Street-Scale Modeling of Storm Surge Inundation along the New Jersey Hudson River Waterfront

Alan F. Blumberg Stevens Institute of Technology, Hoboken, New Jersey

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Nickitas Georgas Stevens Institute of Technology, Hoboken, New Jersey

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Larry Yin Stevens Institute of Technology, Hoboken, New Jersey

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Thomas O. Herrington Stevens Institute of Technology, Hoboken, New Jersey

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Philip M. Orton Stevens Institute of Technology, Hoboken, New Jersey

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Abstract

A new, high-resolution, hydrodynamic model that encompasses the urban coastal waters of New Jersey along the Hudson River Waterfront opposite New York City, New York, has been developed and validated for simulating inundation during Hurricane Sandy. A 3.1-m-resolution square model grid combined with a high-resolution lidar elevation dataset permits a street-by-street focus to inundation modeling. The waterfront inundation model is a triple-nested Stevens Institute Estuarine and Coastal Ocean Hydrodynamic Model (sECOM) application; sECOM is a successor model to the Princeton Ocean Model family of models. Robust flooding and drying of land in the model physics provides for the dynamic prediction of flood elevations and velocities across land features during inundation events. The inundation model was forced by water levels from the extensively validated New York Harbor Observing and Prediction System (NYHOPS) hindcast of that hurricane.

Validation against 56 watermarks and 16 edgemarks provided via the USGS and through an extensive crowdsourcing effort consisting of photographs, videos, and personal stories shows that the model is capable of computing overland water elevations quite accurately throughout the entire surge event. The correlation coefficient (R2) between the watermark observations and the model results is 0.92. The standard deviation of the residual error is 0.07 m. Comparisons to the 16 flood edgemarks suggest that the model was able to reproduce flood extent to within 20 m. Because the model was able to capture the spatial and temporal variation of water levels in the region observed during Hurricane Sandy, it was used to identify the flood pathways and suggest where flood-preventing interventions could be built.

Corresponding author address: Alan F. Blumberg, Davidson Laboratory, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ 07030. E-mail: alan.blumberg@stevens.edu

Abstract

A new, high-resolution, hydrodynamic model that encompasses the urban coastal waters of New Jersey along the Hudson River Waterfront opposite New York City, New York, has been developed and validated for simulating inundation during Hurricane Sandy. A 3.1-m-resolution square model grid combined with a high-resolution lidar elevation dataset permits a street-by-street focus to inundation modeling. The waterfront inundation model is a triple-nested Stevens Institute Estuarine and Coastal Ocean Hydrodynamic Model (sECOM) application; sECOM is a successor model to the Princeton Ocean Model family of models. Robust flooding and drying of land in the model physics provides for the dynamic prediction of flood elevations and velocities across land features during inundation events. The inundation model was forced by water levels from the extensively validated New York Harbor Observing and Prediction System (NYHOPS) hindcast of that hurricane.

Validation against 56 watermarks and 16 edgemarks provided via the USGS and through an extensive crowdsourcing effort consisting of photographs, videos, and personal stories shows that the model is capable of computing overland water elevations quite accurately throughout the entire surge event. The correlation coefficient (R2) between the watermark observations and the model results is 0.92. The standard deviation of the residual error is 0.07 m. Comparisons to the 16 flood edgemarks suggest that the model was able to reproduce flood extent to within 20 m. Because the model was able to capture the spatial and temporal variation of water levels in the region observed during Hurricane Sandy, it was used to identify the flood pathways and suggest where flood-preventing interventions could be built.

Corresponding author address: Alan F. Blumberg, Davidson Laboratory, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ 07030. E-mail: alan.blumberg@stevens.edu
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