Development and Application of a Long-term Shoreline Change Model for Assessing Climate Change Impacts

Reliable, quantitative predictions of shoreline evolution are increasingly sought for adaptation planning. 2-D and 3-D models of coupled hydrodynamics, waves, sediment transport, and morphology are increasingly capable of simulating small-scale, short-term beach change (e.g. beach response to storm events on time scales of days to weeks). However, simulations of large-scale (i.e. 100 m to 100 km length scale), long-term (i.e. 10-100 year time scale) shoreline change require a different modeling paradigm. We present the development and application of a one-line model to predict shoreline change on over 400 km of coastline in Southern California at the end of the 21^st century. The model, synthesized from process-based models in the literature, explicitly accounts for longshore and cross-shore sediment transport due to waves and sea-level rise. Natural and anthropogenic sediment supply is treated implicitly and their combined magnitude is estimated via data assimilation with historical shoreline data. The extended Kalman filter data assimilation method also automatically adjusts the model parameters to best account for the observed behavior. Simulations of shoreline evolution from 1995 to 2100 with 1.0 m of projected sea-level rise indicate that approximately 20-27% of beaches in Southern California may be completely eroded into existing infrastructure.