2018 CSDMS meeting-113: Difference between revisions
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|CSDMS meeting abstract title=A Coupled Geo-Economic Model for Artificial Berm-Dune Management along New Jersey’s Coastline | |||
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|CSDMS meeting coauthor first name abstract=Jorge | |||
|CSDMS meeting coauthor last name abstract=Lorenzo-Trueba | |||
|CSDMS meeting coauthor institute / Organization=Montclair State University | |||
|CSDMS meeting coauthor town-city=Montclair | |||
|CSDMS meeting coauthor country=United States | |||
|State=New Jersey | |||
|CSDMS meeting coauthor email address=lorenzotruej@mail.montclair.edu | |||
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|CSDMS meeting coauthor first name abstract=Porter | |||
|CSDMS meeting coauthor last name abstract=Hoagland | |||
|CSDMS meeting coauthor institute / Organization=Marine Policy Center, WHOI | |||
|CSDMS meeting coauthor town-city=Woods Hole | |||
|CSDMS meeting coauthor country=United States | |||
|State=Massachusetts | |||
|CSDMS meeting coauthor email address=phoagland@whoi.edu | |||
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|CSDMS meeting coauthor first name abstract=Di | |||
|CSDMS meeting coauthor last name abstract=Jin | |||
|CSDMS meeting coauthor institute / Organization=Marine Policy Center, WHOI | |||
|CSDMS meeting coauthor town-city=Woods Hole | |||
|CSDMS meeting coauthor country=United States | |||
|State=Massachusetts | |||
|CSDMS meeting coauthor email address=djin@whoi.edu | |||
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|CSDMS meeting coauthor first name abstract=Andrew | |||
|CSDMS meeting coauthor last name abstract=Ashton | |||
|CSDMS meeting coauthor institute / Organization=Geology and Geophysics Department, WHOI | |||
|CSDMS meeting coauthor town-city=Woods Hole | |||
|CSDMS meeting coauthor country=United States | |||
|State=Massachusetts | |||
|CSDMS meeting coauthor email address=aashton@whoi.edu | |||
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{{CSDMS meeting abstract template 2018 | |||
|CSDMS meeting abstract=After Superstorm Sandy impacted the New Jersey coastline in 2012, the primary coastal resiliency plan was to fortify the entire shoreline with large-scale berm-dune systems. These features, funded entirely by Congress, were constructed to mitigate future storm-damage. Two basic management questions are 1) whether it is feasible for a beachfront community to maintain these projects over the long-term; and 2) if not, what fraction of the cost would need to be subsidized. To tackle these questions, we use a “geo-economic” model that captures the natural processes of beach and dune erosion and migration via storm overwash, coupled with engineering interventions of beach nourishment and dune construction. Additionally, the model accounts for the relationship between property values and berm-dune geometry. Previous work suggests that property values rise as dune height and beach width increase, due to their protective and recreational value. However, it is unclear whether this relationship holds true for dune protection some years after a storm has occurred. Lags in major storm events may lead to a perception of lower risks. Thus, beachfront communities may place greater value upon viewership and private property, rather than on protection by artificial dunes. By deriving mathematical expressions for optimal berm and dune size as a function of geologic and economic parameters, our model suggests that change in risk perception can lower property values and therefore reduce the ability of a community to keep up with the costs of maintaining these structures. We are currently testing this hypothesis by analyzing past and present LiDAR imagery (i.e. 2010, 2014, and 2018) and real-estate data from Long Beach Island, NJ. | |||
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Revision as of 09:07, 28 March 2018
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A Coupled Geo-Economic Model for Artificial Berm-Dune Management along New Jersey’s Coastline
After Superstorm Sandy impacted the New Jersey coastline in 2012, the primary coastal resiliency plan was to fortify the entire shoreline with large-scale berm-dune systems. These features, funded entirely by Congress, were constructed to mitigate future storm-damage. Two basic management questions are 1) whether it is feasible for a beachfront community to maintain these projects over the long-term; and 2) if not, what fraction of the cost would need to be subsidized. To tackle these questions, we use a “geo-economic” model that captures the natural processes of beach and dune erosion and migration via storm overwash, coupled with engineering interventions of beach nourishment and dune construction. Additionally, the model accounts for the relationship between property values and berm-dune geometry. Previous work suggests that property values rise as dune height and beach width increase, due to their protective and recreational value. However, it is unclear whether this relationship holds true for dune protection some years after a storm has occurred. Lags in major storm events may lead to a perception of lower risks. Thus, beachfront communities may place greater value upon viewership and private property, rather than on protection by artificial dunes. By deriving mathematical expressions for optimal berm and dune size as a function of geologic and economic parameters, our model suggests that change in risk perception can lower property values and therefore reduce the ability of a community to keep up with the costs of maintaining these structures. We are currently testing this hypothesis by analyzing past and present LiDAR imagery (i.e. 2010, 2014, and 2018) and real-estate data from Long Beach Island, NJ.
