Schneider Moritz, Halekotte Lukas, Mentges Andrea, Fiedrich Frank
Institute for the Protection of Terrestrial Infrastructures, German Aerospace Center, Sankt Augustin, Germany.
Chair for Public Safety and Emergency Management, University of Wuppertal, Wuppertal, Germany.
Sci Rep. 2025 Feb 17;15(1):5736. doi: 10.1038/s41598-025-89469-0.
Critical infrastructures provide essential services for our modern society. Large-scale natural hazards, such as floods or storms, can disrupt multiple critical infrastructures at once. In addition, a localized failure of one service can trigger a cascade of failures of other dependent services. This makes it challenging to anticipate and prepare adequately for direct and indirect consequences of such events. Existing methods that are spatially explicit and consider service dependencies currently lack practicality, as they require large amounts of data. To address this gap, we propose a novel method called DISruptionMap which analyzes complex disruptions to critical infrastructure services. The proposed method combines (i) spatial service models to assess direct service disruptions with (ii) a service dependency model to assess indirect (cascading) service disruptions. A fault tree-based approach is implemented, resulting in a significant decrease in the information required to set up the service dependency model. We demonstrate the effectiveness of our method in a case study examining the impact of an extreme flood on health, transport, and power services in Cologne, Germany.
关键基础设施为我们的现代社会提供基本服务。大规模自然灾害，如洪水或风暴，可能会同时扰乱多个关键基础设施。此外，一项服务的局部故障可能引发其他相关服务的一连串故障。这使得预测和充分应对此类事件的直接和间接后果具有挑战性。现有的空间明确且考虑服务依赖性的方法目前缺乏实用性，因为它们需要大量数据。为了填补这一空白，我们提出了一种名为DISruptionMap的新方法，该方法分析对关键基础设施服务的复杂干扰。所提出的方法将（i）用于评估直接服务中断的空间服务模型与（ii）用于评估间接（级联）服务中断的服务依赖性模型相结合。实施了基于故障树的方法，从而显著减少了建立服务依赖性模型所需的信息。我们在一个案例研究中展示了我们方法的有效性，该案例研究考察了极端洪水对德国科隆的健康、交通和电力服务的影响。
