EU-funded researchers have developed two cutting-edge software platforms that European crisis responders can now use to improve coordination, communication and preparedness.

The platforms could help prevent catastrophes escalating, reduce economic losses and save lives.

Natural disasters such as floods, storms and earthquakes, or infrastructure failures such as a dam collapse or an electrical blackout can have broad impacts beyond the immediate event. The consequences on other infrastructure and communities can affect many more people and spread beyond regional or national borders.

Flooding in Germany, for example, can rapidly spread to the Netherlands. A dam failure in the Alps could impact towns in both France and Italy and affect transport, water and electricity networks, while an incident with a power station in one European country may trigger blackouts elsewhere.

Today, stakeholders have some knowledge of the dependencies between them, but there is still little clear understanding of possible interactions and cascading effects in scenarios that have impacts outside of individual stakeholders’ daily work, system borders and communication horizons.

In Europe, this situation has resulted in generally weak cross-sectoral cooperation between actors in different cities, regions and countries.

To bridge the gaps, the EU-funded project FORTRESS studied past responses to crises and analysed the interdependencies between different systems and actors. The work has led to two state-of-the-art software platforms that are now being made available to crisis responders across Europe to improve coordination, communication and preparedness.

FORTRESS’ tools aim to help crisis managers and infrastructure operators analyse and understand their mutual dependencies, develop a common understanding of the risks of cascading effects and plan coordinated information exchange and responses during crises.

Having tested prototype demonstrators and evaluated the results in practice with Dutch and German crisis management teams, the FORTRESS researchers are planning to make the tools available to end-users across Europe, initially as part of an integrated inter-sectoral workshop programme.

Advanced modelling to mitigate crisis escalation

On the one hand, the FORTRESS Model Builder enables multiple stakeholders across organisations and countries to systematically describe and model interactions between entities, such as infrastructure operators or crisis first responders, which may become relevant or affected during different kinds of incidents. As a collaborative modelling platform, the tool enables input from numerous stakeholders in order to generate a network of dynamic dependencies and visualise how each affects the others.

Project coordinator Leon Hempel of the Zentrum Technik und Gesellschaft at Technische Universität Berlin explains:

“In crisis situations, cascading effects occur when the impact of a physical event or system failure causes a sequence of events in other human or non-human systems that lead to consequences with higher magnitudes.” 

“It is not simply a linear chain of events but rather a spreading of disruptions in complex ways. An initial impact can trigger diverse effects that expand not just in one but multiple directions involving amplification and feedback loops.”

This information in turn feeds into the FORTRESS ‘Incident Evolution Tool’, which provides stakeholders with a means to evaluate how a crisis initially impacting one entity may result in cascading effects on other entities, systems and stakeholders.

“By assigning different properties and probabilities it is possible to construct a time line and generate various ‘if/then’ scenarios within a given scenario framework. This enables the assessment of multiple pathways to predict how events might develop and impact the overall network of nodes, relations and dependencies,” Hempel says. “All this is not dependent upon real time data, but primarily on the real experiences first responders collected over the years. In the future, we expect to include additional information from various relevant data sources to facilitate the modelling and to integrate further analytical features.”