Evaluation of anthropogenic influence in probabilistic forecasting of coastal change

Abstract:

Prediction of large scale coastal behavior is especially challenging in areas of pervasive human activity. Many coastal zones on the Gulf and Atlantic coasts are moderately to highly modified through the use of soft sediment and hard stabilization techniques. These practices have the potential to alter sediment transport and availability, as well as reshape the beach profile, ultimately transforming the natural evolution of the coastal system.

We present the results of a series of probabilistic models, designed to predict the observed geomorphic response to high wave events at Fire Island, New York. The island comprises a variety of land use types, including inhabited communities with modified beaches, where beach nourishment and artificial dune construction (scraping) occur, unmodified zones, and protected national seashore. This variation in land use presents an opportunity for comparison of model accuracy across highly modified and rarely modified stretches of coastline.

Eight models with basic and expanded structures were developed, resulting in sixteen models, informed with observational data from Fire Island. The basic model type does not include anthropogenic modification. The expanded model includes records of nourishment and scraping, designed to quantify the improved accuracy when anthropogenic activity is represented. Modification was included as frequency of occurrence divided by the time since the most recent event, to distinguish between recent and historic events.

All but one model reported improved predictive accuracy from the basic to expanded form. The addition of nourishment and scraping parameters resulted in a maximum reduction in predictive error of 36%. The seven improved models reported an average 23% reduction in error. These results indicate that it is advantageous to incorporate the human forcing into a coastal hazards probability model framework.