Projections of coastal flood hazards and flood potential for North Carolina and South Carolina

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Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Patrick L. Barnard
Originator: Li H. Erikson
Originator: Kees Nederhoff
Originator: Kai A. Parker
Originator: Jennifer A. Thomas
Originator: Amy C. Foxgrover
Originator: Andrea C. O’Neill
Originator: Norberto C. Nadal-Caraballo
Originator: Chris Massey
Originator: Madison C. Yawn
Originator: Anita C. Engelstad
Publication_Date: 20230128
Title:
Projections of coastal flood hazards and flood potential for North Carolina and South Carolina
Geospatial_Data_Presentation_Form: vector digital data
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P9W91314
Publication_Information:
Publication_Place: Pacific Coastal and Marine Science Center, Santa Cruz, CA
Publisher: U.S. Geological Survey
Online_Linkage: https://doi.org/10.5066/P9W91314
Larger_Work_Citation:
Citation_Information:
Originator: Patrick L. Barnard
Originator: Kevin Befus
Originator: Jeffrey J. Danielson
Originator: Anita C. Engelstad
Originator: Li H. Erikson
Originator: Amy C. Foxgrover
Originator: Matthew W. Hardy
Originator: Daniel J. Hoover
Originator: Tim Leijnse
Originator: Patrick W. Limber
Originator: Chris Massey
Originator: Robert McCall
Originator: Norberto C. Nadal-Caraballo
Originator: Kees Nederhoff
Originator: Leonard Ohenhen
Originator: Andrea C. O’Neill
Originator: Kai A. Parker
Originator: Manoocher Shirzaei
Originator: Xin Su
Originator: Jennifer A. Thomas
Originator: Maarten van Ormondt
Originator: Sean F. Vitousek
Originator: Kilian D. Vos
Originator: Madison C. Yawn
Publication_Date: 2023
Title:
Future coastal hazards along the U.S. North and South Carolina coasts
Series_Information:
Series_Name: data release
Issue_Identification: DOI:10.5066/P9W91314
Publication_Information:
Publication_Place: Pacific Coastal and Marine Science Center, Santa Cruz, CA
Publisher: U.S. Geological Survey
Online_Linkage: https://doi.org/10.5066/P9W91314
Description:
Abstract:
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 (2023), 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 US Army Corp of Engineers. The resulting data products include detailed flood-hazard maps along the North Carolina and South Carolina coast due to sea level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability. In addition to sea-level rise, flood simulations run by these numerical models included dynamic contributions from tide, storm surge, wind, waves, river discharge, precipitation, and seasonal sea-level fluctuations. Outputs include impacts from combinations of SLR scenarios (0, 0.25, 0.5, 1.0, 1.5, 2.0, and 3.0 m) storm conditions including 1-year, 20-year and 100-year return interval storms and a background condition (no storm - astronomic tide and average atmospheric conditions).
Purpose:
These data are intended for policy makers, resource managers, science researchers, students, and the general public. These projections for future sea-level rise scenarios provide emergency responders and coastal planners with critical hazards information that can be used as a screening tool to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. These data can be used with geographic information systems or other software to identify and assess possible areas of vulnerability. These data are not intended to be used for navigation.
