Projections of coastal flood hazards and flood potential for North Carolina and South Carolina
Projected impacts by compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for North Carolina and South Carolina. Accompanying uncertainty for each SLR and storm scenario, indicating total uncertainty from model processes and contributing datasets, are illustrated in maximum and minimum flood potential. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the ... |
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Projections of coastal water depths for North Carolina and South Carolina
Projected water depths from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for North Carolina and South Carolina. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corp of Engineers. The resulting data are depths of projected flood hazards along the ... |
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Projections of coastal flood depths for the U.S. Atlantic coast
Projected depths from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for the U.S. Atlantic coast for three states (Florida, Georgia, and Virginia). Projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corp of Engineers. The resulting data are depths of projected flood hazards along the U.S. Atlantic ... |
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Projections of coastal flood hazards and flood potential for the U.S. Atlantic coast
Projected impacts by compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for the U.S. Atlantic coast for three states (Florida, Georgia, and southern Virginia). Accompanying uncertainty for each SLR and storm scenario, indicating total uncertainty from model processes and contributing datasets, are illustrated in maximum and minimum flood potential. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output ... |
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Projected groundwater emergence and shoaling along the North and South Carolina coasts
Groundwater emergence and shoaling extents are derived from water table depth GeoTIFFs, which are calculated as steady-state groundwater model heads subtracted from high-resolution topographic digital elevation model (DEM) land surface elevations. Results are provided as shapefiles of water table depth in specific depth ranges. |
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Projected groundwater head along the North and South Carolina coasts
Seamless unconfined groundwater heads for U.S. coastal North and South Carolina groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for both current and future sea ... |
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Projected water table depths along the North and South Carolina coasts
To predict water table depths, seamless groundwater heads for unconfined coastal North and South Carolina groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of groundwater heads for ... |
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Projected groundwater emergence and shoaling along the Virginia, Georgia, and Florida coasts
Groundwater emergence and shoaling extents are derived from water table depth GeoTIFFs, which are calculated as steady-state groundwater model heads subtracted from high-resolution topographic digital elevation model (DEM) land surface elevations. Results are provided as shapefiles of water table depth in specific depth ranges. Similar modeled data for North Carolina and South Carolina are available from Barnard and others, 2023 at https://doi.org/10.5066/P9W91314. |
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Projected groundwater head along the Virginia, Georgia, and Florida coasts
Seamless unconfined groundwater heads for U.S. coastal Virginia, Georgia, and Florida (Atlantic and Gulf coast south of Sarasota) groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic scales (100s of kilometers) of ... |
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Projected water table depths along the Virginia, Georgia, and Florida coasts
To predict water table depths, seamless groundwater heads for unconfined coastal Virginia, Georgia, and Florida (Atlantic and Gulf coast south of Sarasota) groundwater systems were modeled with homogeneous, steady-state MODFLOW simulations. The geographic extent examined was limited primarily to low-elevation (land surface less than approximately 10 m above mean sea level) areas. Steady-state MODFLOW groundwater flow models were used to obtain detailed (50-meter-scale) predictions over large geographic ... |
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Vertical land motion rates for the years 2007 to 2020 for the North and South Carolina coasts
Rates of land subsidence and uplift for the North and South Carolina coasts are derived from Sentinel-1A/B (2015-2020) and ALOS (2007-2011) synthetic aperture radar (SAR) satellites, at approximately 50-75 m resolution and mm-level precision. The data consist of vertical land motion (VLM) rates and the 1-sigma error in land motion rates and are available as csv files. |
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Vertical land motion rates for the years 2007 to 2020 for the U.S. Atlantic coast
This dataset contains rates of land subsidence and uplift derived from Sentinel-1A/B (2015-2020) and ALOS (2007-2011) synthetic aperture radar (SAR) satellites, at approximately 50-75 m resolution and mm-level precision for the U.S. Atlantic coast except for the states of North and South Carolina. The data consist of vertical land motion (VLM) rates and the 1-sigma error in land motion rates and are available as csv files. Similar vertical land motion rates for North Carolina and South Carolina are ... |
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Nearshore parametric wave setup future projections (2020-2050) for the North and South Carolina coasts
This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at ... |
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Nearshore parametric wave setup hindcast data (1979-2019) for the North and South Carolina coasts
This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at ... |
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Nearshore water level, tide, and non-tidal residual future projections (2016-2050) for the North and South Carolina coasts
A dataset of modeled nearshore water levels (WLs) was developed for the North and South Carolina coastlines. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields. Water level outputs were extracted from the global grid at approximately 20 km resolution along the southeast Atlantic coastline. These data were then statistically downscaled using a ... |
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Nearshore water level, tide, and non-tidal residual hindcasts (1979-2016) for the North and South Carolina coasts
A dataset of modeled nearshore water levels (WLs) was developed for the North and South Carolina coastlines. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields -. Water level outputs were extracted from the global grid at approximately 20 km resolution along the coastlines. These data were then statistically downscaled using a signal-specific ... |
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Projections of shoreline change of current and future (2005-2100) sea-level rise scenarios for North Carolina and South Carolina
This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps). Projections were made using the Coastal Storm Modeling System - Coastal One-line ... |
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Satellite-derived shorelines for North Carolina and South Carolina (1984-2021)
This dataset contains shoreline positions derived from available Landsat satellite imagery for North Carolina and South Carolina for the time period of 1984 to 2021. Positions were determined using CoastSat (Vos and others, 2019a and 2019b), an open-source mapping toolbox, was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. To understand shoreline evolution in complex environments and operate long-term simulations illustrating potential shoreline positions in the next ... |
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Nearshore parametric wave setup future projections (2020-2050) for the U.S. Atlantic coast
This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to ... |
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Nearshore water level, tide, and non-tidal residual future projections (2016-2050) for the U.S. Atlantic coast
A dataset of modeled nearshore water levels (WLs) was developed for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields. Water level outputs were extracted from the global grid at approximately 20 km resolution along the Atlantic coastline. These data were then ... |
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Nearshore water level, tide, and non-tidal residual hindcasts (1979-2016) for the U.S. Atlantic coast
A dataset of modeled nearshore water levels (WLs) was developed for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Water levels, defined for this dataset as the linear sum of tides and non-tidal residuals (NTR), were produced by Muis and others (2016) using a global tide and surge model (GTSM) forced by global atmospheric fields -. Water level outputs were extracted from the global grid at approximately 20 km resolution along the coastlines. These data were then statistically ... |
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Projections of shoreline change of current and future (2005-2100) sea-level rise scenarios for the U.S. Atlantic Coast
This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps).Projections were made using the Coastal Storm Modeling System - Coastal One-line ... |
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Satellite-derived shorelines for the U.S. Atlantic coast (1984-2021)
This dataset contains shoreline positions derived from available Landsat satellite imagery for five states (Delaware, Maryland, Viginia, Georgia, and Florida) along the U.S. Atlantic coast for the time period 1984 to 2021. An open-source toolbox, CoastSat (Vos and others, 2019a and 2019b), was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. Resulting shorelines are presented in KMZ format. Significant uncertainty is associated with the locations of shorelines in ... |
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Nearshore parametric wave setup hindcast data (1979-2019) for the U.S. Atlantic coast
This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to ... |
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