Skip to main content
Advanced Search

Filters: Tags: sea level rise (X)

339 results (177ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
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...
thumbnail
The points depicted are attributed the highest estimated 100-year tide elevation for locations surrounding the San Francisco Bay.
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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.
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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...
thumbnail
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, All tags...
thumbnail
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, All tags...
thumbnail
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, All tags...
thumbnail
The Yukon-Kuskokwim Delta of Alaska is a globally important region for numerousavian species including millions of migrating and nesting waterbirds. Climate change effectssuch as sea level rise and increased storm frequency and intensity have the potential to impactwaterbird populations and breeding habitat. In order to determine the potential impacts of theseclimate-mediated changes, we investigated both short-term and long-term impacts of stormsurges to geese and eider species that commonly breed on the Yukon-Kuskokwim Delta. Todetermine short-term impacts, we compared nest densities of geese and eiders in relation to themagnitude of storms that occurred in the prior fall from 2000–2013. Additionally, we modeledgeese...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: BIRDS, BIRDS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, DELTAS, All tags...
thumbnail
This project evaluated the potential impacts of storm surges and relative sea level rise on nesting geese and eider species that commonly breed on the Yukon-Kuskokwim Delta (Y-K Delta). Habitat suitability maps for breeding waterbirds were developed to identify current waterbird breeding habitat and distributions. Short-term climate change impacts were assessed by comparing nest densities in relation to magnitude of storms that occurred in the prior fall from 2000-2013. Additionally, nest densities were modeled using random forests in relation to the time-integrated flood index (e.g., a storm specific measure accounting for both water depth and duration of flooding) for four modeled storms (2005, 2006, 2009, and...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: BIRDS, BIRDS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, CLIMATE CHANGE IMPACT ASSESSMENT MODELS, DELTAS, All tags...


map background search result map search result map California Sea Level Rise Coastal Erosion Mapping San Francisco High Tide Elevations, California, USA Mean Higher High Water, 2000, California, USA Pacific Northwest sea-level rise modelling - Habitat classification for site four (2075, A1B mean scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (1980) Pacific Northwest sea-level rise modelling - Habitat classification for site two (1977) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2100, 1 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2075, 2 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2050, A1B maximum scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2025, 1.5 meter rise scenario) Final Report: The Influence of Fall Storms on Nest Densities of Geese and Eiders on the Yukon-Kuskokwim Delta of Alaska Part I Summary: Predicting waterbird nest distributions points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014 Pacific Northwest sea-level rise modelling - Habitat classification for site four (2075, A1B mean scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, A1B maximum scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site four (2025, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (1980) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2050, 1 meter rise scenario) Pacific Northwest sea-level rise modelling - Habitat classification for site one (2025, 1.5 meter rise scenario) points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 Pacific Northwest sea-level rise modelling - Habitat classification for site two (1977) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2100, 1 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2075, 2 meter rise scenario, dikes removed) Pacific Northwest sea-level rise modelling - Habitat classification for site two (2050, A1B maximum scenario, dikes removed) points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014 San Francisco High Tide Elevations, California, USA Final Report: The Influence of Fall Storms on Nest Densities of Geese and Eiders on the Yukon-Kuskokwim Delta of Alaska Part I Summary: Predicting waterbird nest distributions Mean Higher High Water, 2000, California, USA California Sea Level Rise Coastal Erosion Mapping