FUZZY LOGIC-BASED BEACH-DUNE SYSTEM ASSESSMENT METHODOLOGY: DEVELOPMENT AND INITIAL APPLICATIONS

Coastal communities and economies are important to New Jersey's prosperity and quality of life, but they are vulnerable to devastating affects from hurricanes and northeast (“nor'easter”) storms. The last decade has experienced a number of unusually active storm seasons (particularly 2003-2005 and 2008), continuing a 20-25 year long trend of enhanced activity in the Atlantic basin that began in 1995. This increasing trend in storm activity has coincided with a decreasing trend in Federal funding for shore protection and beach nourishment. Since about 2002, responsibility for protecting and maintaining the coast has incrementally shifted to State and municipal governments.

The beach and dune system of New Jersey's barrier islands and spits is a vital natural resource that protects shore communities against storm damage. Assessments of the beach-dune system are important for effective management and sustainability of this coastal zone resource, and facilitate more efficient use of limited State and municipal resources by optimizing storm hazard mitigation activities.

A geospatial beach-dune system susceptibility assessment, which uses a knowledge-driven, spatial data integration technique (fuzzy logic), was developed to evaluate performance potential of the natural beach-dune system, identifying weaknesses and highlighting areas that may be vulnerable to storm damage (such as erosion, overwash, or breach). The beach-dune system is segmented long-shore into “bins” based upon lot-block lines (for local-scale assessments) or a larger fixed interval (for regional-scale assessments). For each bin, several variables relating to dune, beach, and nearshore geomorphology, and to presence of vegetation and structures (such as groins), are collected, compiled, and evaluated in order to determine the susceptibility of the beach-dune system to potential damage from storm activity. These susceptibility variables are quantified and, using expert knowledge, assigned a weight-of-influence (or fuzzy membership value) with respect to their abilities to withstand or counteract storm erosion. LiDAR elevation and bathymetry-profile survey data are used in wave run-up erosion simulations to determine the failure point of the system for each bin (the point of failure is defined as dune crest breach in response to landward erosional recession of the foredune toe). Simulations are run for 2-year, 5-year, 10-year, 20-year, 50-year, and 100-year storm events using parameters developed by FEMA. The results of the erosion simulations are used to specify the value of a fuzzy GAMMA operator, which mathematically integrates the fuzzy membership values assigned to the susceptibility variables, and to classify the resulting susceptibility values into intervals.

The assessment results are conveyed as a series of “susceptibility maps” that consist of an aerial photograph on which two bin-segmented strips are overlain along the extent of the beachfront (fig. 1). Individual maps are made for 2-year, 5-year, 10-year, 20-year, 50-year, and 100-year storm events. One strip is an absolute measure of vulnerability to storm erosion, and is made in relation to a 100-year intensity storm as the worst-case scenario. The other is a relative measure of vulnerability to storm erosion, and is made in comparison to all bins for a given storm intensity.