Cascading Effects of Critical Infrastructures in a Flood Scenario: A Case Study in the City of Cologne

Authors

  • Moritz Schneider German Aerospace Center (DLR), Institute for the Protection of Terrestrial Infrastructures Author
  • Peter Priesmeier Cologne University of Applied Sciences, Institute of Rescue Engineering and Civil Protection Author
  • Alexander Fekete Cologne University of Applied Sciences, Institute of Rescue Engineering and Civil Protection Author
  • Daniel Lichte German Aerospace Center (DLR), Institute for the Protection of Terrestrial Infrastructures Author
  • Frank Fiedrich Chair for Public Safety and Emergency Management, University of Wuppertal Author

Keywords:

Critical Infrastructure, Cascading Effects, Flood Risk Management, Bayesian Network, GIS.

Abstract

Critical infrastructures, which constitute the backbone of our modern society, are increasingly exposed to natural hazards. Loss of performance or failure of a critical infrastructure can lead to cascading effects that affect even more services and citizens. Floods, as one of the most prominent natural hazards, are prone to affect multiple critical infrastructures at once, making it even more difficult to assess combined effects of these (cascading) disruptions. Hospitals are especially vulnerable in a flood scenario, as they are reliant on multiple other infrastructures, such as power and water supply or the road network. In order to prepare for upcoming events, sophisticated analysis tools are required that are capable of modeling the spatial extent of flood induced disruptions and their impact on critical infrastructure services. In this work, we present a proof of concept that focuses on the impact of multiple disruptions on hospitals. We conducted a case study on an extreme flood scenario in the city of Cologne (Germany). Historically, Cologne has proven vulnerable to river-floods, as thousands of people were affected through floods in in 1993 and 1995. The approach is based on a combination of I) a geographic information system, which makes the extent of disruptions spatially explicit and II) a Bayesian network, which is used to assess the impact of one or multiple disruptions on a single hospital. We present a work-in-progress approach in this work. The results generated using this approach enable a first comparative overview of the expected level of services of the examined hospitals. 

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Published

2024-05-16

How to Cite

Schneider, M., Priesmeier, P., Fekete, A., Lichte, D., & Fiedrich, F. (2024). Cascading Effects of Critical Infrastructures in a Flood Scenario: A Case Study in the City of Cologne. ISCRAM Proceedings, 21. http://ojs.iscram.org/index.php/Proceedings/article/view/77

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