Justin J. Birchler Kara S. Doran 20251117 vector digital data Kara S. Doran Justin J. Birchler Heather A. Schreppel Hilary F. Stockdon David M. Thompson 20190619 2.0 U.S. Geological Survey data release doi:10.5066/P9Z362BC St. Petersburg, Florida U.S. Geological Survey https://doi.org/10.5066/P9Z362BC This dataset defines storm-induced coastal erosion hazards for the Florida west coast and Florida through North Carolina Atlantic coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Ian in September 2022. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of three types of coastal change: collision (dune erosion), overwash, and inundation. To provide data on the probability of storm-induced coastal erosion hazards for the Florida, Georgia, South Carolina and North Carolina coast for Hurricane Ian. 20220928 ground condition Complete None planned, however future updates and post-storm analyses are anticipated. -82.8521 -77.9038 34.0019 25.6680 USGS Metadata Identifier USGS:02f3e996-ce2d-4e26-866f-301eff577014 None U.S. Geological Survey USGS St. Petersburg Coastal and Marine Science Center SPCMSC Coastal/Marine Hazards and Resources Program CMHRP coastal Hurricane Ian ISO 19115 Topic Category oceans elevation environment geoscientificInformation USGS Thesaurus hazards marine geology ocean sciences coastal processes erosion Data Categories for Marine Planning distributions bathymetry and elevation physical habitats and geomorphology Marine Realms Information Bank (MRIB) Keywords effects of coastal change shoreline accretion shoreline erosion storm erosion topographic mapping hurricanes and typhoons Geographic Names Information System United States of America Florida Georgia South Carolina North Carolina No access constraints. Please see 'Distribution Information' for details. These data are marked with a Creative Commons CC0 1.0 Universal License. These data are in the public domain and do not have any use constraints. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. Justin J. Birchler Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 jbirchler@usgs.gov The predicted elevations of storm surge were extracted from the National Oceanic and Atmospheric Administration (NOAA) Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model, which has been employed by NOAA in inundation risk studies and operational storm surge forecasting. Wave runup and setup conditions were generated using NOAA's WaveWatch III model. Microsoft Windows 10; Esri ArcGIS 10.6.0.8321 Stockdon, H.F. Doran, K.J. Thompson, D.M. Sopkin, K.L. Plant, N.G. Sallenger, A.H. 2012 U.S. Geological Survey Open-File Report doi:10.3133/ofr20121084 Reston, VA U.S. Geological Survey https://doi.org/10.3133/ofr20121084 No additional checks for consistency were performed on this data. This dataset includes dune morphology and hurricane hydrodynamic data used to generate probabilities of hurricane-induced erosion, elevation data from lidar surveys are not included. Measurements were collected approximately every 10-meters (m) and summarized to 500 m segments. Horizontal accuracy was not estimated. Vertical accuracy for hydrodynamic measurements (surge, setup, and runup) is dependent on input data. SLOSH model accuracy is estimated to be +/- 20 percent of the calculated value. No other accuracy checks were performed. Vertical accuracy for dune morphology (dune crest and toe elevation) data is dependent on the positional accuracy of the lidar data. Estimated accuracy of lidar surveys are +/- 15 centimeters. However, vertical accuracies may vary based on the type of terrain (for example, inaccuracies may increase as slope increases or with the presence of extremely dense vegetation), the accuracy of the global positioning system (GPS), and aircraft-attitude measurements. National Hurricane Center, National Oceanic and Atmospheric Administration 20220928 https://slosh.nws.noaa.gov/psurge2.0/ ftp://ftp.ncep.noaa.gov/pub/data/nccf/com/psurge/prod/ Online digital data 20220928 The date when web page was last modified. P-Surge Data provides water levels that have a 1 in 10 chance of being exceeded within the next 102 hours. NOAA National Weather Service Environmental Modeling Center 20220928 https://polar.ncep.noaa.gov/nwps/para/viewer.shtml