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Journal Article

Citation

Wehrle R, Wiens M, Schultmann F. Prog. Disaster Sci. 2022; 16: e100258.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.pdisas.2022.100258

PMID

unavailable

Abstract

PURPOSE
This paper aims to enable the evaluation of systemic risks resulting from missing or misallocated repair measures of inland waterways infrastructure. In this context, cascading effects and risks arising from interdependent Critical Infrastructures (CIs) are of particular interest. The systemic risk assessment is implemented as a GIS-based tool to support decision makers in a risk-based maintenance strategy.
Methodology
A framework based on a chain of interdependent risks of different levels of the system represents the base model. The interlinkages of industries are quantified by Input-Output-Modeling and the spatial dimension is implemented as a GIS-based decision tool.
Findings
From an analytical perspective, the close interconnection of the systems' levels (subsystems) under consideration can be traced. The results highlight critical buildings leading to potentially serious impacts on industry and population if the infrastructure elements are not maintained.
Research limitations
This research is focused on the framework and impacts on interdependent CIs, while work on the vulnerability of constructions and population protection, which complements our approach, is explored in more depth elsewhere.
Practical implications
Maintenance of infrastructure elements should be more risk-based than time-oriented to avoid potential damage and reduce impacts.
Originality
We examine the interconnected subsystems construction, industry and population in an aggregated risk framework to quantify risks stemming from complex infrastructure interdependencies with waterways as rarely explored infrastructure in this context. The implementation of a decision support tool for infrastructure operators as risk dashboard enables the integration of the approach into everyday infrastructure risk management.


Language: en

Keywords

Empirical; GIS; Input-output-model; Risk; Waterways

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