Understanding and Predicting the Response of a Barrier Beach to Extreme Storms; A Case Study on the South Shore of Rhode Island

Accelerated sea level rise (SLR) is a major challenge for coastal communities in many regions of the U.S. and around the world. SLR leads to shoreline retreat and increased flood risk. Living shoreline methods include a range of shoreline stabilization techniques that are mostly made up of native and natural materials. While erosion mitigation and living shoreline projects are costly to develop and implement, they are often designed and constructed based on empirical methods and the success or failure of previous projects. Alternatively, process-based numerical methods along with in-situ data can be employed to understand the response of a beach to storms and evaluate the performance of a planned living shoreline project. However, because nearshore sediment transport processes are still poorly understood, more research in various case studies are needed to assess the capabilities and shortcomings of process-based models. Here, we employed a suite of numerical models to assess flood risk, coastal erosion, and the performance of several recommended solutions in a case study, Green Hill Pond Shoreline, on the south coast of Rhode Island, USA. This case study represents a typical coastal barrier system. A coupled wave-circulation modeling system SWAN-ADCIRC (Simulating WAves Nearshore-ADvanced CIRCulation) was applied over a regional mesh to simulate offshore sea level and wave conditions. For nearshore modeling, the coastal wave-circulation-morphodynamic model XBeach was nested within the regional model to simulate sediment transport processes and coastal erosion. The modeling system was first applied to historical storms such as Hurricane Sandy (2012), and its performance was assessed against observed data (i.e., a unique beach profile dataset, wave and water level measurements). The validated model was then used to evaluate selected remedial options, including nourishment of the beach and reconstruction of the dune system using synthetic storms. Each synthetic storm represented an even with a probability (e.g., 25-year return period). The sensitivity of model results to vegetative cover was investigated to understand its impact on the performance of the dune in protecting the pond. Several issues such as long-term (year) and short term (storm period) simulations and the impact of SLR were discussed.