Online digital data 20220928 The date when web page was last modified. NWPS Wave model that was used to estimate wave setup and runup conditions at the shoreline within the next 145 hours. United States Army Corps of Engineers (USACE) 20161215 Geographic Coverage: Florida Panhandle (Fort Walton Beach to Bald Point State Park), Florida west coast (Anclote Key to Marco Island) https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=5190 https://coast.noaa.gov/htdata/raster2/elevation/USACE_Florida_Gulf_Cst_Topobathy_DEM_2015_5190 Online digital data 20150606 20150630 The date when lidar surveys were collected. USACE FL WC 2015 A lidar survey that was used to estimate dune morphology variables. National Oceanic Atmospheric Administration (NOAA) National Geodetic Survey (NGS) Remote Sensing Division 20190728 Geographic Coverage: FL WC (Desoto to Boca Grande) https://chs.coast.noaa.gov/htdata/lidar1_z/geoid18/data/8793/ https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8793 Online digital data 20171010 20171027 The date when lidar surveys were collected. NOAA NGS FL WC 2017 A lidar survey that was used to estimate dune morphology variables. Digital Aerial Solutions, LLC (DAS), United States Geological Survey (USGS) 20190711 Geographic Coverage: FL WC (Boca Grande to Marco Island) https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_FL_Southwest_A_2018_LAS_2019/ https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_FL_Southwest_B_2018_LAS_2019/ https://apps.nationalmap.gov/viewer/ Online digital data 20180508 20181029 The date when lidar surveys were collected. USGS FL WC 2018 A lidar survey that was used to estimate dune morphology variables. United States Army Corps of Engineers (USACE) 20171002 Geographic Coverage: FL East Coast https://chs.coast.noaa.gov/htdata/lidar2_z/geoid18/data/6330/ https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6330 Online digital data 20170918 20171025 The date when lidar surveys were collected. USACE FL EC 2017 A lidar survey that was used to estimate dune morphology variables. National Oceanic Atmospheric Administration (NOAA) National Geodetic Survey (NGS) Remote Sensing Division 20190724 Geographic Coverage: FL East Coast (Fort Lauderdale to Highland Beach, FL) https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8923/index.html https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8923 Online digital data 20180605 20180609 The date when lidar surveys were collected. USACE FL EC 2018 A lidar survey that was used to estimate dune morphology variables. United States Army Corps of Engineers (USACE) 20180514 Geographic Coverage: GA, SC, VA https://chs.coast.noaa.gov/htdata/lidar2_z/geoid18/data/5184/ https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=5184 Online digital data 20161028 20161126 The date when lidar surveys were collected. USACE Southeast 2016 A lidar survey that was used to estimate dune morphology variables. U.S. Army Corps of Engineers (USACE), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX) 20190906 Geographic Coverage: SC(Winyah Bay to NC border), NC, VA https://chs.coast.noaa.gov/htdata/lidar4_z/geoid18/data/8617/ https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8617 Online digital data 20181002 20181003 The date when lidar surveys were collected. USACE NCMP SC-VA 2018 A lidar survey that was used to estimate dune morphology variables. For dune morphology data: Elevation data from lidar surveys were interpolated in MATLAB (version R2017a) to a gridded domain that was rotated parallel to the shoreline and had a resolution of 10 m in the longshore direction and 2.5 m in the cross-shore direction. The interpolation method applied spatial filtering with a Hanning window that was twice as wide as the grid resolution. Dune morphology data were extracted from the elevation grid in MATLAB. Dune morphology data were then summarized to 500 m sections. Sections with greater than 75 percent of data missing were flagged with the invalid number of -999. The 1-kilometer smoothed dune crest (DHIGH), toe (DLOW) and root mean square (RMS) error for each (DHIrms and DLOrms) were written to line shapefiles using MATLAB's shapewrite.m script. USACE FL WC 2015 NOAA NGS FL WC 2017 USGS FL WC 2018 