Hurricane Delta Assessment of Potential Coastal-Change Impacts: NHC Advisory 20, 09-Oct-2020 12:00:00

Frequently anticipated questions:

• What does this data set describe?
  1. How might this data set be cited?
  2. What geographic area does the data set cover?
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
  5. What is the general form of this data set?
  6. How does the data set represent geographic features?
  7. How does the data set describe geographic features?
• Who produced the data set?
  1. Who are the originators of the data set?
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
• Why was the data set created?
• How was the data set created?
  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
  3. What similar or related data should the user be aware of?
• How reliable are the data; what problems remain in the data set?
  1. How well have the observations been checked?
  2. How accurate are the geographic locations?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
  5. How consistent are the relationships among the data, including topology?
• How can someone get a copy of the data set?
  1. Are there legal restrictions on access or use of the data?
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  5. How can I download or order the data?
• Who wrote the metadata?

What does this data set describe?

1. How might this data set be cited?
   Birchler, Justin J., Palmsten, Margaret L., and Doran, Kara S., 20260130, Hurricane Delta Assessment of Potential Coastal-Change Impacts: NHC Advisory 20, 09-Oct-2020 12:00:00:.

   This is part of the following larger work.
   Birchler, Justin J., Palmsten, Margaret L., and Doran, Kara S., 20260130, Storm-Induced Coastal Change Forecasts: Louisiana Hurricanes Laura and Delta 2020: U.S. Geological Survey data release doi:10.5066/P148QCG4, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

   Online Links:

   • https://doi.org/10.5066/P148QCG4

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -96.001724
   East_Bounding_Coordinate: -87.499142
   North_Bounding_Coordinate: 30.283534
   South_Bounding_Coordinate: 28.588313
   

3. What does it look like?
4. Does the data set describe conditions during a particular time period?

   Calendar_Date: 09-Oct-2020

   Currentness_Reference:

   ground condition

5. What is the general form of this data set?

   Geospatial_Data_Presentation_Form: vector digital data
   

6. How does the data set represent geographic features?
   1. How are geographic features stored in the data set?
      This is a Vector data set. It contains the following vector data types (SDTS terminology):
      • String (2203)
   2. What coordinate system is used to represent geographic features?
      Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.01975663976. Longitudes are given to the nearest 0.0249972312. Latitude and longitude values are specified in Decimal Degrees. The horizontal datum used is D WGS 1984.
      The ellipsoid used is WGS 1984.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257223563.
      

      Vertical_Coordinate_System_Definition:

      Altitude_System_Definition:

      Altitude_Datum_Name: North American Vertical Datum 1988
      Altitude_Resolution: 0.01
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method: Attribute values
      

7. How does the data set describe geographic features?

   Delta_2020100912_Adv20_PCOI_line.shp

   Shapefile of the probabilities of hurricane-induced coastal erosion, dune morphology, and hurricane hydrodynamic data for Hurricane Delta for NHC Advisory 20, October 09, 2020, 1200 Coordinated Universal Time (UTC). (Source: USGS)

   FID

   Internal feature number. (Source: Esri) Sequential unique whole numbers that are automatically generated.

   Shape

   Feature geometry. (Source: 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. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.59721
   Maximum:	8.2126
   Units:	meters NAVD88

   DLOW

   Elevation of the dune toe, in meters NAVD88. Extracted from lidar surveys collected from September 2012 to October 2020. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.83586
   Maximum:	3.1017
   Units:	meters NAVD88

   DHIrms

   Root mean square error of dune crest elevation measurements. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.013283
   Maximum:	3.0719
   Units:	meters

   DLOrms

   Root mean square error of dune toe elevation measurements. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.0084761
   Maximum:	1.0162
   Units:	meters

   RUNUP

   Wave runup water level. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.46191
   Maximum:	5.1474
   Units:	meters NAVD88

   SETUP

   Wave setup water level. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.015782
   Maximum:	2.0782
   Units:	meters NAVD88

   SURGEe10

   Storm surge water level for probabilistic storm surge 10% exceedance value. (Source: NOAA)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.61
   Maximum:	3.0689
   Units:	meters NAVD88

   PCOLe10

   Probability of collision for probabilistic storm surge 10% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.539738
   Maximum:	100
   Units:	percent