Supplemental_Information:
Work was funded by the Additional Supplemental Appropriations for Disaster Relief Act of 2019 (H.R. 2157) for North Carolina and South Carolina. This work is part of ongoing modeling efforts for the United States. For more information on coastal storm modeling, see https://www.usgs.gov/centers/pcmsc/science/coastal-storm-modeling-system-cosmos. Although this Federal Geographic Data Committee-compliant metadata file is intended to document the data set in nonproprietary form, as well as in Esri format, this metadata file may include some Esri-specific terminology.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2023
Currentness_Reference: publication year
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None Planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -81.41555
East_Bounding_Coordinate: -75.44948
North_Bounding_Coordinate: 36.55215
South_Bounding_Coordinate: 32.03543
Keywords:
Theme:
Theme_Keyword_Thesaurus: USGS Metadata Identifier
Theme_Keyword: USGS:fe48822f-f055-4106-82d1-bae59dd2c1b0
Theme:
Theme_Keyword_Thesaurus: Data Categories for Marine Planning
Theme_Keyword: Physical Habitats and Geomorphology
Theme:
Theme_Keyword_Thesaurus: Global Change Master Directory (GCMD)
Theme_Keyword: Hazards Planning
Theme_Keyword: Ocean Waves
Theme_Keyword: Ocean Winds
Theme_Keyword: Beaches
Theme_Keyword: Erosion
Theme_Keyword: Sea Level Rise
Theme_Keyword: Storm Surge
Theme_Keyword: Extreme Weather
Theme_Keyword: Floods
Theme_Keyword: Water Depth
Theme:
Theme_Keyword_Thesaurus: USGS Thesaurus
Theme_Keyword: Climate Change
Theme_Keyword: Storms
Theme_Keyword: Wind
Theme_Keyword: Floods
Theme_Keyword: Sea-level Change
Theme_Keyword: mathematical modeling
Theme_Keyword: effects of climate change
Theme_Keyword: earth sciences
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: Oceans
Theme_Keyword: ClimatologyMeteorologyAtmosphere
Theme:
Theme_Keyword_Thesaurus: Marine Realms Information Bank (MRIB) keywords
Theme_Keyword: sea level change
Theme_Keyword: waves
Theme_Keyword: floods
Theme_Keyword: coastal erosion
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: U.S. Geological Survey
Theme_Keyword: USGS
Theme_Keyword: Coastal and Marine Hazards and Resources Program
Theme_Keyword: CMHRP
Theme_Keyword: Pacific Coastal and Marine Science Center
Theme_Keyword: PCMSC
Place:
Place_Keyword_Thesaurus: Geographic Names Information System (GNIS)
Place_Keyword: State of North Carolina
Place_Keyword: State of South Carolina
Access_Constraints: None
Use_Constraints:
USGS-authored or produced data and information are in the public domain from the U.S. Government and are freely redistributable with proper metadata and source attribution. Please recognize and acknowledge the U.S. Geological Survey as the originator of the dataset and in products derived from these data.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Person: PCMSC Science Data Coordinator
Contact_Address:
Address_Type: mailing and physical
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Contact_Voice_Telephone: 831-427-4747
Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov
Browse_Graphic:
Browse_Graphic_File_Name: Projections_FloodHazard_NC_SC.png
Browse_Graphic_File_Description:
Map showing area of modelled projections of flood hazards and flood potential for North and South Carolina.
Browse_Graphic_File_Type: PNG
Data_Set_Credit:
This data release was funded by the Additional Supplemental Appropriations for Disaster Relief Act of 2019 (H.R. 2157) for North Carolina and South Carolina. The authors would like to acknowledge the following important contributions: Liv Herdman for help with understanding and accessing the National Water Model (NWM) data; Richard Signell and Daniel Nowacki for crucial python code and troubleshooting help in downloading National Water Model data hosted on Amazon Web Services (AWS); Fernando Salas for sharing route link files for NWM that were crucial in establishing watershed information; Brian Cosgrove and Anthony Guerriero for connecting the authors to Fernando Salas; and Malcolm Roberts for help navigating the CMIP6 tropical cyclone tracking products, providing additional information and access to them, and helpful discussions on research. Additionally, authors would like to extend special thanks to USGS colleagues for a detailed review of the projections: Amy Farris, Rachel Henderson, Kathy Weber, Justin Birchler, Alex Seymour, Sharifa Karwandyar, Matt Hardy, and Josh Pardun.
Native_Data_Set_Environment:
The datasets were created in a Windows 11 Operating system, using Matlab v2020, ArcGIS 10.8.1 and 10.8.8, and python 3.7. Results were output and saved as vector shapefiles.
Cross_Reference:
Citation_Information:
Originator: K. Nederhoff
Originator: T. Leijnse
Originator: K.A. Parker
Originator: J.A. Thomas
Originator: A.C. O'Neill
Originator: M. van Ormondt
Originator: R. McCall
Originator: L.H. Erikson
Originator: P.L. Barnard
Originator: A.C. Foxgrover
Originator: W. Klessens
Originator: N.C. Nadal-Caraballo
Originator: C. Massey
Publication_Date: 2023
Title:
Tropical cyclones or extratropical storms: what drives the compound flood hazard, impact and risk for the US Southeast Atlantic coast?
Other_Citation_Details:
Nederhoff, K., Leijnse, T., Parker, K.A., Thomas, J.A., O'Neill, A.C., van Ormondt, M., McCall, R., Erikson, L.H., Barnard, P.L., Foxgrover, A.C., Klessens W., Nadal-Caraballo, N.C., and Massey, C., 2023, Tropical cyclones or extratropical storms: what drives the compound flood hazard, impact and risk for the US Southeast Atlantic coast?: in final review at Coastal Engineering, available on Earth ArXiv, https://doi.org/10.31223/X56H26.
