EMPIRICAL PROJECTION OF FUTURE EROSION HAZARD DUE TO SEA LEVEL RISE USING A HYBRID GEOMETRIC MODEL

Chronic erosion dominates sandy beaches of Hawaii causing loss and narrowing, and damaging homes, infrastructure, and critical habitat. Increased rates of future sea level rise (SLR) will likely exacerbate these problems. Shoreline managers and other stakeholders are in need of guidance to support long-range planning and adaptation efforts. Despite recent advances in numerical models, there remains a need for simple methods of estimating land areas that are threatened by erosion on decadal to century time scales due to SLR. While not as detailed as numerical models, an empirical approach can provide a first-order approximation to shoreline change that is useful for coastal management and planning. In many locations, managers work with historical data to provide information on coastal erosion, but because of projected future increases in the rate of SLR, historical data likely under-predict the rate of future shoreline change. Conversely, predictions of shoreline change with SLR typically employ geometric models (e.g., Bruun 1962) that do not account for sediment availability and alongshore variability that are captured in historical data. Furthermore, these two predictions may produce conflicting results. We report here on the early results of modeling future erosion hazards by integrating historical shoreline change with a standard geometric model of shoreline equilibrium (Davidson-Arnott, 2005). This approach is especially attractive in Hawaii, where complex reef topography causes high spatial variability in sediment transport patterns and where physical models of wave transformation may fail to capture the true influence of the variable seafloor. Our hybrid historical/geometric model projects future rates and distances of shoreline change under the RCP8.5 scenario of SLR. The projected erosion hazards at various time intervals and confidence levels are plotted in a geographic information system for a diversity of shoreline management and planning purposes. We apply this model (80% probability) to 10 Hawaii beaches and report on future rates of shoreline change, distances of retreat, and where these dynamics intersect with coastal plain geology and development patterns. Our results provide a management tool in a geographic information system for use by coastal stakeholders.