Data to Decisions: Using Stormwater Technology and AI to Guide Smarter Land Use in New Jersey
Artificial intelligence, or “AI,” is colloquially understood as language-learning models (LLMs), such as ChatGPT, or webpage-specific assistants, such as X’s Grok or Google’s Gemini. What these models have in common is their ability to absorb aggregate data, synthesize it, and produce insights. Whether this data comes in the form of a question about the best restaurants in New Jersey for a dinner date or a request to solve a complex math equation, the processes behind AI’s functionality remain the same, giving it near limitless applications. But what if, instead of being used to answer individual queries, it could be used to guide complex land-use and planning decisions affecting entire communities?
This question was explored at this year’s New Jersey Planning and Redevelopment Conference, co-hosted by New Jersey Future and APA NJ. The session, “Data to Decisions: Using Stormwater Technology and AI to Guide Smarter Land Use in New Jersey”, convened expert practitioners pioneering AI technology to address stormwater challenges exacerbated by climate change. Moderated by New Jersey Future’s Climate Adaptation Manager, Molly Riley, attendees learned from Dr. Yi Bao, founding director of Smart Infrastructure Laboratory at Stevens Institute of Technology, Dr. Brett Banco, Executive Director of the Science and Resilience Institute at Jamaica Bay, and co-lead of FloodNet NYC, and Dr. Efthymios Nikolopoulos, Co-Director of Rutgers University Flood Resilience Lab.
Flood risk today is dynamic, hyperlocal, and increasingly unpredictable. The realities of a changing climate, compounded by outdated and backward-looking FEMA flood maps, create gaps in local understanding of vulnerability. Traditionally safe areas are now threatened by fast-rising urban flash flooding. As Dr. Nikolopoulos highlighted, an estimated $197 billion worth of buildings are vulnerable to flooding in New Jersey. As weather patterns become increasingly extreme and new impervious surfaces are created, AI-powered tools can help communities understand and adapt to their new normal. Dr. Bao described this shift, “These systems do not just collect data, but also analyze it, learn from it, and support decision-making. The goal is to move from reactive management to proactive and adaptive management.” Dr. Bao, along with his 16-person research team, is also using smart drones for infrastructure assessment, sensor networks, and pipeline monitoring to assess conditions in real time during extreme weather events. By integrating intelligence into infrastructure, municipalities can identify maintenance priorities, target investments, and better prepare for future storms.
While AI-powered analysis is crucial to understanding emerging vulnerabilities, panelists also emphasized that direct community engagement is needed to connect data with residents’ lived experiences. Dr. Branco, through FloodNet NYC, works to install networks of low-cost flood sensors to provide real-time, on-the-ground monitoring of urban flooding, partnering with communities to help them understand the data, determine where sensors should go, and receive feedback on where flooding impacts their daily lives. This partnership ensures the technology reflects the realities residents face, creating hyper-local data sources that can support emergency responders and planners.
Smart, predictive models of climate vulnerabilities should not exist in a vacuum. As municipalities seek development and redevelopment opportunities, these AI-powered tools can provide an additional layer of project approvals to ensure that new investments are resilient in the face of a changing climate. Dr. Nikolopoulos shared insights through Flood Smart Elizabeth, an operational flood intelligence system that spans fluvial, pluvial, combined sewer, and coastal flood events into a single platform. In densely packed cities, like Elizabeth, where aging infrastructure, combined sewer systems, and limited first-floor elevations compound flood vulnerability, real-time monitoring and predictive forecasting provide emergency responders and local officials with previously inaccessible information to guide decision-making. Dr. Nikolopoulos argued that these systems should become a form of planning infrastructure by incorporating monitoring systems and data requirements into redevelopment approvals and long-term land-use planning.
As New Jersey communities face increasingly frequent and severe flooding, this session challenged attendees to consider emerging technologies as a resource for municipalities in adapting to climate change. By combining real-time monitoring, predictive analytics, and community knowledge, AI-powered technologies can help to proactively identify vulnerabilities, prioritize infrastructure upgrades, and keep residents informed. Going forward, these tools can be integrated into municipal planning, supporting redevelopment plans, Climate Change-Related Hazard Vulnerability Assessments (CCRHVA), and compliance with new regulations, such as Resilient Environments and Landscapes (REAL), which require municipalities to consider future flood risk. As planning decisions become more complex in the face of climate change, turning data into action will be essential for building safer, more resilient communities across New Jersey.
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