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 Louisiana, Mississippi, Alabama and 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 Ida in August 2021. 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 Louisiana, Mississippi, Alabama and Florida coast for Hurricane Ida. 20210829 ground condition Complete None planned, however future updates and post-storm analyses are anticipated. -94.0024 -84.3336 30.3969 29.045 USGS Metadata Identifier USGS:5d55f0d8-92b6-492d-8776-412f9f67c57a None U.S. Geological Survey USGS St. Petersburg Coastal and Marine Science Center SPCMSC Coastal/Marine Hazards and Resources Program CMHRP coastal Hurricane Ida 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 Louisiana Mississippi Alabama 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. 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's (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 20210829 http://slosh.nws.noaa.gov/psurge2.0/index.php ftp://ftp.ncep.noaa.gov/pub/data/nccf/com/psurge/prod/ Online digital data 20210829 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 20210829 https://polar.ncep.noaa.gov/waves/ Online digital data 20210829 The date when the model was run. GFS-WAVE Wave model that was used to estimate wave setup and runup conditions at the shoreline within the next 180 hours. United States Army Corps of Engineers (USACE), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX) 20170913 Geographic Coverage: AL, FL, MS, TX https://chs.coast.noaa.gov/htdata/lidar4_z/geoid18/data/5186/ https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=5186 Online digital data 20160723 20161010 The date when lidar surveys were collected. USACE NCMP Gulf Coast 2016 A lidar survey that was used to estimate dune morphology variables. Woolpert, Inc., United States Geological Survey (USGS) 20171212 Geographic Coverage: LA Chenier Plain https://chs.coast.noaa.gov/htdata/lidar2_z/geoid18/data/8597/ https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8597 Online digital data 20170108 20170303 The date when lidar surveys were collected. USGS LA 2017 A lidar survey that was used to estimate dune morphology variables. Digital Aerial Solutions, LLC, United States Geological Survey (USGS) 20161018 Geographic Coverage: South Terrebonne and Gulf Islands ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_LA_SoTerrebonne_GI_2015_LAS_2016/ https://nationalmap.gov/viewer.html Online digital data 20150118 20150213 The date when lidar surveys were collected. USGS LA 2015 A lidar survey that was used to estimate dune morphology variables. Guy, K.K. 20140602 USGS Data Series 839 Geographic Coverage: LA, MS https://pubs.usgs.gov/ds/0839/ Online digital data 20120905 20121011 The date when lidar surveys were collected. USGS DS839 LA 2012 A lidar survey that was used to estimate dune morphology variables. Quantum Spatial, Inc., United States Geological Survey (USGS) 20190329 Geographic Coverage: LA Chandeleurs, AL Dauphin Island, FL Gulf Islands ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/USGS_LPC_FL_GulfCoast_Topography_2018/ https://nationalmap.gov/viewer.html Online digital data 20181027 20181103 The date when lidar surveys were collected. USGS LA AL 2018 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) 20181108 Geographic Coverage: AL, MS Islands https://chs.coast.noaa.gov/htdata/lidar4_z/geoid18/data/8626/ https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8626 Online digital data 20181116 20181118 The date when lidar surveys were collected. USACE NCMP MS AL 2018 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://chs.coast.noaa.gov/htdata/lidar2_z/geoid18/data/8625/ 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. 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 NCMP Gulf Coast 2016 USGS LA 2017 USGS LA 2015 USGS DS839 LA 2012 USGS LA AL 2018 USACE NCMP MS AL 2018 USACE JALBTCX FL PH 2018 2021 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 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 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 GFS-WAVE 20210829 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 20210829 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 2531 0.01975663976 0.0249972312 Decimal Degrees D WGS 1984 WGS 1984 6378137.0 298.257223563 Ida_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 September 2012 to November 2018. USGS 0.59508 10.5247 meters -999 Null value USGS DLOW Elevation of the dune toe, in meters NAVD88. Extracted from lidar surveys collected from September 2012 to November 2018. USGS 0.70559 3.543 meters -999 Null value USGS DHIrms Root mean square error of dune crest elevation measurements . USGS 0.1158 1.7351 meters -999 Null value USGS DLOrms Root mean square error of dune toe elevation measurements . USGS 0.1352 0.9578 square meters -999 Null value USGS SURGE Storm surge water level. NOAA 0.396 3.5204 meters -999 Null value NOAA RUNUP Wave runup water level. USGS 0.013168 3.8988 meters -999 Null value USGS SETUP Wave setup water level. USGS 0.004846 1.5651 meters -999 Null value USGS PCOL Probability of collision. USGS 2.1376 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 0.4783 3.9504 meters -999 Null value USGS EXTREME Extreme water level (surge + runup). USGS 0.64948 5.3193 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/Ida_2021.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