Online_Linkage: https://doi.org/10.31223/X56H26
Cross_Reference:
Citation_Information:
Originator: N.C. Nadal-Caraballo
Originator: M.O. Campbell
Originator: V.M. Gonzalez
Originator: M.J. Torres
Originator: J.A. Melby
Originator: A.A. Taflanidis
Publication_Date: 2020
Title:
Coastal Hazards System: A Probabilistic Coastal Hazard Analysis Framework
Other_Citation_Details:
Nadal-Caraballo, N. C., Campbell, M. O., Gonzalez, V. M., Torres, M. J., Melby, J. A., and Taflanidis, A. A., 2020, Coastal Hazards System: A Probabilistic Coastal Hazard Analysis Framework, Journal of Coastal Research, 95, 1211, https://doi.org/10.2112/SI95-235.1
Online_Linkage: https://doi.org/10.2112/SI95-235.1
Cross_Reference:
Citation_Information:
Originator: R.J. Haarsma
Originator: M.J. Roberts
Originator: P.L. Vidale
Originator: C.A. Senior
Originator: A. Bellucci
Originator: Q. Bao
Originator: P. Chang
Originator: S. Corti
Originator: N.S. Fučkar
Originator: V. Guemas
Originator: J. von Hardenberg
Originator: W. Hazeleger
Originator: C. Kodama
Originator: T. Koenigk
Originator: L. R. Leung
Originator: J. Lu
Originator: J.J. Luo
Originator: J. Mao
Originator: M.S. Mizielinski
Originator: R. Mizuta
Originator: P. Nobre
Originator: M. Satoh
Originator: E. Scoccimarro
Originator: T. Semmler
Originator: J. Small
Originator: J.S. von Storch
Publication_Date: 2016
Title:
High resolution model intercomparison project (HighResMIP v1.0) for CMIP6
Other_Citation_Details:
Haarsma, R.J., Roberts, M.J., Vidale, P.L., Senior, C.A., Bellucci, A., Bao, Q., Chang, P., Corti, S., Fučkar, N.S., Guemas, V., von Hardenberg, J., Hazeleger, W., Kodama, C., Koenigk, T., Leung, L. R., Lu, J., Luo, J. J., Mao, J., Mizielinski, M.S., Mizuta, R., Nobre, P., Satoh, M., Scoccimarro, E., Semmler, T., Small, J., and von Storch, J.S., 2016, High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6, Geoscientific Model Development, 9, 4185–4208, https://doi.org/10.5194/gmd-9-4185-2016, 2016.
Online_Linkage: https://doi.org/10.5194/gmd-9-4185-2016
Cross_Reference:
Citation_Information:
Originator: Natural Resources Conservation Service
Publication_Date: 1985
Title: National Engineering Handbook
Other_Citation_Details:
Natural Resources Conservation Service, 1985, Hydrology, in, Natural Resources Conservation Service, 1985, National Engineering Handbook: U.S. Dept. of Agriculture, Soil Conservation Service.
Online_Linkage:
Cross_Reference:
Citation_Information:
Originator: Tim Leijnse
Originator: Maarten van Ormondt
Originator: Kees Nederhoff
Originator: Ap van Dongeren
Publication_Date: 2021
Title:
Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes
Other_Citation_Details:
Leijnse, T., van Ormondt, M., Nederhoff, K., and van Dongeren, A., 2021, Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes, Coastal Engineering, v. 163, https://doi.org/10.1016/j.coastaleng.2020.103796
Online_Linkage: https://doi.org/10.1016/j.coastaleng.2020.103796
Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
Attribute values are model-derived extents of flood projections, ponding areas, and maximum/minimum flood potential (flood uncertainty) due to plausible sea-level rise and future storm conditions and therefore cannot be validated against observations. The projections were generated using the latest downscaled climate projections from the Coupled Model Intercomparison Project (CMIP6).
Logical_Consistency_Report: Data have undergone quality checks and meet standards.
Completeness_Report:
Dataset is considered complete for the information presented (as described in the abstract).
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report: Data are concurrent with topobathymetric DEM locations.
Vertical_Positional_Accuracy:
Vertical_Positional_Accuracy_Report:
Model-derived data are accurate within the flood potential layers (uncertainty bounds), indicative of total uncertainty from elevation data sources, model processes and contributing data, and vertical land motion. This value is spatially variable and dependent on scenario. See Process Steps for details on total contributions to uncertainty.