   POVWe10

   Probability of overwash for probabilistic storm surge 10% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.0e-06
   Maximum:	100
   Units:	percent

   PINDe10

   Probability of inundation for probabilistic storm surge 10% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   MEANe10

   Mean water level (surge + setup) for probabilistic storm surge 10% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.69768
   Maximum:	4.9218
   Units:	meters NAVD88

   EXTREMEe10

   Extreme water level (surge + runup) for probabilistic storm surge 10% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.1561
   Maximum:	7.991
   Units:	meters NAVD88

   SURGEe20

   Storm surge water level for probabilistic storm surge 20% exceedance value. (Source: NOAA)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.549
   Maximum:	2.8707
   Units:	meters NAVD88

   PCOLe20

   Probability of collision for probabilistic storm surge 20% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.353035
   Maximum:	100
   Units:	percent

   POVWe20

   Probability of overwash for probabilistic storm surge 20% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   PINDe20

   Probability of inundation for probabilistic storm surge 20% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   MEANe20

   Mean water level (surge + setup) for probabilistic storm surge 20% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.65374
   Maximum:	4.6794
   Units:	meters NAVD88

   EXTREMEe20

   Extreme water level (surge + runup) for probabilistic storm surge 20% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.1337
   Maximum:	7.7486
   Units:	meters NAVD88

   SURGEe30

   Storm surge water level for probabilistic storm surge 30% exceedance value. (Source: NOAA)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.49525
   Maximum:	2.659
   Units:	meters NAVD88

   PCOLe30

   Probability of collision for probabilistic storm surge 30% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.219442
   Maximum:	100
   Units:	percent

   POVWe30

   Probability of overwash for probabilistic storm surge 30% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   PINDe30

   Probability of inundation for probabilistic storm surge 30% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	99.999999
   Units:	percent

   MEANe30

   Mean water level (surge + setup) for probabilistic storm surge 30% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.56089
   Maximum:	4.5574
   Units:	meters NAVD88

   EXTREMEe30

   Extreme water level (surge + runup) for probabilistic storm surge 30% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.0513
   Maximum:	7.6265
   Units:	meters NAVD88

   SURGEe40

   Storm surge water level for probabilistic storm surge 40% exceedance value. (Source: NOAA)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.49525
   Maximum:	2.5505
   Units:	meters NAVD88

   PCOLe40

   Probability of collision for probabilistic storm surge 40% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.219443
   Maximum:	100
   Units:	percent

   POVWe40

   Probability of overwash for probabilistic storm surge 40% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   PINDe40

   Probability of inundation for probabilistic storm surge 40% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	99.999995
   Units:	percent

   MEANe40

   Mean water level (surge + setup) for probabilistic storm surge 40% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.56089
   Maximum:	4.3479
   Units:	meters NAVD88

   EXTREMEe40

   Extreme water level (surge + runup) for probabilistic storm surge 40% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.0513
   Maximum:	7.4171
   Units:	meters NAVD88

   SURGEe50

   Storm surge water level for probabilistic storm surge 50% exceedance value. (Source: NOAA)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.49525
   Maximum:	2.448
   Units:	meters NAVD88

   PCOLe50

   Probability of collision for probabilistic storm surge 50% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.178024
   Maximum:	100
   Units:	percent

   POVWe50

   Probability of overwash for probabilistic storm surge 50% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	100
   Units:	percent

   PINDe50

   Probability of inundation for probabilistic storm surge 50% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	99.999958
   Units:	percent

   MEANe50

   Mean water level (surge + setup) for probabilistic storm surge 50% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.56089
   Maximum:	4.2404
   Units:	meters NAVD88

   EXTREMEe50

   Extreme water level (surge + runup) for probabilistic storm surge 50% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.0513
   Maximum:	7.3095
   Units:	meters NAVD88

   SURGEe90

   Storm surge water level for probabilistic storm surge 90% exceedance value. (Source: NOAA)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.49525
   Maximum:	1.8709
   Units:	meters NAVD88

   PCOLe90

   Probability of collision for probabilistic storm surge 90% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.896606
   Maximum:	99.999911
   Units:	percent

   POVWe90

   Probability of overwash for probabilistic storm surge 90% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	99.999999
   Units:	percent

   PINDe90

   Probability of inundation for probabilistic storm surge 90% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0
   Maximum:	99.980767
   Units:	percent

   MEANe90

   Mean water level (surge + setup) for probabilistic storm surge 90% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	0.56089
   Maximum:	3.4836
   Units:	meters NAVD88

   EXTREMEe90

   Extreme water level (surge + runup) for probabilistic storm surge 90% exceedance value. (Source: USGS)

   Value	Definition
   -999	Null value

   Range of values
   Minimum:	1.0409
   Maximum:	6.5528
   Units:	meters NAVD88

Who produced the data set?

