Flood hazard assessment from storm tides, rain and sea level rise for a tidal river estuary

  • P. M. Orton
  • F. R. Conticello
  • F. Cioffi
  • T. M. Hall
  • N. Georgas
  • U. Lall
  • A. F. Blumberg
  • K. MacManus
Original Paper


Cities and towns along the tidal Hudson River are highly vulnerable to flooding through the combination of storm tides and high streamflows, compounded by sea level rise. Here a three-dimensional hydrodynamic model, validated by comparing peak water levels for 76 historical storms, is applied in a probabilistic flood hazard assessment. In simulations, the model merges streamflows and storm tides from tropical cyclones (TCs), offshore extratropical cyclones (ETCs) and inland “wet extratropical” cyclones (WETCs). The climatology of possible ETC and WETC storm events is represented by historical events (1931–2013), and simulations include gauged streamflows and inferred ungauged streamflows (based on watershed area) for the Hudson River and its tributaries. The TC climatology is created using a stochastic statistical model to represent a wider range of storms than is contained in the historical record. TC streamflow hydrographs are simulated for tributaries spaced along the Hudson, modeled as a function of TC attributes (storm track, sea surface temperature, maximum wind speed) using a statistical Bayesian approach. Results show WETCs are important to flood risk in the upper tidal river (e.g., Albany, New York), ETCs are important in the estuary (e.g., New York City) and lower tidal river, and TCs are important at all locations due to their potential for both high surge and extreme rainfall. The raising of floods by sea level rise is shown to be reduced by ~ 30–60% at Albany due to the dominance of streamflow for flood risk. This can be explained with simple channel flow dynamics, in which increased depth throughout the river reduces frictional resistance, thereby reducing the water level slope and the upriver water level.


Floods Storm surge Sea level rise Tidal river Tropical cyclones Hudson River 



We would like to acknowledge the vision and leadership of Mark G. Becker (1961–2014), who was an original Principal Investigator for the project. Amanda Stevens, Jane Mills and Dara Mendeloff also played important roles in the project.


This research was primarily funded by New York State Energy Research and Development Authority (NYSERDA; Agreement 28258A). Funding also came from the National Aeronautics and Space Administration (NASA) Centers call for support of the National Climate Assessment (Agreements NNX12AI28G and NNX15AD61G) and Research Opportunities in Space and Earth Sciences (NASA-ROSES-2012; grant NNX14AD48G). Modeling was made possible by a grant of computer time from the City University of New York High Performance Computing Center under NSF Grants CNS-0855217, CNS-0958379 and ACI-1126113.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Stevens Institute of TechnologyHobokenUSA
  2. 2.Dipartimento di Ingegneria Civile, Edile ed Ambinetale, DICEA“La Sapienza” University of RomeRomeItaly
  3. 3.NASA Goddard Institute for Space StudiesNew YorkUSA
  4. 4.Columbia UniversityNew YorkUSA
  5. 5.Columbia University Center for International Earth Science Information Network (CIESIN)PalisadesUSA

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