Lineage:
Source_Information:
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Citation_Information:
Originator: Malcolm Roberts
Publication_Date: 2019
Title:
MOHC HadGEM3-GC31-HH model output prepared for CMIP6 HighResMIP highres-future
Geospatial_Data_Presentation_Form: netCDF files
Publication_Information:
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Wind velocities, sea level pressure, and precipitation output were used as boundary conditions for the SFINCS model.
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MOHC HadGEM3-GC31-HM model output prepared for CMIP6 HighResMIP highres-future
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Wind velocities, sea level pressure, and precipitation output were used as boundary conditions for the SFINCS model.
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Originator: Malcolm Roberts
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MOHC HadGEM3-GC31-HM-SST model output prepared for CMIP6 HighResMIP highresSST-present
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The SST variant of HadGEM, wind velocities, sea level pressure, and precipitation output were used as boundary conditions for the SFINCS model.
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EC-Earth-Consortium EC-Earth3P-HR model output prepared for CMIP6 HighResMIP highres-future
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Wind velocities, sea level pressure, and precipitation output were used as boundary conditions for the SFINCS model.
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CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 ScenarioMIP ssp585
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Wind velocities, sea level pressure, and precipitation output were used as boundary conditions for the SFINCS model.
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Wind velocities, sea level pressure, and precipitation output were used as boundary conditions for the SFINCS model.
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Wind velocities, sea level pressure, and precipitation output were used as boundary conditions for the SFINCS model.
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Publication_Information:
Publication_Place: online
Publisher: U.S. Geological Survey
Online_Linkage: https://doi.org/10.5066/P9KR0RFM
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2022
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: WW3
Source_Contribution: projected wave data
Source_Information:
Source_Citation:
Citation_Information:
Originator: Kai A. Parker
Originator: Li Erikson
Originator: Jennifer A. Thomas
Originator: Kees Nederhoff
Originator: Tim Leijnse
Publication_Date: 2023
Title:
Nearshore parametric wave setup hindcast data (1979-2019) for North Carolina and South Carolina coasts
Geospatial_Data_Presentation_Form: csv files
Publication_Information:
Publication_Place: online
Publisher: United States Geological Survey
Online_Linkage: https://doi.org/10.5066/P9W91314
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2023
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: waveSetup_hindc
Source_Contribution: provided wave setup for the hindcast period
Source_Information:
Source_Citation:
Citation_Information:
Originator: Kai A. Parker
Originator: Li Erikson
Originator: Jennifer A. Thomas
Originator: Kees Nederhoff
Originator: Tim Leijnse
Publication_Date: 2023
Title:
Nearshore parametric wave setup future projections (2020-2050) for North Carolina and South Carolina coasts
Geospatial_Data_Presentation_Form: csv files
Publication_Information:
Publication_Place: online
Publisher: United States Geological Survey
Online_Linkage: https://doi.org/10.5066/P9W91314
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2023
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: waveSetup_proj
Source_Contribution: provided wave setup for the projection period
Source_Information:
Source_Citation:
Citation_Information:
Originator: Kai A. Parker
Originator: Li Erikson
Originator: Jennifer A. Thomas
Originator: Kees Nederhoff
Originator: Tim Leijnse
Publication_Date: 2023
Title:
Nearshore water level, tide and non-tidal residual hindcasts (1979-2016) for North Carolina and South Carolina coasts
Geospatial_Data_Presentation_Form: csv files
Publication_Information:
Publication_Place: online
Publisher: United States Geological Survey
Online_Linkage: https://doi.org/10.5066/P9W91314
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2023
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: waterLevel_hindc
Source_Contribution:
provided water levels, tides, and non-tidal residuals for the hindcast period
Source_Information:
Source_Citation:
Citation_Information:
Originator: Kai A. Parker
Originator: Li Erikson
Originator: Jennifer A. Thomas
Originator: Kees Nederhoff
Originator: Tim Leijnse
Publication_Date: 2023
Title:
Nearshore water level, tide and non-tidal residual projections (2016-2050) for North Carolina and South Carolina coasts
Geospatial_Data_Presentation_Form: csv files
Publication_Information:
Publication_Place: online
Publisher: United States Geological Survey
Online_Linkage: https://doi.org/10.5066/P9W91314
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2023
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: waterLevel_proj
