Urban stormwater flooding represents a persistent and escalating challenge for transportation networks and the well-being of urban populations, causing significant disruptions, economic losses, and safety hazards. This research project directly addresses this critical issue by advancing the development and validation of empirical models capable of predicting the depth and velocity of floodwaters in urban environments under a range of precipitation scenarios. Building upon prior successful modeling efforts focused on a singular urban context (Newark, NJ) and a specific precipitation event, this year's research significantly expands in scope and complexity. The investigation now encompasses three additional diverse New Jersey municipalities – Englewood, Irvington, and Asbury Park – each with unique geomorphic characteristics and flooding histories.

A central focus of this project is to establish robust correlations between key flood parameters – water depth and velocity – and a spectrum of precipitation conditions, including design storms with varying return periods (2, 10, 50, 100, and 500 years). To achieve this, the project will employ advanced two-dimensional (2D) hydrodynamic simulations utilizing the Hydraulic Engineering Center’s River Analysis System (HEC-RAS) with a rain-on-grid approach. This sophisticated modeling technique allows for a detailed representation of overland flow, surface water accumulation, and its interaction with urban terrain and infrastructure at strategically selected sites within each of the target cities. The selection of these sites prioritizes areas with documented flooding incidents and transportation significance, ensuring the models are calibrated and validated against real-world conditions.

The project's methodology incorporates a rigorous analytical framework. Initial site selection will leverage publicly available GIS data to characterize key geomorphic parameters such as drainage area and slope. Subsequently, the HEC-RAS 2D simulations will generate detailed outputs, including hydrographs, water depth distributions, and velocity fields for each precipitation scenario at each site. To extract meaningful relationships from this extensive dataset, principal component analysis (PCA) will be applied to refine the correlations between precipitation characteristics and the resulting floodwater depth and velocity. This analysis will identify the most influential precipitation parameters and quantify their impact on flood behavior across different urban settings.

The anticipated outcomes of this research are significantly enhanced empirical models capable of accurately predicting flood inundation and flow dynamics under a variety of rainfall events. These models will serve as the foundation for generating high-resolution, spatially explicit stormwater flood maps tailored to the specific characteristics of Englewood, Irvington, and Asbury Park. These maps will provide invaluable insights for urban planners, emergency responders, and transportation agencies, enabling more effective flood preparedness, risk assessment, and infrastructure management strategies. By informing resilient infrastructure solutions, this research also contributes to fostering safer and more resilient urban environments.