  Natural hazards including floods can trigger catastrophic failures in
interdependent urban transport network-of-networks (NoNs). Population growth
has enhanced transportation demand while urbanization and climate change have
intensified urban floods. However, despite the clear need to develop actionable
insights for improving the resilience of critical urban lifelines, the theory
and methods remain underdeveloped. Furthermore, as infrastructure systems
become more intelligent, security experts point to the growing threat of
targeted cyber-physical attacks during natural hazards. Here we develop a
hypothesis-driven resilience framework for urban transport NoNs, which we
demonstrate on the London Rail Network (LRN). We find that topological
attributes designed for maximizing efficiency rather than robustness render the
network more vulnerable to compound natural-targeted threats including
cascading failures. Our results suggest that an organizing principle for
post-disruption recovery may be developed with network science principles. Our
findings and frameworks can generalize to urban lifelines and more generally to
real-world spatial networks.
