This study used a data base of shoreline positions (digitized from aerialrnphotographs) through time (1930s to 1980s) for 55 km of the Maryland and Delawarerncoasts and 144 km of the North Carolina coast to detect statistical outliers that have thernpotential to increase shoreline prediction uncertainty. Comparing the outliers to thernmagnitude and timing of the largest storm prior to a photo date gave an a posteriorirnmeans of assessing the impact of a storm on shoreline positions. Analyses of the outliersrnrelative to two storm indices, wave energy and erosion potential, showed that storms playrna greater role in producing outliers in Maryland and Delaware than in North Carolina.rnThe spatial and temporal variability in storm response along the U.S. Eastern seaboardrnsuggest that no single holistic or “correct” approach exists for treating post-storm data inrnthe analysis of historical shoreline change data and development of shoreline changernmodels. However, conducting outlier tests, like those used in this study, coupled withrnincorporating model terms that utilize multiple driving processes, will engender greaterrnconfidence in assessments of historical shoreline change, and predictions of future short-rnand long-term shoreline positions.
展开▼
