National Assessment of Hurricane-Induced Coastal Erosion Hazards: Puerto Rico

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?
  2. Who distributes the data?
  3. What's the catalog number I need to order this data set?
  4. What legal disclaimers am I supposed to read?
  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?
   Torres-Garcia, Legna M., Thompson, David M., Doran, Kara S., and Vargas-Babilonia, Priscilla, 20220815, National Assessment of Hurricane-Induced Coastal Erosion Hazards: Puerto Rico:.

   This is part of the following larger work.
   Doran, Kara S., Torres-Garcia, Legna M., Thompson, David M., Birchler, Justin J., Bendik, Kirsten J., Seymour, Alex C., Vargas-Babilonia, Priscilla, Storlazzi, Curt D., Buckley, Mark, and Palmsten, Margaret L., 20220815, National Assessment of Hurricane-Induced Coastal Erosion Hazards: Puerto Rico: U.S. Geological Survey data release doi:10.5066/P9N01XLQ, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

   Online Links:

   • https://doi.org/10.5066/P9N01XLQ

2. What geographic area does the data set cover?

   West_Bounding_Coordinate: -67.2710
   East_Bounding_Coordinate: -65.5896
   North_Bounding_Coordinate: 18.5160
   South_Bounding_Coordinate: 17.9269
   

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

   Calendar_Date: 15-Aug-2022

   Currentness_Reference:

   Publication date

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 (3325)
   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 0.0197699442. Longitudes are given to the nearest 0.0239719265. 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: 0.15
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method: Attribute values
      

7. How does the data set describe geographic features?

   PR_PCOI_line.shp

   Shapefile (.shp) containing the probabilities of hurricane-induced coastal erosion, dune morphology, and hurricane hydrodynamic data of Puerto Rico for category 1 through 5 storm scenarios. (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.

   DHIGH

   Elevation of dune crest or cliff top in meters, referenced to NAVD88. (Source: USGS)

   Range of values
   Minimum:	0.405438
   Maximum:	100.565053
   Units:	meters

   DLOW

   Elevation of the dune or cliff toe in meters, referenced to NAVD88. (Source: USGS)

   Value	Definition
   999	Null value

   Range of values
   Minimum:	0
   Maximum:	7.71334
   Units:	meters

   DHIrms

   Root mean squared error of dune crest or cliff top elevation measurements (square meters). (Source: USGS)

   Range of values
   Minimum:	0.021528
   Maximum:	27.465203
   Units:	square meters

   DLOrms

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

   Value	Definition
   999	Null value

   Range of values
   Minimum:	0
   Maximum:	2.776537
   Units:	square meters

   PCOL1

   Probability of collision from a category 1 storm (Source: USGS)

   Value	Definition
   999	Null value

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

   PCOL2

   Probability of collision from a category 2 storm (Source: USGS)

   Value	Definition
   999	Null value

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

   PCOL3

   Probability of collision from a category 3 storm (Source: USGS)

   Value	Definition
   999	Null value

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

   PCOL4

   Probability of collision from a category 4 storm (Source: USGS)

   Value	Definition
   999	Null value

   Range of values
   Minimum:	0.043041
   Maximum:	100
   Units:	percent

   PCOL5

   Probability of collision from a category 5 storm (Source: USGS)

   Value	Definition
   999	Null value

   Range of values
   Minimum:	54.723087
   Maximum:	100
   Units:	percent

   POVW1

   Probability of overwash from a category 1 storm (Source: USGS)

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

   POVW2

   Probability of overwash from a category 2 storm (Source: USGS)

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

   POVW3

   Probability of overwash from a category 3 storm (Source: USGS)

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

   POVW4

   Probability of overwash from a category 4 storm (Source: USGS)

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

   POVW5

   Probability of overwash from a category 5 storm (Source: USGS)

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

   PIND1

   Probability of inundation from a category 1 storm (Source: USGS)

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

   PIND2

   Probability of inundation from a category 2 storm (Source: USGS)

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

   PIND3

   Probability of inundation from a category 3 storm (Source: USGS)

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

   PIND4

   Probability of inundation from a category 4 storm (Source: USGS)

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

   PIND5

   Probability of inundation from a category 5 storm (Source: USGS)

   Range of values
   Minimum:	0.00
   Maximum:	100.00
   Units:	percent

   MEAN1

   Mean water level (Setup + Surge) for a category 1 storm (Source: USGS)

   Range of values
   Minimum:	0.373387
   Maximum:	3.747773
   Units:	meters

   MEAN2

   Mean water level (Setup + Surge) for a category 2 storm (Source: USGS)

   Range of values
   Minimum:	0.41675
   Maximum:	4.201769
   Units:	meters

   MEAN3

   Mean water level (Setup + Surge) for a category 3 storm (Source: USGS)

   Range of values
   Minimum:	0.64477
   Maximum:	4.996417
   Units:	meters

   MEAN4

   Mean water level (Setup + Surge) for a category 4 storm (Source: USGS)

   Range of values
   Minimum:	0.870202
   Maximum:	5.57431
   Units:	meters

   MEAN5

   Mean water level (Setup + Surge) for a category 5 storm (Source: USGS)

