Quantifying Uncertainty of Regional Shoreline Evolution Using Stochastic Wave Climate Emulator

Quantifying uncertainty of regional shoreline evolution is critical for success in risk-based coastal protection practices. Shoreline changes result from multiple interactive coastal processes such as subaqueous sediment transport processes driven by nearshore waves, currents, and sea level change. By considering those driving forces as stochastic variables, probabilistic shoreline modeling would be able to predict variations of seasonal and interannual shoreline positions over a project-scale coast. Meanwhile, for assessing performance of coastal protection measures, it is also important to simulate effects of structural (e.g., groins, breakwaters, seawall) and beach nourishment on sediment transport and beach changes. This paper presents a probabilistic shoreline evolution model based on GenCade Monte-Carlo simulation by using input conditions of waves and mean sea levels generated by a stochastic wave climate emulator (SWCE). This SWCE model uses pressure and temperatures on sea surface that reflect inter-annual oceanic variability and outgoing long wave radiation that reflects intra-seasonal variability to modulate the probability of weather occurring at a range of climate timescales. Therefore, by incorporating the SWCE, the GenCade Monte-Carlo shoreline simulations can predict realistic uncertainty and risks, because seasonal and annual variations of shoreline changes are simulated. The probabilistic shoreline model is validated by simulating multiple-years shoreline changes in Duck coast, NC.