Local floods induce large-scale abrupt failures of road networks

Abstract

The adverse effect of climate change continues to expand, and the risks of flooding are increasing. Despite advances in network science and risk analysis, we lack a systematic mathematical framework for road network percolation under the disturbance of flooding. The difficulty is rooted in the unique three-dimensional nature of a flood, where altitude plays a critical role as the third dimension, and the current network-based framework is unsuitable for it. Here we develop a failure model to study the effect of floods on road networks; the result covers 90.6% of road closures and 94.1% of flooded streets resulting from Hurricane Harvey. We study the effects of floods on road networks in China and the United States, showing a discontinuous phase transition, indicating that a small local disturbance may lead to a large-scale systematic malfunction of the entire road network at a critical point. Our integrated approach opens avenues for understanding the resilience of critical infrastructure networks against floods.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 15, 2019
Source ID
10.1038/s41467-019-10063-w

Entities

People

  • H. Eugene Stanley
  • Jianxi Gao
  • Saini Yang
  • Weiping Wang

Organizations

  • China Scholarship Council
  • Defense Threat Reduction Agency
  • National Science Foundation
  • Science Fund for Creative Research Groups

Tags

Readers

  • Economics
  • Neural Network Machine Learning.
  • Pavement Materials Engineering.