   Range of values
   Minimum:	1.139342
   Maximum:	6.069454
   Units:	meters

   EXTREME1

   Extreme water level (Runup + Surge) for a category 1 storm (Source: USGS)

   Range of values
   Minimum:	0.433844
   Maximum:	5.960094
   Units:	meters

   EXTREME2

   Extreme water level (Runup + Surge) for a category 2 storm (Source: USGS)

   Range of values
   Minimum:	0.614942
   Maximum:	9.370895
   Units:	meters

   EXTREME3

   Extreme water level (Runup + Surge) for a category 3 storm (Source: USGS)

   Range of values
   Minimum:	0.727493
   Maximum:	11.174338
   Units:	meters

   EXTREME4

   Extreme water level (Runup + Surge) for a category 4 storm (Source: USGS)

   Range of values
   Minimum:	1.015742
   Maximum:	13.113772
   Units:	meters

   EXTREME5

   Extreme water level (Runup + Surge) for a category 5 storm (Source: USGS)

   Range of values
   Minimum:	1.232767
   Maximum:	13.053943
   Units:	meters

Who produced the data set?

1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
   • Legna M. Torres-Garcia
   • David M. Thompson
   • Kara S. Doran
   • Priscilla Vargas-Babilonia
2. Who also contributed to the data set?
   The predicted elevations of combined high tide and storm surge for category 1-5 hurricanes were obtained from the Caribbean Coastal Ocean Observing System (CARICOOS) Storm Surge Atlas for Puerto Rico, a tightly-coupled hydrodynamic and wind wave model developed with the Advance Circulation Model (ADCIRC) and Simulating Waves Nearshore (SWAN) by Benitez-Menendez and Mercado-Irizarry (2015). The algorithm estimates the maximum storm surge elevation during hypothetical hurricane scenarios at each computational node of an unstructured mesh that covers the Caribbean Sea, extending between latitudes 9 degrees North to 24 degrees North and longitudes 72 degrees West to 58 degrees West, with a spacing of 14 m nearshore and 13 kilometers (km) in deep water. The data used represents the Maximum of the Maximum (MOM) storm surge elevations modeled, providing the expected worst-case surge during an extreme storm, assuming no sea level rise.
3. To whom should users address questions about the data?
   U.S. Geological Survey

   Attn: Legna M. Torres-Garcia

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8105 (voice)

   727-502-8182 (FAX)

   ltorresgarcia@usgs.gov

Why was the data set created?

How was the data set created?

1. From what previous works were the data drawn?

   Cliff top and toe (source 1 of 4)

   Bendik, Kirsten J., Seymour, Alexander C., and Doran, Kara S., 20210121, Coastal cliff top and toe delineation derived from lidar for Puerto Rico: 2018.

   Online Links:

   • https://doi.org/10.5066/F7610XCX

   Type_of_Source_Media: vector digital data
   Source_Contribution:

   Cliff top and toe delineation data derived from lidar for Puerto Rico in 2018 were summarized into 100-meter sections and used as inputs to generate cliff morphology (DHIGH, DLOW, DHIrms, DLOrms).

   MOM (source 2 of 4)

   Benitez-Menendez, Jose L., and Mercado-Irizarry, Aurelio, 2015, CARICOOS Storm Surge Atlas for Puerto Rico.

   Online Links:

   • https://www.caricoos.org/map/storm-surge?locale=en

   Type_of_Source_Media: digital data
   Source_Contribution:

   Maximum of Maximum (MOM) data provide a worst-case snapshot for a particular hurricane category under "perfect" storm conditions and was used to estimate water level under hurricane categories 1-5.

   XBeach (source 3 of 4)

   Deltares, 20201019, XBeach.

   Online Links:

   • https://oss.deltares.nl/web/xbeach

   Type_of_Source_Media: Computer program
   Source_Contribution:

   Model used to estimate wave setup and runup conditions for different hurricane categories.

   2018 USACE PR (source 4 of 4)

   US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center for Expertise (JALBTCX), 20180717, 2018 USACE FEMA Topobathy Lidar: Main Island, Culebra, and Vieques, Puerto Rico Point Cloud files with Orthometric Vertical Datum Puerto Rico Vertical Datum of 2002 (PRVD02) using GEOID18.

   Online Links:

   • https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8560/index.html

   Type_of_Source_Media: digital data
   Source_Contribution:

   A lidar survey of Puerto Rico that was used to estimate dune morphology variables (DHIGH, DLOW, DHIrms, DLOrms).

