CReDo Technical Report 4: Modelling System Impact

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Infrastructure assets in different sectors require connectivity in order to operate and provide essential services to end users. For example, water requires power and telecoms, power requires telecoms, among other connections. Understanding the connectivity of different infrastructure assets at the systems level, as well as which connections and assets are critical, is essential to ensure that investment planning is targeted at the most critical assets for normal and unusual operation. CReDo’s ambition is to address the connections between different infrastructure assets owned and operated by different asset owners in order to understand where the critical connections at the systems level may be, how critical assets may fail during extreme flooding scenarios and what is the level of vulnerability and impact on service provision.

In this use case, asset data from three service providers delivering power, water and telecommunication services have been integrated and interrogated within a single platform to provide insights into sectoral interdependencies and better understand how the system responds to and is impacted by a range of potential future flood events, driven by a changing climate. This first phase of CReDo involves a modelling approach that assesses how the different assets are connected in the wider system and how cascading failures are propagating across the system following asset failures in parts of the network.

The approach taken to analyse the flood impacts first used a flood-depth criteria for high-level identification of assets that would directly fail from high flood levels across the site. Building on this, the core of the work was to propagate failures from those directly impacted nodes. Failures are triggered from the direct connections between assets (a power asset providing external power supply to water assets) when a single asset fails as a result of flooding. The model developed is deterministic. The propagation of failure is implemented first within each sectoral network independently (water, power and telecommunication) before being extended across networks. This was achieved by integrating the data into component networks models and connecting these with an overarching coordinating algorithm.

Building on the work undertaken in this first phase of CReDo, it is recommended that the next phases consider the following to address the current limitations. These include:


  • Modelling of more complex interdependencies in the system (including for links and dependencies on the transport sector);
  • Modelling of existing redundancy in individual assets, for example a flood defence wall or backup power supplies;
  • Modelling of criticality of individual assets and how system vulnerability may be expressed;
  • Running of a series of simulations at the system level to better understand how the system responds under a range of possible climate impact and individual asset failure scenarios;
  • Development of dynamic models that simulate system impacts over time; recognising that the system is not static, and failures will unfold as the event progresses and recovery methods are put in place.


Testing the system under various scenarios with these criticalities identified would provide useful insights to asset owners/operators for making investment decisions that maximise system resilience in the face of extreme flood and other climate hazards driven by a changing climate.

Finally, where the current work focussed on developing and testing failure and propagation models at a local scale, future work should allow for an implementation at a larger scale where the Information Management Framework associated tools can be scaled up and adapted to wider geographies and portfolio of assets.