Justin J. Birchler Margaret L. Palmsten Kara S. Doran 20260130 vector digital data Justin J. Birchler Margaret L. Palmsten Kara S. Doran 20260130 U.S. Geological Survey data release doi:10.5066/P148QCG4 St. Petersburg, Florida U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center https://doi.org/10.5066/P148QCG4 This dataset contains information on the probabilities of storm-induced erosion (collision, inundation and overwash) on sandy beaches along the U.S. Gulf coast of Texas, Louisiana, Mississippi, and Alabama during hurricane impact conditions of Hurricane Laura in August 2020. The analysis is based on a storm-impact scaling model that uses observations of dune morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to storm events. 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. Dune morphology observations (dune crest and toe elevation) were derived from topographic lidar (light detection and ranging) surveys. Hydrodynamic data were derived from the National Oceanic and Atmospheric Administration (NOAA) Nearshore Wave Prediction System model (wave setup and runup) and the NOAA Probabilistic Tropical Storm Surge model (storm surge). Storm surge exceedance levels of 10, 20, 30, 40, 50, and 90% were used; meaning that, for the 10% exceedance level, the storm surge would be expected to exceed the water level forecast in only 10% of locations, for example. The storm surge, mean and extreme water levels, and probabilities of collision, overwash, and inundation varied due to each storm surge exceedance level. Multiple similar variables are included in each data file for these parameters; the basic names are appended using the following format, ‘e10’ for the 10% exceedance level of storm surge. Data are provided for each NOAA National Hurricane Center (NHC) advisory during the study period for each storm. For further information regarding data collection and/or processing methods refer to Stockdon and others (2012). For further information regarding dune morphology observations refer to Doran and others (2017). To provide data on the probability of storm-induced coastal erosion hazards for the Texas, Louisiana, Mississippi, and Alabama coast for Hurricane Laura. The following websites provide background information on USGS research topics that pertain to the data contained herein; Forecasting Coastal Change, https://www.usgs.gov/programs/cmhrp/science/forecasting-coastal-change and Storm-Induced Coastal Change, https://www.usgs.gov/centers/spcmsc/science/storm-induced-coastal-change. 20200826 ground condition Complete None planned -95.802076 -87.249230 30.325986 28.670949 USGS Metadata Identifier USGS:70d6e1cd-0733-4dff-98d9-31860045ddd1 ISO 19115 Topic Category oceans elevation environment geoscientificInformation Global Change Master Science Directory (GCMD) EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION EARTH SCIENCE > OCEANS > COASTAL PROCESSES > BEACHES PROVIDERS > GOVERNMENT AGENCIES-U.S. FEDERAL AGENCIES > DOI > USGS > DOI/USGS/CMG/SP > ST. PETERSBURG COASTAL AND MARINE SCIENCE CENTER, COASTAL AND MARINE GEOLOGY, U.S. GEOLOGICAL SURVEY, U.S. DEPARTMENT OF THE INTERIOR USGS Thesaurus hazards marine geology ocean sciences coastal processes erosion hurricanes 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 None U.S. Geological Survey USGS St. Petersburg Coastal and Marine Science Center SPCMSC Coastal/Marine Hazards and Resources Program CMHRP coastal Hurricane Laura Common geographic areas United States Texas Louisiana Mississippi Alabama 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. U.S. Geological Survey Justin J. Birchler mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8019 727-502-8182 jbirchler@usgs.gov The predicted elevations of storm surge were extracted from the National Oceanic and Atmospheric Administration’s (NOAA) Probabilistic Tropical 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. Environment as of Metadata Creation: Microsoft Windows 11 23H2; MATLAB 2024a; Esri ArcGIS Pro 3.4.3 Stockdon, H.F. Doran, K.J. Thompson, D.M. Sopkin, K.L. Plant, N.G. Sallenger, A.H. 20120501 U.S. Geological Survey Open-File Report 2012–1084 Reston, VA U.S. Geological Survey https://doi.org/10.3133/ofr20121084 Doran, K.S. Long, J.W. Birchler, J.J. Brenner, O.T. Hardy, M.W. Morgan, K.L.M. Stockdon, H.F. Loubriel Torres, M. 20170805 7.0 U.S. Geological Survey data release doi:10.5066/F7GF0S0Z St. Petersburg, FL U.S. Geological Survey – St. Petersburg Coastal and Marine Science Center https://doi.org/10.5066/F7GF0S0Z 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 sections. Sections with greater than 75 percent of data missing were flagged with the invalid number of -999. 