Critical infrastructure (CI) networks are essential for the survival and functionality of society and the economy. Disruptions to CI services and the cascading effects of these disruptions are not currently included in flood risk management (FRM). The work presented in this study integrates CI into every step of FRM, including flood risk analysis, risk mitigation and risk communication. A CI network modelling technique enables the flood consequences for CI to be quantified as part of the flood risk analysis. The CI consequences derived from this analysis include spatial overviews and the temporal succession of CI disruptions. The number of affected CI end-users and the duration of the disruption are arranged in a risk matrix and in a decision-making matrix. Thus, the total flood risk is extended with CI consequences. By integrating CI and CI network characteristics into the flood risk assessment and the mitigation steps, a wider range of measures for action can be considered. Additionally, the continuous participation of CI operators is introduced as beneficial for every step of the FRM. A case study in Accra, Ghana proves the benefits of CI integration for all FRM steps. During participatory CI stakeholder engagements for this study six CI sectors were identified for the assembly of the CI network. The backbone of the analysis is a multisectoral, layered CI network model with 433 point elements, 1216 connector elements and 486 polygon elements.

In flood risk analysis, it is state‐of‐the‐art to determine the direct consequences of flooding for assets and people. Flooding also disrupts critical infrastructure (CI) networks, which are vital in modern society. Cascading effects in a CI network can exceed the hydrological catchment boundaries. The effects of directly impacted CI cascade to other infrastructures, which are thus indirectly affected by a flood. A robust modelling approach of CI networks is a basis for including these effects in flood risk analysis. One challenge is to balance the simplicity of the modelling approach, the reproduction of a CI network's complexity and the decisions made based on potential model outputs. In this article, a topology‐based modelling approach of CI networks for catchment‐wide flood risk analyses is proposed. The basic model elements are points, connectors and polygons, which are utilised to represent a multisectoral and layered CI network. The newly defined approach is implemented as CI network module to the state‐of‐the‐art flood risk analysis framework ProMaIDes. It analyses the CI's direct and cascading impacts as well as the indirect disruption of CI services triggered by flooding scenarios. It quantifies the consequences by determining the number of disrupted CI users or the disruption time. A proof of concept in Accra, Ghana demonstrates the method's capabilities.

<p>Floods are natural hazards with severe socio-economic and environmental impacts on affected areas and societies every year. A chain of different processes being involved in a flooding - characterized by precipitation, topography, land use etc. - complicates the understanding of the dynamics of a flood. However, the prediction of probabilities, flood hazards, flooding extents, dike failure, consequences and understanding the ongoing processes during a flood event are important issues in flood risk management. Computational modelling is a key method in supporting flood risk management and tackling the mentioned challenges.</p><p>While several computer-based models for assisting flood risk management exist, typically they concentrate on only one component of the flood risk analysis chain such as rainfall generation, hydrological/hydraulic modelling or damage analysis. They do not merge the other components on one platform which may result in encapsulated conclusions. In recent years the availability of higher detailed data, larger study domains, more computational power and more innovative models paved the way for more effective solutions.</p><p>In this work we present ProMaIDes (Protection Measures against Inundation Decision support), an open-source, free software package for risk-based evaluation of flood risk mitigation measures<sup>1</sup>. The software package consists of numerous relevant modules for a flood risk analysis in riverine and coastal regions: the HYD-module for a hydrodynamic analysis, the DAM-module for an analysis of consequences (including economical damage, consequences to people and the disruption of critical infrastructure services), the FPL-module for the reliability analysis of dikes and dunes as well as a combining RISK-module and the decision support MADM-module. To support a user-friendly model setup, visualization of input and data results, a connection with the free QGIS-system is established by QGIS-plugins and a PostgreSQL-database as data-management system. A detailed online documentation featuring theory, application and programming is available<sup>2</sup>. A community of users is currently set-up.</p><p>In order to give a better understanding and to demonstrate the capabilities of ProMaIDes, the tool itself, but also the modules combined with case studies are shortly presented.</p><p> </p><p><sup>1 </sup>https://promaides.h2.de</p><p><sup>2 </sup>https://promaides.myjetbrains.com/youtrack/articles/PMID-A-7/General</p>

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<p>In flood risk analysis it is a key element to determine consequences of flooding to assets, people and infrastructures. However, damages to critical infrastructure networks (CIN) are not always restricted to inundated areas. The effects of directly impacted objects cascade to other infrastructures, which are indirectly 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 in a flood risk analysis?’.</p><p>The modelling of complex CIN is utilized for different purposes: For modelling transportation routing, for damage assessments due to cyber attacks or infrastructure and interdependency analysis of water and waste water flow. For the purpose of flood risk assessments and, finally, in flood risk management application cases are scarce. The presented work introduced a method to overcome this gap. Major challenge is to balance the simplicity of a modeling approach with the resemblance of real interdependencies in a CIN and their task to supply services to end users. The more complex and realistic the network model is desired to be, the harder it is to gather the necessary data and the more expertise is necessary for potential users of this method. Additionally, users are required to switch from a raster or cell-based calculation philosophy to a network-based philosophy including points, connectors (edges) and areas (surfaces).</p><p>In this work, a network-based and topology-based method for a catchment-wide analysis is presented. The basic model elements (points, connectors and polygons) are utilized to model the complex CIN interdependencies. The CIN-module of the freely available software package ProMaIDes<sup>1</sup>, a state-of-the-art flood risk analysis tool, is used. The module is suited for an analysis of critical infrastructure damages, disruption of infrastructures and quantifies those damages by the number of disrupted users and the disruption duration. In a case study in Accra, Ghana, the method capabilities are showcased in a multisectoral model. Sectors included are electricity supply, fresh water supply, telecommunication services, health sector, emergency services and transportation. The model consists of 419 point elements, 472 polygon elements and 1124 connector elements. A synthetic precipitation event is used to visualize the reactions of the model as well as display first results. The case study has shown the flexibility and scalability of the introduced method to differentiate CI sector specifics. Consequently, the potential of the method to support flood risk management is discussed.</p><p> </p><p><sup>1 </sup>https://promaides.h2.de</p>