The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the coastal zone vertically from -12 meters (m) to 10 m above mean high water (MHW). Results are produced at a horizontal resolution of 30 meters for four decades (the 2020s, 2030s, 2050s and 2080s). Adjusted elevations and their respective probabilities are generated using regional geospatial datasets of current sea-level forecasts, vertical land movement rates, and current elevation data. Coastal response type predictions incorporate adjusted elevation predictions with land cover data and expert knowledge to determine the likelihood that an area will be able to accommodate or adapt to water level increases and maintain its initial land class state or transition to a new non-submerged state (dynamic) or become submerged (static). Intended users of these data include scientific researchers, coastal planners, and natural resource management communities.
30 meter Esri binary grids of predicted elevation with respect to projected sea levels for the Northeastern U.S. from Maine to Virginia for the 2020s, 2030s, 2050s and 2080s (Albers, NAD 83)