Infrastructure systems are becoming increasingly complex and interdependent. As a result our ability to predict the
likelihood of large-scale failure of these systems has significantly diminished and the consequence of this is that we
now have a greatly increased risk of devastating impacts to society.
Traditionally these systems have been analysed using physically-based models. However, this approach can only
provide information for a specific network and is limited by the number of scenarios that can be tested. In an attempt
to overcome this shortcoming, many studies have used network graph theory to provide an alternative analysis
approach. This approach has tended to consider infrastructure systems in isolation, but has recently considered
the analysis of interdependent networks through combination with percolation theory. However, these studies have
focused on the analysis of synthetic networks and tend to only consider the topology of the system.
In this paper we develop a new analysis approach, based upon network theory, but accounting for the hierarchical
structure and functional dependency observed in real world infrastructure networks. We apply this method to two
real world networks, to show that it can be used to quantify the impact that failures within an electricity network have
upon a dependent water network