USACE FL EC 2017 USACE FL EC 2018 USACE Southeast 2016 USACE NCMP SC-VA 2018 2022 Dune morphology (DHIGH, DLOW, DHIrms, DLOrms) Justin J. Birchler Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 jbirchler@usgs.gov For hydrodynamic data: Water level was computed in MATLAB by adding storm surge from NOAAs Probabilistic Tropical Storm Surge (P-Surge) model (https://slosh.nws.noaa.gov/psurge2.0/) to wave setup and runup. The wave height and period used for calculating wave runup and setup came from the Wavewatch III model. Hydrodynamic parameters were calculated in MATLAB and exported into ArcGIS shapefile format. For details on modeling parameterization, see Stockdon and others (2012). P-Surge NWPS 20220928 Hydrodynamics (SURGE, SETUP, RUNUP) Justin J. Birchler Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 jbirchler@usgs.gov Probabilities of coastal erosion hazards were based on estimating the likelihood that the beach system would experience erosion and deposition patterns consistent with collision (PCOL), overwash (POVW), or inundation (PIND) regimes. The regimes were calculated by using values of dune morphology and mean and extreme water levels for each 500 m section, such that the probability of collision (PCOL) occurs when extreme water levels reach the dune toe; overwash (POVW) when extreme water levels reach the dune crest; and inundation (PIND) when mean water levels reach the dune crest. In cases where DLOW is null (-999) PCOL is also null (-999) due to the inability to compute water level elevation reaching dune toe. Probabilities were calculated in MATLAB and exported using MATLABs shapewrite.m script. For details on modeling parameterization, see Stockdon and others (2012) Dune morphology Hydrodynamics 20220928 Probabilities (PCOL, POVW, PIND) Justin J. Birchler Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 jbirchler@usgs.gov Vector String 3520 0.01975663976 0.0249972312 Decimal Degrees D WGS 1984 WGS 1984 6378137.0 298.257223563 Ian_PCOI_line Probabilities of hurricane-induced coastal erosion, dune morphology, and hurricane hydrodynamic data USGS FID Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Feature geometry. Esri Coordinates defining the features. DHIGH Elevation of dune crest, in meters, using the North American Vertical Datum of 1988 (NAVD88). Extracted from lidar surveys collected from June 2015 to October 2018. USGS 0.81231 9.2953 meters -999 Null value USGS DLOW Elevation of the dune toe, in meters . Extracted from lidar surveys collected from June 2015 to October 2018. USGS 0.61632 3.7193 meters -999 Null value USGS DHIrms Root mean square error of dune crest elevation measurements . USGS 0.1471 2.1228 meters -999 Null value USGS DLOrms Root mean square error of dune toe elevation measurements . USGS 0.1697 0.9736 meters -999 Null value USGS SURGE Storm surge water level. NOAA 0.549 5.8427 meters -999 Null value NOAA RUNUP Wave runup water level. USGS 0.1633 4.2274 meters -999 Null value USGS SETUP Wave setup water level. USGS 0.039489 1.7523 meters -999 Null value USGS PCOL Probability of collision. USGS 0.44167 100 percent -999 Null value USGS POVW Probability of overwash. USGS .000001 100 percent -999 Null value USGS PIND Probability of inundation. USGS 0 100 percent -999 Null value USGS MEAN Mean water level (surge + setup). USGS 0.71426 6.2965 meters -999 Null value USGS EXTREME Extreme water level (surge + runup). USGS 1.2771 7.9245 meters -999 Null value USGS TIDE Predicted tide water level. USGS 0 0 meters U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center USGS SPCMSC Data Management mailing and physical

600 4th Street South

Saint Petersburg FL 33701 727-502-8000 gs-g-spcmsc_data_inquiries@usgs.gov 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 for other purposes, nor on all computer systems, 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. shapefile zip https://coastal.er.usgs.gov/data-release/doi-P9Z362BC/data/Ian_2022.zip None, if obtained online. 20251117 U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center USGS SPCMSC Data Management mailing and physical

600 4th Street South

Saint Petersburg FL 33701 727-502-8000 gs-g-spcmsc_data_inquiries@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998