Source_Contribution:
provided water levels, tides, and non-tidal residuals for the projection period
Source_Information:
Source_Citation:
Citation_Information:
Originator: Y. Xia
Originator: M. Mitchell
Originator: J. Ek
Originator: B. Sheffield
Originator: E. Cosgrove
Originator: L. Wood
Originator: C. Luo
Originator: H. Alonge
Originator: J. Wei
Originator: B. Meng
Originator: D. Livneh
Originator: V. Lettenmaier
Originator: Q. Koren
Originator: K. Mo Duan
Originator: Y. Fan
Originator: D. Mocko
Publication_Date: 2009
Title:
North American Land Data Assimilation System (NLDAS) Primary Forcing Data L4 Hourly 0.125 x 0.125 degree V002
Geospatial_Data_Presentation_Form: GRIB files
Publication_Information:
Publication_Place: online
Publisher:
Goddard Earth Sciences Data and Information Services Center (GES DISC)
Online_Linkage: https://10.5067/6J5LHHOHZHN4
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2009
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: NLDAS
Source_Contribution: historic precipitation used to compare to NWM streamflow
Source_Information:
Source_Citation:
Citation_Information:
Originator: Yan Y. Liu
Originator: David R. Maidment
Originator: David G. Tarboton
Originator: Xing Zheng
Originator: Ahmet Yildirim
Originator: Nazmus S. Sazib
Originator: Shaowen Wang
Publication_Date: 2016
Title: NFIE Continental Flood Inundation Mapping - Data Repository
Geospatial_Data_Presentation_Form: shapefiles
Publication_Information:
Publication_Place: online
Publisher: University of Texas
Online_Linkage: https://web.corral.tacc.utexas.edu/nfiedata/
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20201007
Source_Currentness_Reference: time when data were accessed
Source_Citation_Abbreviation: NFIE
Source_Contribution: shapefiles providing stream reach ID locations
Source_Information:
Source_Citation:
Citation_Information:
Originator: NOAA
Publication_Date: 2020
Title: The NOAA National Water Model Retrospective dataset, V.2.0
Geospatial_Data_Presentation_Form: zarr
Publication_Information:
Publication_Place: online
Publisher: aws
Online_Linkage: https://registry.opendata.aws/nwm-archive
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20201231
Source_Currentness_Reference: date data were accessed
Source_Citation_Abbreviation: NWM
Source_Contribution: used to establish projected river/fluvial discharge
Source_Information:
Source_Citation:
Citation_Information:
Originator: Manoocher Shirzaei
Originator: Leonard Ohenhen
Originator: Matthew W. Hardy
Publication_Date: 2023
Title:
Vertical land motion rates for the years 2007 to 2021 for North Carolina and South Carolina coasts
Geospatial_Data_Presentation_Form: csv files
Publication_Information:
Publication_Place: online
Publisher: United States Geological Survey
Online_Linkage: https://doi.org/10.5066/P9W91314
Type_of_Source_Media: online database
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2023
Source_Currentness_Reference: publication date
Source_Citation_Abbreviation: VLM
Source_Contribution: provided vertical land motion for uncertainty calculations
Process_Step:
Process_Description:
All processes and methods are outlined in Nederhoff and others (2023); please refer to that for more information beyond the summary in this document. To generate time-series of forcings for coastal flooding models in order to map future coastal flooding hazards along the south Atlantic United States coast due to sea level rise and plausible future storm conditions that consider the changing climate, hurricanes, and natural variability, we gathered available atmospheric forcing data (specifically precipitation, sea-level pressure, and near-surface wind for this study) from CMIP6 Global Climate Models (GCM). At the time of this study, only products for Representative Concentration Pathway 8.5 for the projected time-period 2020-2050 were available and used. Output was gathered for specific High-Resolution Model Intercomparison Project (HighResMIP) experiments: HadGEM3-GC31, EC-Earth3P-HR, CNRM-CM6-1-HR, GFDL-CMC4C192 and CMCC-CM2-VHR4
Source_Used_Citation_Abbreviation:
HadGEM3-GC31-HH, HadGEM3-GC31-HM, HadGEM3-GC31-HM-SST, EC-Earth3P-HR, CNRM-CM6-1-HR, GFDL-CMC4C192 and CMCC-CM2-VHR4
Process_Date: 20200501
Process_Step:
Process_Description:
We analyzed multi-model trends in future (2020-2050) tropical cyclone climatology depicted in GCMs throughout the study area (Nederhoff and others, 2023). This included detailed comparisons to historical runs in probability functions of tropical cyclone sea-level pressure, propagation speed and maximum wind speed throughout the study area, to highlight future changes in tropical cyclone characteristics by geographical position
Source_Used_Citation_Abbreviation:
HadGEM3-GC31-HH, HadGEM3-GC31-HM, HadGEM3-GC31-HM-SST, EC-Earth3P-HR, CNRM-CM6-1-HR, GFDL-CMC4C192 and CMCC-CM2-VHR4
Process_Date: 20201215
Process_Step:
Process_Description:
We obtained Global Surge and Tide Model (GTSM) output (run for all aforementioned CMIP6 experiments’ sea-level pressure and wind) for nearshore water levels for projected period 2016-2050, and historical period (1976-2015). As described in Nederhoff and others (2023), we conducted initial comparisons of datasets and analysis of extreme water level changes, before preparing data for use in following process steps.
