk of cascading failures in co-located road and channel networks. The proposed Bayesian network analysis framework integrates network structural properties and empirical flood propagation data to model the spread of flooding. The model was tested in a multiple watershed scenario in Harris County, Texas (USA), using historical flood data from past events. The results show the capability of the proposed Bayesian network model to quantitatively characterize the failure (i.e., inundation) of road network considering the cascading failure (i.e., overflow) from the channel network. The proposed model also enables simulating the risk of flood cascades (i.e., flood propagation) on the road network with high accuracy. The generic design of the algorithm also enables the adaptation of the proposed framework in other cities and regions. Accordingly, the proposed model provides a new tool to help decision-makers prioritize infrastructure protection plans and emergency response actions.