Abstract Estimating the extent of hazard-induced damage to infrastructure networks is a complex task that goes beyond computing direct costs and requires considering the effect of network connection patterns and interactions. This article presents a new model that combines a systems approach with strategies for detecting the internal structure of networks, and providing flexibility and different levels of accuracy in estimating the extent of damage. The model describes networks as hierarchical structures obtained by successive clustering. Hierarchical analysis of networks provides unique insights about how damage affects performance throughout the whole infrastructure system. The model enables using information for decision-making more efficiently by generating different levels of resolution for different problems. This is illustrated using data from hurricane Ike, Texas, USA in 2008, where the primary transportation network is studied. Estimates of population affected and loss of productivity are discussed, emphasising the importance of multiple levels for assessment, and their application on fast decision-making for emergency situations. Keywords: network analysisrisk managementreliabilitysystemstransportation networks Acknowledgements This article was partially funded by the Texas Transportation Institute (TTI) at Texas A&M University, under grant 08−01–13 (UTCM), and by the US National Science Foundation, through grant CMMI-0748231. The authors gratefully acknowledge these financial supports.