Source_Used_Citation_Abbreviation: GTSM
Process_Date: 20201215
Process_Step:
Process_Description:
As described by Nederhoff and others (2023), we tested the Super-Fast Inundation of CoastS model (SFINCS; Leijnse and others, 2021) resolutions and computational efficiency. Determined running the SFINCS at 200 m spatial resolution, with sub-gridding was optimum for this study, providing balance between fast simulations and accuracy of coastal water levels (tested for Hurricane Florence,14 September 2018, with historical NOAA water levels). The study area was covered by three rectilinear SFINCS domains, aligned shore-normal for each respective area, with the offshore boundary as the nearshore GTSM output locations. Model boundaries extend outside the study area to encompass and include necessary hydrodynamics. Elevation for the SFINCS domains was extracted from the corresponding DEMs in the region and resampled from 1 meter resolution to the SFINCS model's computational grid. SFINCS simulations were run with soil infiltration rates derived using the Curve Number Method (U.S. Dept. of Agriculture, Soil Conservation Service, 1985) to capture absorption/run-off of precipitation in the model. Curve Numbers were derived using the National Land Classification Dataset (NLCD 2016) and the Digital General Soil Map of the United States (NRCS).
Source_Used_Citation_Abbreviation: NOAA water levels, DEM1, DEM2
Process_Date: 20210115
Process_Step:
Process_Description:
We conducted initial comparisons of WW3 data for projections (run with wind conditions for all aforementioned CMIP6 experiments) at the 15-20 m isobath and analysis of extreme nearshore wave changes, before preparing data for use in following process steps.
Source_Used_Citation_Abbreviation: WW3
Process_Date: 20210228
Process_Step:
Process_Description:
Hindcasted water levels were compared to NOAA tide station observations and were used to guide any necessary bias corrections (see the Nearshore water level, tide and non-tidal residual projections (2016-2050) and hindcasts (1979-2016) for North Carolina and South Carolina datasets, also available in this data release). Bias corrections were applied to the projected water levels. See Nederhoff and others (2023) for more details.
Source_Used_Citation_Abbreviation: waterLevel_hindc, waterLevel_proj
Process_Date: 20210301
Process_Step:
Process_Description:
In collaboration with U.S. Army Corps of Engineers (USACE), we used a synthetic database available from Nadal-Caraballo and others (2020) of approximately 1,200 tropical cyclone events to establish a baseline of boundary conditions for tropical storms. As described in Nederhoff and others (2023), changes in tropical storm parameters, computed from the previous tropical cyclone analysis comparing GCM data for historical to future periods, were used to shift the hazard curves to represent future cyclone conditions and changes in frequency of occurrence and magnitude.
Process_Date: 20210531
Process_Step:
Process_Description:
We derived future time-series data of river/fluvial discharge through the study area for 48 rivers, using the relationship between historical NLDAS precipitation and NWM reanalysis data and applying it to future GCM precipitation output (Nederhoff and others, 2023). The upstream watershed of each of the 48 rivers was identified from the network of river reach IDs used by the NWM (NFIE). Historical precipitation (1993-2018) over each individual watershed was used for each respective river. Future discharge was then estimated by applying future GCM precipitation data (2020-2050) over watersheds and using the established relationships between historical precipitation/pluvial rates and discharge. When no precipitation was projected in data, baseline river discharge rates (from NWM historical periods) were used. An additional river time series consisted solely of its historical baseline discharge, due to its watershed being too small for this process.
