Sea-Level Rise Hazards and Decision Support
Science Center Objects
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 framework to explore the future likelihood of a variety of impacts and outcomes. Scenario-based products and tools can be applied to inform adaptation strategies, evaluate tradeoffs, and examine mitigation options.
Although the general nature of the changes that can occur on ocean coasts in response to sea-level rise (SLR) is widely recognized, it is difficult to predict exactly what changes may occur, or when they may occur. The ability to predict the extent of these changes is limited by uncertainties in both currently available data that describe the coastal environment, as well as gaps in understanding of some of the driving processes that contribute to coastal change (e.g., rate and magnitude of sea level rise, changes in storminess). Additionally, the cumulative impacts of physical and biological change on the quantity and quality of coastal habitats are not well understood, and potential societal responses to SLR are uncertain. Nonetheless, coastal managers need actionable information to make decisions that account for future hazards, including SLR.
This project brings together scientists from the disciplines of geology, hydrology, geography, biology, and ecology to synthesize information on coastal environments to address the effects of SLR on our Nation’s coasts. The approach uses a probabilistic framework, which allows researchers to incorporate observations and account for uncertainties, to evaluate the likelihood of a variety of SLR impacts, including:
- land loss from inundation and erosion,
- migration of coastal landforms,
- changes to groundwater systems, and
- changes to coastal habitat.
Decision makers depend on the future coastal environment having certain characteristics. For example, homeowners desire a home that is at low risk of loss due to coastal erosion. Local planners and managers also need to be able to identify infrastructure that could be at risk to make effective long-term adaptation or mitigation decisions. Land managers may target parcels for acquisition that provide critical habitat for threatened and endangered species. Flora and fauna require specific habitat attributes to survive and flourish. To proactively plan for an uncertain future, decision makers need the ability to consider alternative response measures and assess the benefits and costs of options. Consequently, there is a need to develop decision frameworks that combine detailed and sometimes complicated scientific information in a way that improves the ability to translate it into decision making scenarios.
Conceptual diagram demonstrating how Bayesian networks used in this project incorporate data and knowledge to provide predictions with decision-support applications. Learn more
(Credit: Erika Lentz, Woods Hole Coastal and Marine Science Center. Public domain.)
Probabilistic Framing
The Bayesian statistical framework is ideal for using data sets derived from historical or modern observations such as long-term shoreline change or wetland accretion/elevation trends. This information can be combined with model simulations and used to define the relationships between key variables in coastal environments. A Bayesian network provides a means of integrating these data to evaluate competing hypotheses regarding the relationships between forcing factors (e.g., rate of SLR, suspended sediment concentration, elevation change) and responses (e.g., shoreline change, wetland vertical accretion, water table change). This framework allows scientists to make probabilistic predictions of the future state of coastal environments for outcomes such as shoreline change, wetland survival, and changes in the depth to groundwater. The predictions also have estimates of outcome uncertainty that can be expressed as both numbers (e.g., 90%) and words (e.g., very likely). The ability to communicate SLR impacts in terms of a probabilistic prediction can improve scientists’ ability to support decision making and evaluate specific management questions about alternatives for addressing SLR.
Below are other science projects associated with this project.
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Date published: July 16, 2019Status: Active
Probabilistic Framing
The Bayesian statistical framework is ideal for using data sets derived from historical or modern observations such as long-term shoreline change or wetland accretion/elevation trends. This information can be combined with model simulations and used to define the relationships between key variables in coastal environments.
Contacts: Erika Lentz, Ph.D. -
Date published: February 19, 2019Status: Active
Sea Level Change
An interactive guide to global and regional sea level rise scenarios for the United States.
Contacts: Erika Lentz, Ph.D. -
Date published: February 1, 2019Status: Active
Estuarine Processes, Hazards, and Ecosystems
Estuarine processes, hazards, and ecosystems describes several interdisciplinary projects that aim to quantify and understand estuarine processes through observations and numerical modeling. Both the spatial and temporal scales of these mechanisms are important, and therefore require modern instrumentation and state-of-the-art hydrodynamic models. These projects are led from the U.S....
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Date published: December 30, 2018Status: Active
Coastal Landscape Response to Sea-Level Rise Assessment for the Northeastern United States
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...
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Date published: August 29, 2018Status: Active
Beach-dependent Shorebirds
Policy-makers, individuals from government agencies, and natural resource managers are under increasing pressure to manage changing coastal areas to meet social, economic, and natural resource demands, particularly under a regime of sea-level rise. Scientific knowledge of coastal processes and habitat-use can support decision-makers as they balance these often-conflicting human and ecological...
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Date published: January 18, 2018Status: Active
National Assessment of Coastal Vulnerability to Sea Level Rise
The original national coastal vulnerability index (CVI) assessment was motivated by expected accelerated sea-level rise (SLR) and the uncertainty in the response of the coastline to SLR. This research was conducted between 1999 and 2001, and is currently being updated using new data sources and methodology. This original study was part of the ...
