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The AAPG/Datapages Combined Publications Database

Environmental Geosciences (DEG)

Abstract

 

DOI: 10.1046/j.1526-0984.2001.008001011.x
© 2001 American Association of Petroleum Geologists (AAPG)

Applications of Digital Elevation Models and Geographic Information Systems to Coastal Flood Studies along the Shoreline of Raritan Bay, New Jersey

John Dobosiewicz1

1Rutgers University, New Brunswick, NJ 07068

John Dobosiewicz is a Ph.D. Candidate in the Department of Geography at Rutgers University in New Brunswick, New Jersey. His research interests are in Physical Geography and the application of Geographic Information Systems (GIS) to the study of hazards, especially in coastal environments. He is also an adjunct instructor in the Department of Geography at Rutgers University and the Department of Geology and Meteorology at Kean University in Union, New Jersey.

ABSTRACT

Geographic information systems (GIS) are increasingly used in coastal hazard research for coastal management and for analysis of information following major storm events because of their ability to evaluate multiple data sets. Digital flood zone data sets and qualitative post storm flood water level observations exist for Raritan Bay, New Jersey, an urban estuary. A desktop GIS is used to overlay different digital data sets containing flood zone information and determine the number and length of roads that are within the flood zone. The elevation of the 1% probability flood zone on the digital elevation model is determined from a long-term tidal record at Sandy Hook, New Jersey and roads flooded during a major coastal storm in December 1992. In this article, 1% probability flood zones, also called the 100-year flood zone, are calculated using digital elevation models and compared to 1% probability flood zones from the Federal Emergency Management Agency and the New Jersey Department of Environmental Protection. The 1% probability flood is typically used for flood zone management. The results indicate that digital elevation models and GIS can be used to identify roads that would be flooded by the 1% probability flood comparable to roads found on existing flood zone maps.

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