Source_Used_Citation_Abbreviation: NLDAS, NWM, NFIE
Process_Date: 20211101
Process_Step:
Process_Description:
Using the GTSM output and computed wave setup, we identified extreme water levels along the open coast and associated fluvial inputs and precipitation for extreme coastal water elevation events. As described by Nederhoff and others (2023), the largest coastal storm events (from GTSM storm tide and wave setup) of each GCM were identified, equivalent to an average of the largest 5 storms per year. The overland flow model (SFINCS) was run for all anomalously high-water level events (top 150 from each contributing GCM, plus all tropical cyclone events from USACE) with each event’s commensurate GTSM coastal water levels, wave setup, SLR, point-source river discharge (at each river), and precipitation data fields included as forcing for the simulation
Source_Used_Citation_Abbreviation:
GTSM, waterLevel_proj, waterLevel_proj, waveSetup_hindc, waveSetup_proj
Process_Date: 20210615
Process_Step:
Process_Description:
Detailed quality control was conducted for test outputs from the model system. After identifying initial sources of error, all simulations were rerun.
Process_Date: 20211101
Process_Step:
Process_Description:
Return period (RP) statistics (1/20/100-year storm, or no storm/daily average conditions) were calculated per grid cell for each SLR scenario to yield a composited raster of water levels for each SLR and storm combination (Nederhoff and others, 2023). With each composited raster, by RP and SLR, a depth threshold of 5 cm (at native 200-m scale of SFINCS computational grid) was used to preserve legitimate flood projections in high-relief areas. Raster outputs were run through an iterative function (in Matlab) to identify cells connected to coastally driven flooding (such as, physically connected to contiguous coastal flood surface and ocean). For cells not connected to coastal flooding, output was labeled "ponding", to signify vulnerability to flood hazards driven by river discharge or precipitation. Water levels/elevations in each cell were then depth-differenced to underlying DEM data (sub-sampled to horizontal resolution of 10 m) to resolve fine-scale features in coastal flood hazards and ponding areas, as well as return corresponding water depth information. Water depths were only calculated for areas identified as coastal flooding (not ponding), as that was the focus of the study. Uncertainty was calculated as a sum of contributions, including DEM uncertainty (35 cm), projected vertical land motion (VLM) based on SLR (spatially variable per SLR scenario), and uncertainty with the model and model processes (spatially variable, derived from water level return-period curves at each grid point, dependent on scenario). This total uncertainty is applied to the final water elevation and extrapolated outward to depict the maximum and minimum potential flood area considering total uncertainty (labeled as ‘flood potential’). Water depths are accurate within these bounds.
Source_Used_Citation_Abbreviation: VLM, DEM1, DEM2
Process_Date: 20220115
Process_Step:
Process_Description:
Data from all domains were merged to make geoTIFFs of the originating rasters for each data layer (coastal flood hazard, ponding, and maximum/minimum flood potential). The geoTIFFs were exported as shapefiles from ArcMap for all combinations of seven SLRs (0, 0.25, 0.5, 1.0, 1.5, 2.0 and 3.0 m), 3 storms (1-year, 20-year, and 100-year return period coastal events), and the non-storm condition for a total of 28 scenarios. Final shapefiles were separated by state (Projections_FloodHazards_*STATE*.zip) for file-size considerations. Shapefiles are further organized by storm scenario (’RP’), with flood hazards and ponding under one directory, and flood potential in another directory. Shapefiles depicting the study-area boundary are also included (FloodHazard_boundaries_NC_SC.zip).
Process_Date: 20220126
Process_Step:
Process_Description:
Metadata was modified to include doi# and full citation for Nederhoff and others (2023) Cross Reference. No data information was changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata dates to determine which metadata file is most recent.
