As part of the USGS Sea-Level Rise Hazards and Decision-Support project, this assessment seeks to predict the response to sea-level rise 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 to ensure research outcomes meet decision making needs.
The effects of sea-level rise (SLR) and changes in coastal storm intensities are expected to have a broad range of impacts on natural and built environments. These effects include changes in habitat area and/or quality along sandy and/or wetland shorelines, and increased vulnerability of human infrastructure.
This project seeks to provide a geospatially explicit description of coastal landscape change and land loss in response to SLR by evaluating the likelihood of inundation as well as dynamic coastal change in different settings. Probabilistic predictions ensure that consideration of uncertainty is robust and is straightforward to integrate in decision making. This information will directly address decision-support needs elicited in a collaborative Structured Decision Making (SDM) process involving regional resource managers and researchers through the North Atlantic Landscape Conservation Cooperative (NALCC). The coastal response information can be used to inform corresponding habitat models, as well as to map out alternative management strategies to optimize conservation efforts and allocate regional resources in the future. As such, our study area encompasses the entire NALCC region which extends from Maine to Virginia.
Below are other science projects associated with this project.
Sea-Level Rise Hazards and Decision Support
Coastal Landscape- Structured Decision Making
Coastal Landscape- Change Predictions
Below are publications associated with this project.
Relationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model
Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood
Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods
Below are news stories associated with this project.
Up to 70 Percent of Northeast U.S. Coast May Adapt to Rising Seas
Much of the coast from Maine to Virginia is more likely to change than to simply drown in response to rising seas during the next 70 years or so, according to a new study led by the U.S. Geological Survey.
- Overview
As part of the USGS Sea-Level Rise Hazards and Decision-Support project, this assessment seeks to predict the response to sea-level rise 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 to ensure research outcomes meet decision making needs.
The effects of sea-level rise (SLR) and changes in coastal storm intensities are expected to have a broad range of impacts on natural and built environments. These effects include changes in habitat area and/or quality along sandy and/or wetland shorelines, and increased vulnerability of human infrastructure.
This project seeks to provide a geospatially explicit description of coastal landscape change and land loss in response to SLR by evaluating the likelihood of inundation as well as dynamic coastal change in different settings. Probabilistic predictions ensure that consideration of uncertainty is robust and is straightforward to integrate in decision making. This information will directly address decision-support needs elicited in a collaborative Structured Decision Making (SDM) process involving regional resource managers and researchers through the North Atlantic Landscape Conservation Cooperative (NALCC). The coastal response information can be used to inform corresponding habitat models, as well as to map out alternative management strategies to optimize conservation efforts and allocate regional resources in the future. As such, our study area encompasses the entire NALCC region which extends from Maine to Virginia.
Coastal area within the North Atlantic Landscape Conservation Cooperative region for which predictions have been generated. - Science
Below are other science projects associated with this project.
Sea-Level Rise Hazards and Decision Support
The Sea-Level Rise Hazards and Decision-Support project assesses present and future coastal vulnerability to provide actionable information for management of our Nation’s coasts. Through multidisciplinary research and collaborative partnerships with decision-makers, physical, biological, and social factors that describe landscape and habitat changes are incorporated in a probabilistic modeling...Coastal Landscape- Structured Decision Making
An effort to better understand the effects that sea-level rise (SLR) is likely to have on the coastal zone has brought together a network of Department of Interior collaborators and academic partners through the DOI North Atlantic Landscape Conservation Cooperative (NALCC) and Northeast Climate Science Center. The USGS Sea-Level Rise Hazards and Decision-Support project is developing decision...Coastal Landscape- Change Predictions
Sea-level rise (SLR) impacts on the coastal landscape are presented here as: 1) level of landscape submergence (adjusted land elevation with respect to projected mean high water levels); and 2) coastal response type characterized as either static (for example, inundation) or dynamic (for example, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades... - Publications
Below are publications associated with this project.
Relationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model
Understanding land loss or resilience in response to sea-level rise (SLR) requires spatially extensive and continuous datasets to capture landscape variability. We investigate sensitivity and skill of a model that predicts dynamic response likelihood to SLR across the northeastern U.S. by exploring several data inputs and outcomes. Using elevation and land cover datasets, we determine where datAuthorsErika Lentz, Nathaniel G. Plant, E. Robert ThielerEvaluation of dynamic coastal response to sea-level rise modifies inundation likelihood
Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolutionAuthorsErika E. Lentz, E. Robert Thieler, Nathaniel G. Plant, Sawyer R. Stippa, Radley M. Horton, Dean B. GeschEvaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods
The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, inclAuthorsErika E. Lentz, Sawyer R. Stippa, E. Robert Thieler, Nathaniel G. Plant, Dean B. Gesch, Radley M. Horton - News
Below are news stories associated with this project.
Up to 70 Percent of Northeast U.S. Coast May Adapt to Rising Seas
Much of the coast from Maine to Virginia is more likely to change than to simply drown in response to rising seas during the next 70 years or so, according to a new study led by the U.S. Geological Survey.