Evaluating the Coastal Landscape Response to Sea-Level Rise
Wednesday, March 4, 2015
For a project partly funded by the NE CSC, a USGS and Columbia University team recently completed their study evaluating the effects of sea-level rise on the northeastern U.S. The project produced an approach and methodology to distinguish coastal areas in the northeastern U.S. (Virginia-Maine) likely to inundate (e.g., flooding) in response to sea-level rise from those likely to respond dynamically by moving or changing (e.g., landforms such as barrier islands and marshes). The coastal response model, developed using a Bayesian network, integrates relative sea-level-rise scenarios with elevation and land-cover data to evaluate the probability of observing dynamic coastal response; areas less likely to dynamically respond are conversely more likely to inundate (e.g. rocky or hard shorelines). Results are presented as spatially explicit predictions at 30 m resolution for the 2020s, 2030s, 2050s, and 2080s. Distinguishing the likely coastal response to a variety of sea level projections can be used in conjunction with habitat models to identify areas within the region that may be suitable for mitigation, buffering, or tradeoffs, as well as to inform scientific research and decision support efforts moving forward.
The products come out of the USGS Sea-Level Rise Hazards and Decision-Support project, which seeks to predict the sea-level rise response across the coastal landscape under a range of future scenarios by evaluating the likelihood of inundation as well as dynamic coastal change.
The research is being conducted in conjunction with resource managers and decision makers from federal and state agencies, and non-governmental organizations and utilizes a structured decision-making approach developed in collaboration with the North Atlantic Landscape Conservation Cooperative to ensure that research outcomes meet decision making needs.
Project team: Erika Lentz, E. Robert Thieler, Nathaniel G. Plant, Sawyer R. Stippa, Radley Horton, Dean Gesch
Access all materials at the USGS project page >>
Photo credit: Jane Thomas, IAN Image Library
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