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Morphologic typologies and sediment budget for the ocean shoreline of Long Island, New York

Posted on:2004-11-05Degree:Ph.DType:Dissertation
University:State University of New York at Stony BrookCandidate:Batten, Brian KeithFull Text:PDF
GTID:1460390011970135Subject:Engineering
Abstract/Summary:
The Atlantic Coast of New York Monitoring Program (ACNYMP) collected approximately 3,136 beach profiles and seasonal aerial photography along the south shore of Long Island between 1995 and 2002. Data analysis for each profile consisted of identification or measurement of up to 44 parameters, which generated approximately 137,984 entries. Data were organized with a relational database to enable data access and analysis by geographic units, or individual to multiple stations. Analysis of these parameters showed several trends related to regional geomorphology. The slope of the glacial outwash plain in combination with increasing wave energy to the eastern end of the island influenced depth/distance to closure, beach width and volume and dune toe elevations.; Volumetric beach profile change was calculated to the 7.3 m (24 ft) depth contour, representing volume change from landward of the primary dune to below the depth of closure for the region between Jones Inlet and Montauk Point. Volume change was extrapolated alongshore between available stations with seasonal and end-member calculations performed. Residual volumes indicated a net gain in sand volume between 1995 and 2001. Artificial nourishment inputs into the system were removed from the calculations, therefore, it must be assumed that the gain represents an onshore flux of material at a minimum rate of 586,000 m3/yr (766,000 yd3/yr).; A combination of 44 profile properties were used to delineate areas of vulnerability to storm events or persistent erosion. It is often difficult to incorporate such a large number of parameters in an analysis; however, recent environmental studies into coastal typologies have demonstrated the value of clustering analysis techniques for dealing with large datasets of multiple parameters. Supervised clustering analysis was applied for the first time to a coastal data set, ACNYMP beach profiles were classified into one of three groups: a high risk profile, moderate risk profile and low risk profile. Thirteen areas of consistent high vulnerability were identified. Areas along Fire Island and Westhampton were similar to areas previously identified with vulnerability to breaching events by the U.S. Army Corps of Engineers.
Keywords/Search Tags:Profile, Island, Beach, Areas
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