Research & Innovation

Stevens Researchers Study Hoboken to Develop Resiliency Framework for Flooding in Cities

Using Hoboken as a case study, the Stevens duo devised a data-driven method for predicting flood susceptibility in other flood-vulnerable cities such as New York City and New Orleans.

Female Stevens student in red hoodie walking on a Hoboken sidewalk after a rainshower.
Yeganeh Hayeri, Assistant Professor, School of Systems and Enterprises
Professor Hayeri's research explores decision-making analytics, surface transportation disruptions and applications of AI in transportation systems.

Yeganeh Hayeri, assistant professor at the School of Systems & Enterprises (SSE), alongside Raif Bucar, a Ph.D. candidate in the engineering management doctoral program, were recently published in Reliability Engineering & System Safety for developing a model assessing the resilience of city street networks during flood events.

Using Stevens Institute of Technology’s home city of Hoboken, New Jersey as the center of their case study, the researchers followed the framework of resiliency engineering which aims to retain infrastructure functionality under extreme conditions or events. The Stevens resiliency project looks to enhance the safety and efficiency of operations in U.S. surface transportation systems nationwide during frequent flooding conditions, resulting in strong societal and economic impacts. 

“Flood events are one of the most common natural disasters affecting the U.S., posing high safety risks to public transit users, pedestrians, and drivers and causing challenges to accessing transportation infrastructure,” said Hayeri. “We used Hoboken as the study area because of the city’s chronic problems with flooding and its continuing efforts to mitigate them. The goal was to help cities to develop effective transportation education and mitigation plans that could enhance the overall resilience of their city’s networks.”

Focusing on the flood-prone area of Hoboken, this model quantifies the effects flooding has on mobility and accessibility and predicts the ensuing driver behavior due to the disruptive patterns. These patterns are then simulated and evaluated during and after flooding disruptions through scenario generation. Results then provide a model to improve operational decision-making through prioritization and risk communication. For example, city authorities can use the model to plan road closures ahead of heavy precipitation events, and drivers can better navigate by detouring around flood-prone areas.

Although the case study used data specific to Hoboken, the completed framework is scalable to other flood-prone cities such as New York City and New Orleans. According to Hayeri, the obtained results should help authorities of such cities to effectively review their infrastructure strategic plans as well as their short and long-term urban mobility plans. Further, the researched framework will provide an educational tool to teach quantitative decision-making and risk analysis.

“This project is 100% on risk analysis, risk management and decision making, which relates to ‘SYS 660: Decision Making and Risk Analysis’ that I teach every spring semester,” said Hayeri. “Stevens projects and courses such as these exemplify how SSE tackles practical problems in our local community through research and education.”