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 2019 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 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 Idalia in August 2023. 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 coast for Hurricane Idalia. 20230829 ground condition Complete None planned, however future updates and post-storm analyses are anticipated. -87.4525 -81.6783 30.3969 25.8458 USGS Metadata Identifier USGS:886fd7e0-23e1-47ba-9ba1-c72db19a8edf None U.S. Geological Survey USGS St. Petersburg Coastal and Marine Science Center SPCMSC Coastal/Marine Hazards and Resources Program CMHRP coastal Hurricane Idalia 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 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. Kara Doran Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 kdoran@usgs.gov The predicted elevations of storm surge were extracted from the National Oceanic and Atmospheric Administration's (NOAA) Probabilistic Hurricane Storm Surge (P-Surge) model; an ensemble model based on the 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 Nearshore Wave Prediction System model. Microsoft Windows 10; Esri ArcGIS 10.8.1 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 20230829 https://slosh.nws.noaa.gov/psurge2.0/ ftp://ftp.ncep.noaa.gov/pub/data/nccf/com/psurge/prod/ Online digital data 20230829 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 20230829 https://polar.ncep.noaa.gov/nwps/para/viewer.shtml Online digital data 20230829 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), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX) 20210316 Geographic Coverage: AL https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/9200/index.html https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9200 Online digital data 20200922 20201013 The date when lidar surveys were collected. USACE NCMP AL 2020 A lidar survey that was used to estimate dune morphology variables. United States Army Corps of Engineers (USACE), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX), Federal Emergency Management Agency (FEMA) 20181108 Geographic Coverage: FL Panhandle https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8625/index.html https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8625 Online digital data 20181024 20181104 The date when lidar surveys were collected. USACE JALBTCX FL PH 2018 A lidar survey that was used to estimate dune morphology variables. United States Army Corps of Engineers (USACE) 20161215 Geographic Coverage: FL PH (Fort Walton Beach to Bald Point State Park), FL WC (Anclote Key to Marco Island) https://coast.noaa.gov/htdata/raster2/elevation/USACE_Florida_Gulf_Cst_Topobathy_DEM_2015_5190 Online_Linkage: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=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://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8793/index.html 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. For dune morphology data: Elevation data from lidar surveys were interpolated in MATLAB (version R2021a) to a gridded domain that was rotated parallel to the shoreline and had a resolution of 10 m in the alongshore 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 JALBTCX FL PH 2018 USACE FL WC 2015 NOAA NGS FL WC 2017 USGS FL WC 2018 2023 Dune morphology (DHIGH, DLOW, DHIrms, DLOrms) Kara Doran Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 kdoran@usgs.gov For hydrodynamic data: Water level was computed in MATLAB by adding storm surge from NOAA's 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 Nearshore Wave Prediction System model (https://polar.ncep.noaa.gov/nwps/). 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 20230829 Hydrodynamics (SURGE, SETUP, RUNUP) Kara Doran Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 kdoran@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 MATLAB's shapewrite.m script. For details on modeling parameterization, see Stockdon and others (2012). Dune morphology Hydrodynamics 20230829 Probabilities (PCOL, POVW, PIND) Kara Doran Physical Scientist mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8000 kdoran@usgs.gov Vector String 1946 0.01975663976 0.0249972312 Decimal Degrees D WGS 1984 WGS 1984 6378137.0 298.257223563 Idalia_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 2015 to 2020. USGS 0.81403 10.3312 meters -999 Null value USGS DLOW Elevation of the dune toe, in meters NAVD88. Extracted from lidar surveys collected from 2015 to 2020. USGS 0.61893 3.4936 meters -999 Null value USGS DHIrms Root mean square error of dune crest elevation measurements (square meters). USGS 0.1802 1.7429 meters -999 Null value USGS DLOrms Root mean square error of dune toe elevation measurements . USGS 0.1612 0.8008 meters -999 Null value USGS SURGE Storm surge water level. NOAA 0.45026 3.5887 meters -999 Null value NOAA RUNUP Wave runup water level. USGS 0.000146 3.9249 meters -999 Null value USGS SETUP Wave setup water level. USGS 3.5e-05 1.5817 meters -999 Null value USGS PCOL Probability of collision. USGS 2.7954 100 percent -999 Null value USGS POVW Probability of overwash. USGS 0 100 percent -999 Null value USGS PIND Probability of inundation. USGS 0 100 percent -999 Null value USGS MEAN Mean water level (surge + setup). USGS 0.55292 4.6269 meters -999 Null value USGS EXTREME Extreme water level (surge + runup). USGS 1.0358 6.8578 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/Idalia_2023.zip None, if obtained online. 20251117 U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center USGS SPCMSC Data Management mailing and physical

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