Modern societies developed an elaborate system of critical infrastructures (CIs) to address essential human needs. Given that the flawless operation of most CIs directly depends on other CIs, they can be interpreted as nodes of an intricate network connected by various interdependencies. The vital importance of CIs for well-being and even survival makes it mandatory to understand their resilience to be able to detect and quantify risks which might disturb their operation. It is important to quantify the effects of numerous risk mitigation measures to not only understand how the resilience of CIs is generally improved but to also identify the most (cost-)effective measures to support decision making in case not all measures can be implemented. Recently, in the face of climate change and progressing destruction of nature, nature-based solutions (NBS) have attracted broad attention. They promise to not only increase the resilience of humanly build infrastructure but to also support environmental protection. However, given their limited implementation and the lack of practical experiences regarding their effectiveness against, e.g., natural disasters, modelling approaches are essential to analyse the effects of NBS on the protection of CIs against a broad set of starting conditions and disruptions. In recent years, several modelling approaches based on different methods were proposed, e.g., graph-based or flow-based approaches. Still, most studies focus on specific CIs and often neglect dynamic aspects, like damage cascades evolving over time, hampering the possibilities to gain a holistic understanding of the CI grid’s resilience.
This contribution presents a graph-based modelling approach aimed to provide a comprehensive understanding of the resilience in terms of possible performance degradation and the corresponding response and recovery captured over time of CIs disturbed by natural disasters. It targets the quantification of the resulting failure cascades and restauration periods. Different CIs, such as hospitals and elements of the power grid, are represented by network nodes connected by edges representing the interdependencies. The contribution demonstrates how the highly diverse CIs and disparate dependencies can be incorporated into a single network model and how the temporal evolution of failure cascades is captured based on dependencies, lifetimes and repair times. Based on work performed in the Horizon-Europe project NBSInfra, the city of Aveiro will be considered to show exemplary results for natural disasters threatening the local CIs. The simulation results enable a comparison of the overall city resilience with and without NBS, highlighting the benefits of strategically implemented NBS.