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 accuracy 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 20200826 https://slosh.nws.noaa.gov/psurge/index.php Online digital data 20200826 publication date P-Surge Storm surge model that was used to estimate surge-induced water levels at the shoreline within the next 80 hours. NOAA National Weather Service Environmental Modeling Center 20200826 https://polar.ncep.noaa.gov/nwps/para/viewer.shtml Online digital data 20200826 publication date NWPS Wave model that was used to estimate wave setup and runup conditions at the shoreline within the next 145 hours. Quantum Spatial, Inc., United States Geological Survey (USGS) 20191011 Geographic Coverage: South Texas (through Matagorda Island) https://www.fisheries.noaa.gov/inport/item/57941 Online digital data 20180113 20190223 ground condition USGS TX 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) 20170913 Geographic Coverage: TX https://www.fisheries.noaa.gov/inport/item/49738 Online digital data 20160723 20161010 ground condition 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://www.fisheries.noaa.gov/inport/item/53710 Online digital data 20170108 20170303 ground condition USGS LA 2017 A lidar survey that was used to estimate dune morphology variables. Digital Aerial Solutions, LLC, United States Geological Survey (USGS) 2020 Geographic Coverage: LA (South Terrebonne, Gulf, Chandeleur Islands) https://www.fisheries.noaa.gov/inport/item/73667 Online digital data 20150118 20150213 ground condition USGS LA 2015 A lidar survey that was used to estimate dune morphology variables. Guy, K.K. Doran, K.J. Stockdon, H.F. Plant, N.G. 20140602 U.S. Geological Survey Data Series 839 Geographic Coverage: LA (west coast islands) https://doi.org/10.3133/ds839 Online digital data 20120905 20121011 ground condition 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) https://www.fisheries.noaa.gov/inport/item/64345 Online digital data 20181027 20181103 ground condition USGS LA 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: MS Islands https://www.fisheries.noaa.gov/inport/item/55844 Online digital data 20181116 20181118 ground condition USACE NCMP MS 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) 20210316 Geographic Coverage: AL https://www.fisheries.noaa.gov/inport/item/64384/ Online digital data 20200922 20201013 ground condition USACE NCMP AL 2020 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 R2024a) 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 500-m 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. For further information regarding dune morphology observations see Doran and others (2017). USGS TX 2018 USACE NCMP Gulf Coast 2016 USGS LA 2017 USGS LA 2015 USGS DS839 LA 2012 USGS LA 2018 USACE NCMP MS 2018 USACE NCMP AL 2020 2020 Dune morphology (DHIGH, DLOW, DHIrms, DLOrms) U.S. Geological Survey Justin J. Birchler mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8019 727-502-8182 jbirchler@usgs.gov For hydrodynamic data: Water level was computed in MATLAB by adding storm surge (SURGE) from the NOAA Probabilistic Tropical Storm Surge (P-Surge) model (https://slosh.nws.noaa.gov/psurge/index.php) to wave setup (SETUP) and runup (RUNUP). The mean water level (MEAN) is the sum of storm surge (SURGE) and wave setup (SETUP). The extreme water level (EXTREME) is the sum of storm surge (SURGE) and wave runup (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/). Hydrodynamics names were appended with the exceedance value for