Characterization of the Vulnerability of Road Networks to Fluvial Flooding Using Network Percolation Approach
Characterization of the Vulnerability of Road Networks to Fluvial Flooding Using Network Percolation Approach
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DOI：
10.1061/9780784482445.055
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发表时间：
2019-06
期刊：
影响因子：
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通讯作者：
B. Abdulla;A. Mostafavi;B. Birgisson
中科院分区：
文献类型：
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作者：
B. Abdulla;A. Mostafavi;B. Birgisson
本文的目的是在一个主要的河流洪水事件的道路网络的渗流动力学建模和表征。首先，一个道路系统建模为平面图，然后，使用的水平与防洪基础设施作为代理的道路网络的洪水脆弱性的共址相互依赖性，它估计的破坏程度，每个社区的道路网络经历了洪水事件。其次，在道路网络中的渗透机制，通过分配不同的删除概率，道路网络中的节点，根据贝叶斯规则捕获。最后，在随机和加权调整的节点删除的情况下，道路网络的鲁棒性的时间变化。所提出的方法被应用到道路洪水在一个超级社区在休斯敦飓风哈维。结果表明，基于贝叶斯规则的节点去除方案模拟的河流洪水造成的网络渗流会导致道路网络连通性以不同的速率下降。
The objective of this paper is to model and characterize the percolation dynamics in road networks during a major fluvial flooding event. First, a road system is modelled as planar graph, then, using the level of co-location interdependency with flood control infrastructure as a proxy to the flood vulnerability of the road networks, it estimated the extent of disruptions each neighborhood road network experienced during a flooding event. Second, percolation mechanism in the road network during the flood is captured by assigning different removal probabilities to nodes in road network according to a Bayesian rule. Finally, temporal changes in road network robustness were obtained for random and weighted-adjusted node-removal scenarios. The proposed method was applied to road flooding in a super neighborhood in Houston during hurricane Harvey. The result shows that, network percolation due to fluvial flooding, which is modelled with the proposed Bayes rule based node-removal scheme, causes the decrease in the road network connectivity at varying rate.