EGU21-922, updated on 03 Mar 2021
https://doi.org/10.5194/egusphere-egu21-922
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Conceptualization of a Critical Infrastructure Network – Model for Flood Risk Assessments

Roman Schotten and Daniel Bachmann
Roman Schotten and Daniel Bachmann
  • Magdeburg/Stendal University of applied Sciences, Water Environment Construction and Safety, Work Group Flood Risk Managment, Magdeburg, Germany (roman.schotten@h2.de)

In flood risk analysis it is a key principle to predetermine consequences of flooding to assets, people and infrastructures. Damages to critical infrastructures are not restricted to the flooded area. The effects of directly affected objects cascades to other infrastructures, which are not directly affected by a flood. Modelling critical infrastructure networks is one possible answer to the question ‘how to include indirect and direct impacts to critical infrastructures?’.

Critical infrastructures are connected in very complex networks. The modelling of those networks has been a basis for different purposes (Ouyang, 2014). Thus, it is a challenge to determine the right method to model a critical infrastructure network. For this example, a network-based and topology-based method will be applied (Pant et al., 2018). The basic model elements are points, connectors and polygons which are utilized to resemble the critical infrastructure network characteristics.

The objective of this model is to complement the state-of-the-art flood risk analysis with a quantitative analysis of critical infrastructure damages and disruptions for people and infrastructures. These results deliver an extended basis to differentiate the flood risk assessment and to derive measures for flood risk mitigation strategies. From a technical point of view, a critical infrastructure damage analysis will be integrated into the tool ProMaIDes (Bachmann, 2020), a free software for a risk-based evaluation of flood risk mitigation measures.

The data on critical infrastructure cascades and their potential linkages is scars but necessary for an actionable modelling. The CIrcle method from Deltares delivers a method for a workshop that has proven to deliver applicable datasets for identifying and connecting infrastructures on basis of cascading effects (de Bruijn et al., 2019). The data gained from CIrcle workshops will be one compound for the critical infrastructure network model.

Acknowledgment: This work is part of the BMBF-IKARIM funded project PARADes (Participatory assessment of flood related disaster prevention and development of an adapted coping system in Ghana).

Bachmann, D. (2020). ProMaIDeS - Knowledge Base. https://promaides.myjetbrains.com

de Bruijn, K. M., Maran, C., Zygnerski, M., Jurado, J., Burzel, A., Jeuken, C., & Obeysekera, J. (2019). Flood resilience of critical infrastructure: Approach and method applied to Fort Lauderdale, Florida. Water (Switzerland), 11(3). https://doi.org/10.3390/w11030517

Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering and System Safety, 121, 43–60. https://doi.org/10.1016/j.ress.2013.06.040

Pant, R., Thacker, S., Hall, J. W., Alderson, D., & Barr, S. (2018). Critical infrastructure impact assessment due to flood exposure. Journal of Flood Risk Management, 11(1), 22–33. https://doi.org/10.1111/jfr3.12288

How to cite: Schotten, R. and Bachmann, D.: Conceptualization of a Critical Infrastructure Network – Model for Flood Risk Assessments, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-922, https://doi.org/10.5194/egusphere-egu21-922, 2021.

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