We propose a solution based on a multiplex network science-multiscale system dynamics simulation and analysis framework that captures interdependencies between infrastructure systems modeled as networks and installations modeled as dynamical systems, with the installations’ boundary conditions determined by the state of the networks they depend upon. Our approach captures indirect failures and complex dependency structures, enabling what-if scenario generation and decision support for adaptation planning and disaster recovery under constrained budgets. This can reduce human and economic losses caused by natural disasters through a quantification of resilience and efficiency in stakeholder decision making processes, drawing from network science, catastrophe modeling, and resilience analysis to do so. We selected a case study in Augusta, Maine, chosen with consideration of generalizability to other cities across the United States.