Filters: Tags: Sea level rise (X)
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This dataset includes: The locations of EPA listed sites that are vulnerable to a 100-year coastal flood with a 1.4 meter sea-level rise. Extents of dune and bluff erosion given a 1.4 meter (approx. 55") sea-level rise for the entire California coast. Extent of a 100-year coastal flood, based on FEMA 100-year flood elevations, with a sea-level rise of 1.4 meters (55 inches) (year 2100). Extent of inundation due to Mean Higher High Water (MHHW), after a 1.4 meter sea-level rise (scenario for year 2100), for the California coast (excluding the San Francisco Bay). The current inundation due to MHHW was based on NOAA tide stations elevation data (mhhw_2000 raster), to which 140 centimeters were added to the Z-value...
The points depicted are attributed the highest estimated 100-year tide elevation for locations surrounding the San Francisco Bay.
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
The polygon represents the extent of inundation due to Mean Higher High Water (MHHW) under current conditions (year 2000) based on NOAA tide stations tide elevation data.
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
In order to predict the impacts of climate change induced sea-level rise on Pacific Northwest coastal habitats, the Sea Level Affecting Marshes Model (SLAMM) was utilized to simulate future coastal habitat configurations under various sea-level rise scenarios. The model was run for 2025, 2050, 2075, and 2100. Historical or "initial condition" habitat classifications are also available for some sites. The sea-level rise scenarios include: 1. A1B greenhouse gas emission mean : 0.39 meter rise by 2100 2. A1B greenhouse gas emission maximum : 0.69 meter rise by 2100 3. 1 meter rise by 2100 4. 1.5 meter rise by 2100 5. 2 meter rise by 2100 Due to differing site conditions, local sea-level rise varies slightly from...
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
Bayesian Network,
CMHRP,
Cape Cod,
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
Bayesian Network,
CMHRP,
Coastal Erosion,
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Raster,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
Bayesian Network,
CMGP,
Coastal Erosion,
Some of California’s most cherished coastal wetlands, where endangered birds chatter and green growth thrives, could turn to mudflats by the middle of the century. By the end of the century, they could be gone. New research based on years of observation says rising sea levels might well outpace the ability of coastal wetlands to adapt, inundating them before they have time to colonize higher elevations. Continue Reading >>
These three PDFs contain qualitative notes taken during focus group-style interviews in 2017 with coastal resource managers Grand Bay, AL; Port Aransas, TX; and Tampa Bay, FL about their data needs related to tidal wetlands and sea level rise and interest in working with USGS researchers to receive that data. The coastal managers were all engaged in conversations with USGS scientists as part of a separate project entitled Landscape conservation design for enhancing the adaptive capacity of coastal wetlands in the face of sea-level rise and coastal development, regarding tidal wetlands in the Gulf Coast region and the ability of investigators leading that project to provide data suitable for use in various resource...
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