Contacts: Erika Lentz, Ph.D.Attribution: Natural Hazards, Coastal and Marine Hazards and Resources Program, Region 11: Alaska, Region 6: Arkansas-Rio Grande-Texas-Gulf, Region 9: Columbia-Pacific Northwest, Region 2: South Atlantic-Gulf (Includes Puerto Rico and the U.S. Virgin Islands), Region 4: Mississippi Basin, Region 1: North Atlantic-Appalachian, St. Petersburg Coastal and Marine Science Center, Woods Hole Coastal and Marine Science Center -
Date published: October 1, 2017Status: Active
Empowering decision-makers: A dynamic web interface for running Bayesian networks
U.S. Geological Survey (USGS) scientists are at the forefront of research that is critical for decision-making, particularly through the development of models (Bayesian networks, or BNs) that forecast coastal change. The utility of these tools outside the scientific community has been limited because they rely on expensive, technical software and a moderate understanding of statistical...
Attribution: Community for Data Integration (CDI) -
Date published: November 15, 2016Status: Archived
Relative Coastal Vulnerability Assessment of National Park Units to Sea-Level Rise
The National Park Service (NPS) is responsible for managing nearly 12,000 km (7,500 miles) of shoreline along oceans and lakes. In 2001 the U.S. Geological Survey (USGS), in partnership with the NPS Geologic Resources Division, began conducting hazard assessments of future sea-level change by creating maps to assist NPS in managing its valuable resources. This website contains results of the...
Contacts: Erika Lentz, Ph.D., Elizabeth Pendleton
Below are publications associated with this project.
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Year Published: 2021
Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast
ContextCoastal landscapes evolve in response to sea-level rise (SLR) through a variety of geologic processes and ecological feedbacks. When the SLR rate surpasses the rate at which these processes build elevation and drive lateral migration, inundation is likely.ObjectivesTo examine the role of land cover diversity and composition in landscape...
Lentz, Erika E.; Zeigler, Sara L.; Thieler, E. Robert; Plant, Nathaniel G.
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...
Lentz, Erika E.; Plant, Nathaniel G.; Thieler, E. RobertSmartphone technologies and Bayesian networks to assess shorebird habitat selection
Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods...
Zeigler, Sara L.; Thieler, E. Robert; Gutierrez, Benjamin T.; Plant, Nathaniel G.; Hines, Megan K.; Fraser, James D.; Catlin, Daniel H.; Karpanty, Sarah M.Global and regional sea level rise scenarios for the United States
The Sea Level Rise and Coastal Flood Hazard Scenarios and Tools Interagency Task Force, jointly convened by the U.S. Global Change Research Program (USGCRP) and the National Ocean Council (NOC), began its work in August 2015. The Task Force has focused its efforts on three primary tasks: 1) updating scenarios of global mean sea level (GMSL) rise,...
Sweet, W.; Kopp, R.E.; Weaver, C.P.; Obeysekera, J; Horton, Radley M.; Thieler, E. Robert; Zervas, C.Smartphone-based distributed data collection enables rapid assessment of shorebird habitat suitability
Understanding and managing dynamic coastal landscapes for beach-dependent species requires biological and geological data across the range of relevant environments and habitats. It is difficult to acquire such information; data often have limited focus due to resource constraints, are collected by non-specialists, or lack observational uniformity...
Thieler, E. Robert; Zeigler, Sara L.; Winslow, Luke; Hines, Megan K.; Read, Jordan S.; Walker, Jordan I.Evaluation 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...
Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.Coupling centennial-scale shoreline change to sea-level rise and coastal morphology in the Gulf of Mexico using a Bayesian network
Predictions of coastal evolution driven by episodic and persistent processes associated with storms and relative sea-level rise (SLR) are required to test our understanding, evaluate our predictive capability, and to provide guidance for coastal management decisions. Previous work demonstrated that the spatial variability of long-term shoreline...
Plant, Nathaniel G.Using a Bayesian network to predict barrier island geomorphologic characteristics
Quantifying geomorphic variability of coastal environments is important for understanding and describing the vulnerability of coastal topography, infrastructure, and ecosystems to future storms and sea level rise. Here we use a Bayesian network (BN) to test the importance of multiple interactions between barrier island geomorphic variables. This...
Gutierrez, Benjamin T.; Plant, Nathaniel G.; Thieler, E. Robert; Turecek, AaronEvaluating 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...
Lentz, Erika E.; Stippa, Sawyer R.; Thieler, E. Robert; Plant, Nathaniel G.; Gesch, Dean B.; Horton, Radley M.Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States
Sea-level rise is an ongoing phenomenon that is expected to continue and is projected to have a wide range of effects on coastal environments and infrastructure during the 21st century and beyond. Consequently, there is a need to assemble relevant datasets and to develop modeling or other analytical approaches to evaluate the likelihood of...
Gutierrez, Benjamin T.; Plant, Nathaniel G.; Pendleton, Elizabeth A.; Thieler, E. RobertA Bayesian network approach to predicting nest presence of thefederally-threatened piping plover (Charadrius melodus) using barrier island features
Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to...
