Adaptive capacity for multimodal transport network resilience to extreme floods

As extreme weather events enhanced by climate change pose challenges to the resilience of critical infrastructure, the ability to handle disruptions, avoid tipping points, adapt and transform in crises becomes essential. Despite advances in resilience research, there is a need to improve empirical evidence and mathematical models to quantify the systems’ adaptive capabilities to extreme climate-related phenomena, such as floods. This research fills this gap by integrating an agent-based multimodal traffic functional model with a compound failure model to provide valuable insights into adaptation patterns (that is, mode shift and route switching) and risk mitigation in response to flood-related disruptions. The proposed modelling approach not only quantifies the recovery and adaptive capacity against failures, going beyond traditional resilience analyses, but also unveils the key factors that drive adaptation of transportation to flood-induced disasters. These factors include variations in trip demand and network density, which together reveal a universal law of mode shift. The study provides valuable insights into the design of resilient and sustainable critical infrastructure systems, such as transportation, energy and communication systems capable of withstanding severe flood events while maintaining their functionality.