1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
   • Justin J. Birchler
   • Margaret L. Palmsten
   • Kara S. Doran
2. Who also contributed to the data set?
   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.
3. To whom should users address questions about the data?
   U.S. Geological Survey

   Attn: Justin J. Birchler

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8019 (voice)

   727-502-8182 (FAX)

   jbirchler@usgs.gov

Why was the data set created?

How was the data set created?

1. From what previous works were the data drawn?

   P-Surge (source 1 of 10)

   National Hurricane Center, National Oceanic and Atmospheric Administration, 20201009, Probabilistic Tropical Storm Surge.

   Online Links:

   • https://slosh.nws.noaa.gov/psurge/index.php

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   Storm surge model that was used to estimate surge-induced water levels at the shoreline within the next 80 hours.

   NWPS (source 2 of 10)

   NOAA National Weather Service Environmental Modeling Center, 20201009, Nearshore Wave Prediction System.

   Online Links:

   • https://polar.ncep.noaa.gov/nwps/para/viewer.shtml

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   Wave model that was used to estimate wave setup and runup conditions at the shoreline within the next 145 hours.

   USGS TX 2018 (source 3 of 10)

   Quantum Spatial, Inc., United States Geological Survey (USGS), 20191011, 2018 USGS Lidar: South Texas.

   Online Links:

   • https://www.fisheries.noaa.gov/inport/item/57941

   Other_Citation_Details: Geographic Coverage: South Texas (through Matagorda Island)
   

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

   USACE NCMP Gulf Coast 2016 (source 4 of 10)

   United States Army Corps of Engineers (USACE), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX), 20170913, 2016 USACE NCMP Topobathy Lidar: Gulf Coast (AL, FL, MS, TX).

   Online Links:

   • https://www.fisheries.noaa.gov/inport/item/49738

   Other_Citation_Details: Geographic Coverage: TX
   

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

   USGS LA 2017 (source 5 of 10)

   Woolpert, Inc., United States Geological Survey (USGS), 20171212, 2017 USGS Lidar: Chenier Plain, LA.

   Online Links:

   • https://www.fisheries.noaa.gov/inport/item/53710

   Other_Citation_Details: Geographic Coverage: LA Chenier Plain
   

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

   USGS LA 2015 (source 6 of 10)

   Digital Aerial Solutions, LLC, United States Geological Survey (USGS), 2020, 2015 USGS Lidar: South Terrebonne and Gulf Islands, LA.

   Online Links:

   • https://www.fisheries.noaa.gov/inport/item/73667

   Other_Citation_Details:

   Geographic Coverage: LA (South Terrebonne, Gulf, Chandeleur Islands)

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

   USGS DS839 LA 2012 (source 7 of 10)

   Guy, K.K., Doran, K.J., Stockdon, H.F., and Plant, N.G., 20140602, Topographic Lidar Survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012: U.S. Geological Survey Data Series 839.

   Online Links:

   • https://doi.org/10.3133/ds839

   Other_Citation_Details: Geographic Coverage: LA (west coast islands)
   

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

   USGS LA 2018 (source 8 of 10)

   Quantum Spatial, Inc., United States Geological Survey (USGS), 20190329, 2018 USGS Topobathy Lidar: Gulf Coast Islands (AL, FL, LA).

   Online Links:

   • https://www.fisheries.noaa.gov/inport/item/64345

   Other_Citation_Details: Geographic Coverage: LA (Chandeleurs)
   

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

   USACE NCMP MS 2018 (source 9 of 10)

   U.S. Army Corps of Engineers (USACE), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX), 20181108, 2018 USACE NCMP Topobathy Lidar: Gulf Coast (AL, MS).

