Nationally, ~40% of the US population lives in coastal counties. Coastal bluff retreat impacts property owners across seven Great Lakes states, and across at least ten states on the Atlantic and Pacific coasts. Bluff retreat is also a major coastal hazard affecting over $66 million of near-bluff property along all nine municipalities in Erie County, Pennsylvania’s only coastal county on the Great Lakes.
Objective 1 of this proposal is to develop a multivariate Bayesian network model of bluff retreat for the western Erie County littoral cell (WECLC). The model will provide a flexible predictive tool for explaining recent-historical bluff retreat and for estimating future retreat magnitudes and patterns. Objective 2 is to generate a GIS/LiDAR-derived estimate of bluff-sourced total (clay-gravel) and littoral (sand, gravel) sediment input to the WECLC that impacts coastal water quality (turbidity, nutrients) and represents the principal input to the WECLC and to the Presque Isle littoral cell immediately downdrift. The latter hosts Presque Isle State Park, the state’s largest coastal naturalresource attraction.
The project area comprises ~35 km of coastline dominated by unconsolidated glacial-till-rich bluffs with relief of 1.5-40 m. Six to eight field sites will be selected for Bayesian modeling of bluff retreat, and will connect WECLC-wide GIS/LiDAR mapping to quantify post-1998 bluff contributions to the littoral sediment budget. The latter effort will also reveal chronic erosion hotspots and stable sectors important to future hazard management. The project will allow improved explanations and forecasting of bluff change and erosion hazards for coastal managers by integrating interactions between multiple variables to provide new statistical forecasts. Dissemination of results will enhance scientific understanding of bluff processes, while the project will also foster participation of undergraduate STEM and non-STEM majors in research and outreach at a regional PUI college. Outreach will increase hazard-consciousness among the regional coastal populace.