Joint optimization of flood water routing and congestion-aware evacuation scheduling

• Presents a joint optimization model for coordinating flood routing and vehicular evacuation. • Integrates the Muskingum-Cunge and Cell Transmission Models to capture water-traffic interactions. • Uses Benders decomposition to solve the nonlinear evacuation problem efficiently. • Demonstrates improvements in evacuation performance through a real-world case study. Urban flood emergencies pose significant risks to human safety and infrastructure operability, particularly in smart cities with interdependent systems. This study proposes an integrated optimization model for coordinating water and transportation networks during flood evacuations. The model simultaneously determines optimal reservoir discharge rates and dynamic vehicular evacuation schedules to maximize the number of evacuees within the limited warning time. Water flow is modeled using the Muskingum-Cunge flood-routing method to simulate flood propagation through a river-reservoir system, while traffic flow is captured via the Cell Transmission Model, which accounts for congestion dynamics and road capacities. The problem is formulated as a nonlinear program and solved through a linear relaxation using generalized Benders decomposition. A case study of the Town of High River, Canada, illustrates the model’s practical utility. Results show that the integrated strategy extends warning times, reduces congestion, and lowers the number of individuals exposed to flood risks compared to uncoordinated approaches. By enabling real-time, infrastructure-aware evacuation planning, the proposed framework offers a scalable decision-support tool for emergency managers. This work contributes to the growing body of research on the management of city infrastructures under disruption and supports the development of resilient and coordinated evacuation strategies in smart urban environments.