Future Resilient Systems at the Singapore-ETH Centre (SEC), ETH Zurich, Singapore.
Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland.
PLoS One. 2019 Jul 31;14(7):e0220338. doi: 10.1371/journal.pone.0220338. eCollection 2019.
Infrastructure systems are the structural backbone of cities, facilitating the flow of essential services. Because those systems can be disrupted by natural hazards, risk management has been the prevailing approach for assessing the consequences and expected level of damage. Although this may be a valuable metric, the practice of risk assessment does not represent how hazards affect a network of assets on a larger scale. In contrast, network topology metrics are useful because they evaluate the performance of network infrastructures by looking at the system as a whole. As described here, we began this study to improve our understanding of how flooding events affect the topological properties of road networks, in this case, the urban road infrastructure of Zurich, Switzerland. Using maps of flooding risk, we developed a procedure to extract the damaged networks and analyze the centrality metrics for peak water levels on the surface of the city. Our approach modelled roads as edges and junctions between roads as nodes. The betweenness centrality metric characterizes the importance of nodes or edges for any type of exchange within a network, whereas the closeness centrality metric measures the accessibility of a specific node to all the other nodes. This investigation produced three main findings. First, descriptive analyses showed that the characteristics and patterns of nodes and edges changed under the flooding events. Second, the distribution function of centrality metrics became heavier in the tails as the flood magnitude increased. Third, the associated strain shifted critical nodes to areas in which those nodes would not be important under normal conditions. These findings are essential for identifying crucial locations and devising plans to address risks. Future projects could expand our approach by including traffic flow to move the analysis closer to real-world flows, and by studying the accessibility under emergency conditions at local levels.
基础设施系统是城市的结构骨干，促进了基本服务的流动。由于这些系统可能会受到自然灾害的破坏，因此风险管理一直是评估后果和预期破坏程度的主要方法。尽管这可能是一个有价值的指标，但风险评估的实践并不能代表灾害如何在更大规模上影响资产网络。相比之下，网络拓扑指标很有用，因为它们通过整体评估系统来评估网络基础设施的性能。正如这里所描述的，我们开始这项研究是为了提高我们对洪水事件如何影响道路网络拓扑性质的理解，在这种情况下，是瑞士苏黎世的城市道路基础设施。我们使用洪水风险地图，开发了一种从受损网络中提取数据的程序，并分析了城市表面洪峰水位的中心性指标。我们的方法将道路建模为边缘，将道路之间的交点建模为节点。介数中心性指标描述了网络中任何类型的交换中节点或边缘的重要性，而接近中心性指标则衡量特定节点对所有其他节点的可达性。这项研究有三个主要发现。首先，描述性分析表明，在洪水事件下，节点和边缘的特征和模式发生了变化。其次，随着洪水规模的增加，中心性指标的分布函数在尾部变得更重。第三，相关的应变将关键节点转移到了正常情况下这些节点不重要的区域。这些发现对于确定关键位置和制定应对风险的计划至关重要。未来的项目可以通过包括交通流量来扩展我们的方法，使分析更接近实际流量，并通过研究局部紧急情况下的可达性。
