Multiagent Simulation for Complex Adaptive Modeling of Road Infrastructure Resilience to Sea‐Level Rise

Infrastructure systems in coastal areas are exposed to episodic flooding exacerbated by sea-level rise stressors. To enable assessing the long-term resilience of infrastructure to such chronic impacts of sea-level rise, the present study created a novel complex system modeling framework that integrates: (i) stochastic simulation of sea-level rise stressors, based on the data obtained from downscaled climate studies pertaining to future projections of sea level and precipitation; (ii) dynamic modeling of infrastructure conditions by considering regular decay of infrastructure, as well as structural damages caused by flooding; and (iii) a decision-theoretic modeling of infrastructure management and adaptation processes based on bounded rationality and regret theories. Using the proposed framework and data collected from a road network in Miami, a multiagent computational simulation model was created to assess the long-term cost and performance of the road network under various sea-level rise scenarios, adaptation approaches, and network degradation effects. The results showed the capabilities of the proposed computational model for robust planning and scenario analysis to enhance the resilience of infrastructure systems to sea-level rise impacts.