Process_Date: 20230313
Process_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Susan A Cochran
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Position: Geologist
Contact_Address:
Address_Type: mailing and physical address
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060-5792
Country: USA
Contact_Voice_Telephone: (831) 460-7545
Contact_Electronic_Mail_Address: scochran@usgs.gov
Process_Step:
Process_Description:
Edits were made to correct spelling in authors names and to add final citation information to a Cross_Reference. No data were changed. The metadata available from a harvester may supersede metadata bundled within a download file. Users are advised to compare the metadata date of this file to any similar file to ensure they are using the most recent version. (scochran@usgs.gov)
Process_Date: 20230516
Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Vector
Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Grid_Coordinate_System:
Grid_Coordinate_System_Name: Universal Transverse Mercator
Universal_Transverse_Mercator:
UTM_Zone_Number: 17
Transverse_Mercator:
Scale_Factor_at_Central_Meridian: 0.9996
Longitude_of_Central_Meridian: -81.00000
Latitude_of_Projection_Origin: 0.00000
False_Easting: 500000.0
False_Northing: 0.00
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 10
Ordinate_Resolution: 10
Planar_Distance_Units: Meters
Geodetic_Model:
Horizontal_Datum_Name: GCS WGS 1984
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.00
Denominator_of_Flattening_Ratio: 298.257223563
Vertical_Coordinate_System_Definition:
Depth_System_Definition:
Depth_Datum_Name: North American Vertical Datum of 1988
Depth_Resolution: 0.01
Depth_Distance_Units: meters
Depth_Encoding_Method: Implicit coordinate
Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
Zip files contained in this part of the data release include projected flood hazards [Projections_FloodHazards_*STATE*.zip] and boundaries of study area [FloodHaz_ModelOutput_Boundary_NC.zip and FloodHaz_ModelOutput_Boundary_SC.zip] shapefiles containing single-polygon projected extents of flood hazard, ponding, maximum flooding potential, minimum flooding potential, and boundaries of North and South Carolina study area The data contain projections of coastally driven flood extent (‘flood_hazards’), areas vulnerable to flooding but not hydrologically connected to coastal flooding (‘ponding’), and the minimum and maximum potential flood extent given total uncertainty (‘min_potential’ and ‘max_potential’). Shapefiles represent the given hazard associated with the sea-level rise and storm condition indicated. Storm condition return periods cover background conditions (RP000), once-a-year on average storms (RP001), every 20 years on average (RP20) and every 100 years on average (RP100) storms. Shapefile names reflect the area of the projection (state), the attribute of the shapefile, the sea level rise (SLR) scenario (in centimeters) and the return period (RP) of storm conditions. SLR scenarios range from no SLR (SLR000) to a SLR of 300 cm (SLR300). Files are grouped by state, containing all SLR, RP and output files. For example, Projections_FloodHazards_NC.zip, contains all output for North Carolina, within which NC_flood_hazard_SLR200_RP100 illustrates the flood extents for a sea level rise of 200 cm (2 m) during a 100-year storm in the state.
Entity_and_Attribute_Detail_Citation: none
Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey - CMGDS
Contact_Address:
Address_Type: mailing and physical
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Contact_Voice_Telephone: 831-427-4747
Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov
Resource_Description:
These data are available as zip files by state for which [FloodHazards_*STATE*.zip] is the filename, where *STATE* can be either North Carolina (NC) or South Carolina (SC).
Distribution_Liability:
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: Shapefile
Format_Version_Number: ArcGIS 10.8.1
Format_Specification: Esri polygon shapefile
Format_Information_Content:
Zip file contains the flood hazard polygon shapefiles for North Carolina
File_Decompression_Technique: WinZip
Transfer_Size: 11000.00
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.5066/P9W91314
Access_Instructions:
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
Digital_Form:
Digital_Transfer_Information:
Format_Name: Shapefile
Format_Version_Number: ArcGIS 10.8.1
Format_Specification: Esri polygon shapefile
Format_Information_Content:
Zip file contains the flood hazard polygon shapefiles for South Carolina
File_Decompression_Technique: WinZip
Transfer_Size: 594.8
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.5066/P9W91314
Access_Instructions:
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
Digital_Form:
Digital_Transfer_Information:
Format_Name: Shapefile
Format_Version_Number: ArcGIS 10.8.1
Format_Specification: Esri polygon shapefile
Format_Information_Content:
Zip file contains the flood hazard study area boundary shapefile for NC
File_Decompression_Technique: WinZip
Transfer_Size: 0.2
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.5066/P9W91314
Access_Instructions:
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
Digital_Form:
Digital_Transfer_Information:
Format_Name: Shapefile
Format_Version_Number: ArcGIS 10.8.1
Format_Specification: Esri polygon shapefile
Format_Information_Content:
Zip file contains the flood hazard study area boundary shapefile for SC
File_Decompression_Technique: WinZip
Transfer_Size: 0.1
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.5066/P9W91314
Access_Instructions:
Data can be downloaded using the Network_Resource_Name link then scrolling down to the Simulation Data section.
Fees: None
Metadata_Reference_Information:
Metadata_Date: 20230516
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization:
U.S. Geological Survey, Pacific Coastal and Marine Science Center
Contact_Person: PCMSC Science Data Coordinator
Contact_Address:
Address_Type: mailing and physical
Address: 2885 Mission Street
City: Santa Cruz
State_or_Province: CA
Postal_Code: 95060
Contact_Voice_Telephone: 831-427-4747
Contact_Electronic_Mail_Address: pcmsc_data@usgs.gov
Metadata_Standard_Name: Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998

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