storm surge, using the format 'e10' for the 10% exceedance level. Exceedance levels present in this data release are 10, 20, 30, 40, 50, and 90%. Hydrodynamic parameters were calculated in MATLAB and exported into ArcGIS shapefile (.shp) format. For details on modeling parameterization, see Stockdon and others (2012). P-Surge NWPS 20200826 Hydrodynamics (SURGE, SETUP, RUNUP, MEAN, EXTREME) U.S. Geological Survey Justin J. Birchler mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8019 727-502-8182 jbirchler@usgs.gov For probabilities of storm-induced erosion: 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 (MEAN) and extreme (EXTREME) water levels for each 500-m section, such that the probability of collision (PCOL) occurs when extreme water levels (EXTREME) reach the dune toe; overwash (POVW) when extreme water levels (EXTREME) reach the dune crest; and inundation (PIND) when mean water levels (MEAN) reach the dune crest. Probability variable names were appended with the exceedance value for storm surge, using the format 'e10' for the 10% exceedance level. Exceedance levels present in this data release are 10, 20, 30, 40, 50, and 90%. 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 (DHIGH, DLOW, DHIrms, DLOrms) Hydrodynamics (SURGE, SETUP, RUNUP, MEAN, EXTREME) 20200826 Probabilities (PCOL, POVW, PIND) Laura_2020082606_Adv26_PCOI_line.shp U.S. Geological Survey Justin J. Birchler mailing and physical

600 4th Street South

Saint Petersburg FL 33701 UNITED STATES 727-502-8019 727-502-8182 jbirchler@usgs.gov Vector String 2210 0.01975663976 0.0249972312 Decimal Degrees D WGS 1984 WGS 1984 6378137.0 298.257223563 North American Vertical Datum 1988 0.01 meters Attribute values Laura_2020082606_Adv26_PCOI_line.shp Shapefile of the probabilities of hurricane-induced coastal erosion, dune morphology, and hurricane hydrodynamic data for Hurricane Laura for NHC Advisory 26, August 26, 2020, 0600 Coordinated Universal Time (UTC). USGS FID Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Feature geometry. Esri Coordinates defining the features; Polyline. 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 October 2020. USGS 0.5761 8.5401 meters NAVD88 -999 Null value USGS DLOW Elevation of the dune toe, in meters NAVD88. Extracted from lidar surveys collected from September 2012 to October 2020. USGS 0.64449 3.1361 meters NAVD88 -999 Null value USGS DHIrms Root mean square error of dune crest elevation measurements. USGS 0.0121 3.1381 meters -999 Null value USGS DLOrms Root mean square error of dune toe elevation measurements. USGS 0.018318 0.970301 meters -999 Null value USGS RUNUP Wave runup water level. USGS 0.79963 5.7296 meters NAVD88 -999 Null value USGS SETUP Wave setup water level. USGS 0.024147 2.3195 meters NAVD88 -999 Null value USGS SURGEe10 Storm surge water level for probabilistic storm surge 10% exceedance value. NOAA 0.671 3.9345 meters NAVD88 -999 Null value NOAA PCOLe10 Probability of collision for probabilistic storm surge 10% exceedance value. USGS 12.832669 100 percent -999 Null value USGS POVWe10 Probability of overwash for probabilistic storm surge 10% exceedance value. USGS 0.000219 100 percent -999 Null value USGS PINDe10 Probability of inundation for probabilistic storm surge 10% exceedance value. USGS 0 100 percent -999 Null value USGS MEANe10 Mean water level (surge + setup) for probabilistic storm surge 10% exceedance value. USGS 0.76027 6.2338 meters NAVD88 -999 Null value USGS EXTREMEe10 Extreme water level (surge + runup) for probabilistic storm surge 10% exceedance value. USGS 1.5358 9.6439 meters NAVD88 -999 Null value USGS SURGEe20 Storm surge water level for probabilistic storm surge 20% exceedance value. NOAA 0.366 3.2937 meters NAVD88 -999 Null value NOAA PCOLe20 Probability of collision for probabilistic storm surge 20% exceedance value. USGS 6.48454 100 percent -999 Null value USGS POVWe20 Probability of overwash for probabilistic storm surge 20% exceedance value. USGS 6.60e-05 100 percent -999 Null value USGS PINDe20 Probability of inundation for probabilistic storm surge 20% exceedance value. USGS 