   Online Links:

   • https://www.fisheries.noaa.gov/inport/item/55844

   Other_Citation_Details: Geographic Coverage: MS Islands
   

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

   USACE NCMP AL 2020 (source 10 of 10)

   United States Army Corps of Engineers (USACE), Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX), 20210316, 2020 USACE NCMP Post Sally Topobathy Lidar: Gulf Coast (AL, FL, MS).

   Online Links:

   • https://www.fisheries.noaa.gov/inport/item/64384/

   Other_Citation_Details: Geographic Coverage: AL
   

   Type_of_Source_Media: Online digital data
   Source_Contribution:

   A lidar survey that was used to estimate dune morphology variables.

2. How were the data generated, processed, and modified?

   Date: 2020 (process 1 of 3)

   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). Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Justin J. Birchler

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8019 (voice)

   727-502-8182 (FAX)

   jbirchler@usgs.gov

   Data sources used in this process:

   • 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

   Data sources produced in this process:

   • Dune morphology (DHIGH, DLOW, DHIrms, DLOrms)

   Date: 09-Oct-2020 (process 2 of 3)

   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). Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Justin J. Birchler

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8019 (voice)

   727-502-8182 (FAX)

   jbirchler@usgs.gov

   Data sources used in this process:

   • P-Surge
   • NWPS

   Data sources produced in this process:

   • Hydrodynamics (SURGE, SETUP, RUNUP, MEAN, EXTREME)

   Date: 09-Oct-2020 (process 3 of 3)

   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). Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Justin J. Birchler

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8019 (voice)

   727-502-8182 (FAX)

   jbirchler@usgs.gov

   Data sources used in this process:

   • Dune morphology (DHIGH, DLOW, DHIrms, DLOrms)
   • Hydrodynamics (SURGE, SETUP, RUNUP, MEAN, EXTREME)

   Data sources produced in this process:

   • Probabilities (PCOL, POVW, PIND)
   • Delta_2020100912_Adv20_PCOI_line.shp

3. What similar or related data should the user be aware of?
   Stockdon, H.F., Doran, K.J., Thompson, D.M., Sopkin, K.L., Plant, N.G., and Sallenger, A.H., 20120501, National Assessment of Hurricane-Induced Coastal Erosion Hazards: Gulf of Mexico: U.S. Geological Survey Open-File Report 2012–1084, U.S. Geological Survey, Reston, VA.

   Online Links:

   • 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., and Loubriel Torres, M., 20170805, Lidar-derived Beach Morphology (Dune Crest, Dune Toe, and Shoreline) for U.S. Sandy Coastlines: U.S. Geological Survey data release doi:10.5066/F7GF0S0Z, U.S. Geological Survey – St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL.

   Online Links:

   • https://doi.org/10.5066/F7GF0S0Z

How reliable are the data; what problems remain in the data set?

1. How well have the observations been checked?
   
2. How accurate are the geographic locations?
   Horizontal accuracy was not estimated.
3. How accurate are the heights or depths?
   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.
4. Where are the gaps in the data? What is missing?
   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.
5. How consistent are the relationships among the observations, including topology?
   No additional checks for consistency were performed on this data.

How can someone get a copy of the data set?

1. Who distributes the data set? (Distributor 1 of 1)
   
   U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center

   Attn: USGS SPCMSC Data Management

   600 4th Street South

   Saint Petersburg, FL
   

   United States

   727-502-8000 (voice)

   gs-g-spcmsc_data_inquiries@usgs.gov
2. What's the catalog number I need to order this data set? Delta_2020100912_Adv20_PCOI_line.shp
3. What legal disclaimers am I supposed to read?
   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.
4. How can I download or order the data?
   • Availability in digital form:

     Data format:	shapefile
     Network links:	https://coastal.er.usgs.gov/data-release/doi-P148QCG4/data/Delta_2020100912_Adv20.zip

   • Cost to order the data: None

Who wrote the metadata?

Dates:

Last modified: 29-Jan-2026

Metadata author:

U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center

Attn: USGS SPCMSC Data Management

600 4th Street South

Saint Petersburg, FL

United States

727-502-8000 (voice)

gs-g-spcmsc_data_inquiries@usgs.gov

Metadata standard:

Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)