Gieder, Katherina D.; Karpanty, Sarah M.; Fraser, James D.; Catlin, Daniel H.; Gutierrez, Benjamin T.; Plant, Nathaniel G.; Turecek, Aaron M.; Thieler, E. RobertEffects of sea-level rise on barrier island groundwater system dynamics: ecohydrological implications
We used a numerical model to investigate how a barrier island groundwater system responds to increases of up to 60 cm in sea level. We found that a sea-level rise of 20 cm leads to substantial changes in the depth of the water table and the extent and depth of saltwater intrusion, which are key determinants in the establishment, distribution and...
Masterson, John P.; Fienen, Michael N.; Thieler, E. Robert; Gesch, Dean B.; Gutierrez, Benjamin T.; Plant, Nathaniel G.Bridging groundwater models and decision support with a Bayesian network
Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-...
Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. RobertBelow are data or web applications associated with this project.
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Date published: July 16, 2019
Sea Level Change
An Interactive Guide to Global and Regional Sea Level Rise Scenarios for the United States
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Date published: July 11, 2019
Barrier island geomorphology and shorebird habitat metrics: Four sites in New York, New Jersey, and Virginia, 2010–2014
This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology.These datasets and models are being developed for sites along the northeastern coast of the United States.
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Date published: August 3, 2018
Table and accompanying photographs for biogeomorphic classification of shorebird nesting sites on the U.S. Atlantic coast from March to September, 2016
Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution and...
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Date published: March 27, 2018
Biogeomorphic classification and images of shorebird nesting sites on the U.S. Atlantic coast
Atlantic coast piping plover (Charadrius melodus) nest sites are typically found on low-lying beach and dune systems, which respond rapidly to coastal processes like sediment overwash, inlet formation, and island migration that are sensitive to climate-related changes in storminess and the rate of sea-level rise. Data were obtained to understand piping plover habitat distribution.
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Date published: August 24, 2017
Coastal Change Hazards Portal
Interactive access to coastal change science and data for our Nation’s coasts. Information and products are organized within three coastal change hazard themes: 1) extreme storms, 2) shoreline change, and 3) sea-level rise. Displays probabilities of coastal erosion.
Below are map products associated with this project.
Sea Level Change: An Interactive Guide to Global and Regional Sea Level Rise Scenarios for the United States
In collaboration with USGS researchers, The Sea Level Rise and Coastal Flood Hazard Scenarios and Tools Interagency Task Force convened by the U.S. Ocean Policy Committee and the U.S. Global Change Research Program has developed two products that provides users with information and a tool to visualize, interact with, and explore 2017 sea-level rise scenarios.
Below are software products associated with this project.
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Date published: August 13, 2018
bi-transect-extractor
This package is used to calculate coastal geomorphology variables along shore-normal transects. The calculated variables are used as inputs for modeling geomorphology using a Bayesian Network (BN).
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Date published: June 25, 2018
iPlover
iPlover was developed by the U.S. Geological Survey Woods Hole Coastal and Marine Science Center and the USGS Center for Integrated Data Analytics. It is used by trained and vetted personnel to record information about habitats on coastal beaches and he environment surrounding them.
Below are multimedia items associated with this project.
Fire Island, New York shoreline
Fire Island, NY sand dunes with protective sand fencing
Shorebirds on the shoreline on a Fire Island, NY beach
Shorebirds on the shoreline on a Fire Island, NY beach
Ocean side homes on Fire Island, New York
Ocean side homes on Fire Island, New York
Below are news stories associated with this project.
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Date published: May 29, 2019
Challenges of predicting coastal impacts of sea level rise (SLR) in northeastern United States
The impacts of future sea level rise (SLR) are challenging to predict because they are not the same everywhere. Coastal environments and the amount of development vary—from marshes, beaches, and rocky headlands to cities, towns and beach communities—and so does how the coast responds to SLR.
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Date published: March 4, 2019
USGS contributes to the Fourth National Climate Assessment
USGS Research Hydrologist Glenn Hodgkins co-authored the Fourth National Climate Assessment’s Northeast chapter. USGS Research Geologist Erika Lentz was also a co-author. The recently published chapter discusses historical and potential future impacts of climatic changes on New England’s people and natural resources, including it’s inland and coastal waters.
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Date published: February 7, 2019
New Products Provide an Interactive Guide to Global and Regional Sea Level Rise Scenarios for the United States
A geo-narrative and accompanying data viewer provide users a new way to visualize 2017 sea-level rise scenarios originally generated for the National Climate Assessment (NCA).
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Date published: March 14, 2016
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.
Attribution: Land Resources, Climate Adaptation Science Centers -
Date published: May 4, 2015
Shorebird Science? iPlover is the App for That
RESTON, Va.-- The latest tool designed to help manage the threatened piping plover is only a download away; iPlover is the first smartphone data collection application developed by the U.S. Geological Survey and will help those managing plover populations.
Attribution: Ecosystems
Below are partners associated with this project.