0 100 percent -999 Null value USGS MEANe20 Mean water level (surge + setup) for probabilistic storm surge 20% exceedance value. USGS 0.48757 5.583 meters NAVD88 -999 Null value USGS EXTREMEe20 Extreme water level (surge + runup) for probabilistic storm surge 20% exceedance value. USGS 1.3786 8.9931 meters NAVD88 -999 Null value USGS SURGEe30 Storm surge water level for probabilistic storm surge 30% exceedance value. NOAA 0.366 2.8124 meters NAVD88 -999 Null value NOAA PCOLe30 Probability of collision for probabilistic storm surge 30% exceedance value. USGS 6.484551 100 percent -999 Null value USGS POVWe30 Probability of overwash for probabilistic storm surge 30% exceedance value. USGS 6.60e-05 100 percent -999 Null value USGS PINDe30 Probability of inundation for probabilistic storm surge 30% exceedance value. USGS 0 100 percent -999 Null value USGS MEANe30 Mean water level (surge + setup) for probabilistic storm surge 30% exceedance value. USGS 0.48757 5.1065 meters NAVD88 -999 Null value USGS EXTREMEe30 Extreme water level (surge + runup) for probabilistic storm surge 30% exceedance value. USGS 1.3786 8.5165 meters NAVD88 -999 Null value USGS SURGEe40 Storm surge water level for probabilistic storm surge 40% exceedance value. NOAA 0.36477 2.4062 meters NAVD88 -999 Null value NOAA PCOLe40 Probability of collision for probabilistic storm surge 40% exceedance value. USGS 6.484558 100 percent -999 Null value USGS POVWe40 Probability of overwash for probabilistic storm surge 40% exceedance value. USGS 6.60e-05 100 percent -999 Null value USGS PINDe40 Probability of inundation for probabilistic storm surge 40% exceedance value. USGS 0 99.999998 percent -999 Null value USGS MEANe40 Mean water level (surge + setup) for probabilistic storm surge 40% exceedance value. USGS 0.48757 4.7016 meters NAVD88 -999 Null value USGS EXTREMEe40 Extreme water level (surge + runup) for probabilistic storm surge 40% exceedance value. USGS 1.3786 8.1117 meters NAVD88 -999 Null value USGS SURGEe50 Storm surge water level for probabilistic storm surge 50% exceedance value. NOAA 0.36391 2.0401 meters NAVD88 -999 Null value NOAA PCOLe50 Probability of collision for probabilistic storm surge 50% exceedance value. USGS 6.484563 100 percent -999 Null value USGS POVWe50 Probability of overwash for probabilistic storm surge 50% exceedance value. USGS 6.60e-05 100 percent -999 Null value USGS PINDe50 Probability of inundation for probabilistic storm surge 50% exceedance value. USGS 0 99.999844 percent -999 Null value USGS MEANe50 Mean water level (surge + setup) for probabilistic storm surge 50% exceedance value. USGS 0.48757 4.3483 meters NAVD88 -999 Null value USGS EXTREMEe50 Extreme water level (surge + runup) for probabilistic storm surge 50% exceedance value. USGS 1.3786 7.7584 meters NAVD88 -999 Null value USGS SURGEe90 Storm surge water level for probabilistic storm surge 90% exceedance value. NOAA 0.363 1.054 meters NAVD88 -999 Null value NOAA PCOLe90 Probability of collision for probabilistic storm surge 90% exceedance value. USGS 6.484571 99.999981 percent -999 Null value USGS POVWe90 Probability of overwash for probabilistic storm surge 90% exceedance value. USGS 6.60e-05 99.999998 percent -999 Null value USGS PINDe90 Probability of inundation for probabilistic storm surge 90% exceedance value. USGS 0 99.312199 percent -999 Null value USGS MEANe90 Mean water level (surge + setup) for probabilistic storm surge 90% exceedance value. USGS 0.48757 3.3208 meters NAVD88 -999 Null value USGS EXTREMEe90 Extreme water level (surge + runup) for probabilistic storm surge 90% exceedance value. USGS 1.3786 6.7309 meters NAVD88 -999 Null value USGS 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 United States 727-502-8000 gs-g-spcmsc_data_inquiries@usgs.gov Laura_2020082606_Adv26_PCOI_line.shp 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-P148QCG4/data/Laura_2020082606_Adv26.zip None 20260129 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 United States 727-502-8000 gs-g-spcmsc_data_inquiries@usgs.gov Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time