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This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
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This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
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This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
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This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
Sea level rise (SLR) and disturbances from increased storm activity are expected to diminish coastal habitats available for sea turtle, seabird, shorebird, and beach mouse nesting by removing habitat as well as inundating nests during critical incubation periods. The goal of our proposed research is to evaluate past nesting patterns of fourteen coastal nesting species and predict future effects of sea level rise on nesting beaches along the South Atlantic Bight. Maps of coastal vulnerability to SLR combined with historical data sets of long-term and spatially extensive nesting habitat will lead to models that enhance our understanding of the complex environmental changes occurring from global climate change and...
Coastal wetlands provide many valuable benefits to people and wildlife, including critical habitat, improved water quality, reduced flooding impacts, and protected coastlines. However, in the 21st century, accelerated sea-level rise and coastal development are expected to greatly alter coastal landscapes across the globe. The future of coastal wetlands is uncertain, challenging coastal environmental managers to develop conservation strategies that will increase the resilience of these valuable ecosystems to change and preserve the benefits they provide. One strategy for preparing for the effects of sea-level rise is to ensure that there is space available for coastal wetlands to migrate inland. In a recent study,...
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Sea level rise caused by climate change is an ongoing phenomenon and a concern both locally and worldwide. Low-lying coastal areas are particularly at risk to flooding and inundation, affecting a large proportion of the human population concentrated in these areas as well as natural communities-particularly animal species that depend on these habitats as a key component of their life cycle. While more local, state, and federal governments have become concerned with the potential effects that predicted sea levels will have on their communities and coastal landscapes, more information is needed on the potential effects that changes in sea level will have on coastal habitats and species.
Categories: Data, Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2012, 2013, 2014, ANIMALS/VERTEBRATES, ANIMALS/VERTEBRATES, All tags...
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Tidal marshes serve a variety of important functions valued by Maine communities. Unfortunately, tidal marsh habitats are highly vulnerable to damage or loss from sea level rise. Scientists expect marsh habitats will be more frequently flooded in the future and marsh vegetation lost or significantly altered as a result. Salt marshes do, however, have the ability to ‘migrate’ landward with sea level rise-induced changes in shoreline position. The potential and ability for marsh migration is crucial to sustaining these important ecosystems and their functions for the future.Recognizing this, and with financial support from the North Atlantic Landscape Conservation Collaborative (NALCC) and other sources, a team of...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...
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This dataset is part of an extensive analysis of sea-level rise impacts on coastal habitats along the Chesapeake Bay, Delaware Bay, and the ocean beaches of southern New Jersey, Delaware, Maryland, and Virginia. The National Wildlife Federation commissioned Jonathan S. Clough of Warren Pinnacle Consulting, Inc., to apply the Sea Level Affecting Marshes Model (SLAMM, Version 5.0) to the Chesapeake Bay region. The SLAMM model is widely regarded as the premier research tool for simulating the dominant processes involved in wetland conversions and shoreline modifications during long-term sea-level rise. Our analysis looked at a range of sea-level rise scenarios from the 2001 Intergovernmental Panel on Climate Change...
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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...
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This assessment is based on review of available literature and examination of historical air photos that date to the 1940’s, topography developed from LiDAR (light detection and ranging) data obtained in 2007, limited field mapping of beach, dune and fluvial stratigraphy, discussions with other coastal dune geomorphologists, and reconnaissance site visits to the project area and environs. Radiocarbon dating drew from the work of Tushingham et al. (no date), Meyer et al. (2011), Bicknell and Austin (1991) and unpublished data developed by park staff. Optically stimulated luminescence (OSL) dating drew from work by Michaela Spiske (University of Munich, unpublished data 2013) and our resources using funding provided...
Coastal ecosystems in the Eastern U.S. have been severely altered by processes associated with human development, including drainage of wetlands, changes in hydrology, land clearing, agricultural and forestry activity, and the construction of structures that “harden” the coast. Sea-level rise and the changing frequency of extreme events associated with climate change are now further degrading the capacity of those ecological and social systems to remain resilient. As custodians of ecological goods and services valued by society, coastal National Wildlife Refuges (NWRs) have a particularly important role to play in helping socio-ecological systems adapt to global-change processes. To help refuges address this challenge,...
In the Pacific Northwest, coastal wetlands support a wealth of ecosystem services including habitat provision for wildlife and fisheries and flood protection. The tidal marshes, mudflats, and shallow bays of coastal estuaries link marine, freshwater, and terrestrial habitats and provide economic and recreational benefits to local communities. Climate change effects such as sea-level rise are currently altering these habitats, but we know little about how these areas will change over the next 50-100 years. Our study examined the effects of sea-level rise on nine tidal marshes in Washington and Oregon, with the goal of providing scientific data to support future coastal planning and conservation. We compiled physical...
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The goal of this project is to provide a preliminary overview, at a National scale, the relative susceptibility of the Nation's coast to sea- level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of regions where physical changes are likely to occur due to sea-level rise.
In the next 100 years, accelerated sea-level rise (SLR) and urbanization will greatly modify coastal landscapes across the globe (Millennium Ecosystem Assessment, 2005; Stocker and others, 2013). More than one-half of coastal wetlands in the contiguous United States are located along the Gulf of Mexico coast (Field and others, 1991). In addition to supporting fish and wildlife habitat, these highly productive wetlands support many ecosystem goods and services including storm protection, recreation, clean water, and carbon sequestration (Barbier and others, 2011; Engle, 2011). Historically, tidal saline wetlands (TSWs) have adapted to sea-level fluctuations through lateral and vertical movement on the landscape....


map background search result map search result map Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (2 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (A1B mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (1 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (B1 mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2025 (A1B maximum scenario) Employing the Conservation Design Approach on Sea-Level Rise Impacts on Coastal Avian Habitats along the Central Texas Coast Tidal Range Data for the Gulf of Mexico Probability 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) Age Estimation for Landforms at Tolowa Dunes State Park - Report Integrating Science into Policy: Local Adaptation for Marsh Migration CoSMoS v3.1 wave-hazard projections: 20-year storm in San Luis Obispo County CoSMoS v3.1 ocean-currents hazards: 20-year storm in San Luis Obispo County CoSMoS v3.1 wave-hazard projections: 20-year storm in San Mateo County CoSMoS v3.1 water level projections: 20-year storm in San Mateo County CoSMoS v3.1 water level projections: average conditions in San Mateo County CoSMoS v3.1 water level projections: 20-year storm in San Mateo County CoSMoS v3.1 water level projections: average conditions in San Mateo County CoSMoS v3.1 wave-hazard projections: 20-year storm in San Mateo County Age Estimation for Landforms at Tolowa Dunes State Park - Report CoSMoS v3.1 wave-hazard projections: 20-year storm in San Luis Obispo County CoSMoS v3.1 ocean-currents hazards: 20-year storm in San Luis Obispo County Employing the Conservation Design Approach on Sea-Level Rise Impacts on Coastal Avian Habitats along the Central Texas Coast Integrating Science into Policy: Local Adaptation for Marsh Migration Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (2 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2100 (A1B mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (1 meter rise scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2075 (B1 mean scenario) Chesapeake Bay region sea-level rise modelling - Habitat classification, 2025 (A1B maximum scenario) Tidal Range Data for the Gulf of Mexico Probability 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)