Authors: Christopher Amante*, CIRES, University of Colorado Boulder and NOAA National Centers for Environmental Information
Topics: Geographic Information Science and Systems, Hazards, Risks, and Disasters, Coastal and Marine
Keywords: DEM, Uncertainty, Sea-level Rise, Storm Surge, Probabilistic Flood Model
Session Type: Paper
Start / End Time: 9:55 AM / 11:35 AM
Room: Balcony B, Marriott, Mezzanine Level
Presentation File: No File Uploaded
Future sea-level rise will likely expand the inland extent of storm surge inundation and, in turn, increase the vulnerability of the people, property and economy of coastal communities. Modeling future storm surge inundation enhanced by sea-level rise utilizes numerous data sources with inherent uncertainties. There is uncertainty in the (1) hydrodynamic storm surge models, (2) future sea-level rise projections, and (3) topographic digital elevation models representing the height of the coastal land surface. This study implements a Monte Carlo technique to incorporate the uncertainty of these data sources and model the future 1% flood zone in the Tottenville neighborhood of New York City (NYC) in a geographical information science (GIS) framework. Generated spatiotemporal statistical products indicate the future flood zone and its uncertainty in Tottenville. Small changes in the modeled land and water heights result in large uncertainty in the future flood zone in low-lying areas with small terrain slope. There is also larger uncertainty in the future flood zone in later decades due to increasing uncertainty in sea-level rise projections. An interactive web map, UncertainSeas.com, visualizes these statistical products and can inform coastal management policies to reduce the vulnerability of Tottenville, NYC to future coastal inundation.