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

   Date: 2022 (process 1 of 4)

   For dune morphology data: Elevation data from lidar surveys (2018 USACE PR) were interpolated in MATLAB (R2021a) to a gridded domain that was rotated parallel to the shoreline and had a resolution of 10 meters in the long-shore 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 (dune crest and dune toe) were extracted from the elevation grid in MATLAB using methods described in Stockdon and others (2012). Dune morphology data were then summarized to 100-meter sections. Sections with greater than 75 percent of the data missing were flagged with the invalid number of 999. The 100-m smoothed dune crest (DHIGH), toe (DLOW) and root mean square (DHIrms, DLOrms) error for each section are then used to compute probabilities. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Kara S. Doran

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8117 (voice)

   727-502-8182 (FAX)

   kdoran@usgs.gov

   Data sources used in this process:

   • 2018 USACE PR

   Data sources produced in this process:

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

   Date: 2022 (process 2 of 4)

   The coastal cliff top and toe delineation data of Puerto Rico in 2018 from Bendik and others (2021) were summarized to 100-meter sections. Sections with greater than 75 percent of the data missing were flagged with the invalid number of 999. The 100-m smoothed cliff top (DHIGH), toe (DLOW) and root mean square (DHIrms, DLOrms) error for each section are then used to compute probabilities Areas with cliffs were interpolated separate from dunes to avoid averaging over multiple morphologies. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Kara S. Doran

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8117 (voice)

   727-502-8182 (FAX)

   kdoran@usgs.gov

   Data sources used in this process:

   • 2018 USACE PR
   • Cliff top and toe

   Data sources produced in this process:

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

   Date: 2022 (process 3 of 4)

   For hydrodynamic data: One dimensional XBeach models were set up around the island, spaced approximately 100 m apart. Inputs included the maximum of the maximum (MOM) significant wave heights and MOM storm surge values, along with variable bottom friction due to coral coverage. For each hurricane category, the XBeach models were run for 60 minutes. The last thirty-four minutes of each sixty-minute time series of runup computed by XBeach were analyzed to calculate wave setup and the 2% exceedance value of runup. Reading of the netCDF XBeach output files and subsequent calculations were done in MATLAB (R2021a). This resulted in the hydrodynamics (SURGE, SETUP, RUNUP), which was used an input for the next step. Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Kara S. Doran

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8117 (voice)

   727-502-8182 (FAX)

   kdoran@usgs.gov

   Data sources used in this process:

   • MOM
   • XBeach

   Data sources produced in this process:

   • Hydrodynamics (SURGE, SETUP, RUNUP)

   Date: 2011 (process 4 of 4)

   Probabilities of coastal erosion hazards are based on estimating the likelihood that the beach system will experience erosion and deposition patterns consistent with collision, overwash, or inundation regimes. The regimes were calculated by using values of dune and cliff morphology and mean and extreme water levels (hydrodynamics) for each 100-m section, such that probability of collision occurs when extreme water levels reach the dune or cliff toe; overwash when extreme water levels reach the dune crest or cliff top; and inundation when mean water levels reach the dune crest or cliff top. Probabilities were calculated in MATLAB (R2021a) and exported in ArcGIS shapefile (.shp) format using MATLAB shapewrite.m. This produced the probabilities of collision, overwash, inundation, mean water level and extreme water level data for category 1 through 5 hurricanes, found in the final shapefile (PR_PCOI_line.shp). For details on modeling parameterization, refer to the methods in Stockdon and others (2012). Person who carried out this activity:
   

   U.S. Geological Survey

   Attn: Kara S. Doran

   600 4th Street South

   Saint Petersburg, FL
   

   UNITED STATES

   727-502-8117 (voice)

   727-502-8182 (FAX)

   kdoran@usgs.gov

   Data sources used in this process:

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

   Data sources produced in this process:

   • PR_PCOI_line.shp

3. What similar or related data should the user be aware of?
   Stockdon, Hilary F., Doran, Kara J., Thompson, David M., Sopkin, Kristin L., Plant, Nathaniel G., and Sallenger, Asbury H., 2012, National assessment of hurricane-induced coastal erosion hazards-Gulf of Mexico: U.S. Geological Survey Open-File Report doi:10.3133/ofr20121084, U.S. Geological Survey, Reston, Virginia.

   Online Links:

   • https://doi.org/10.3133/ofr20121084

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 of the lidar digital elevation model (DEM) is 1 meter. The nearshore ADCIRC model grid resolution is 14 m, and each Xbeach transect with accompanying morphology is approximately 100 m apart in the alongshore direction. Data are referenced to the World Geodetic System of 1984 (WGS84) coordinate system.
3. How accurate are the heights or depths?
   Vertical accuracy for hydrodynamic measurements (surge, setup, and runup) is dependent on input data. No quantitative comparisons have been made, but qualitative storm surge model predictions match well with the observations. The significant wave height predictions, although in phase with the observations in that the time occurrence of the peaks match, the model predictions tend to be much larger than the measurements. No other accuracy checks were performed. Vertical accuracy for dune and cliff morphology (dune and cliff crest and toe elevation) data is dependent on the positional accuracy of the lidar data. Estimated accuracy of lidar surveys are +/- 15 centimeters (cm). 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) and the accuracy of the Global Positioning System (GPS) and aircraft-attitude measurements. Data are referenced to the North American Vertical Datum of 1988 (NAVD88) coordinate system.
4. Where are the gaps in the data? What is missing?
   These data include dune and cliff morphology, along with hurricane hydrodynamic data used to generate probabilities of hurricane-induced erosion. Elevation data from lidar surveys were not included. Measurements were collected approximately every 10-m and summarized to 100-m segments.
5. How consistent are the relationships among the observations, including topology?
   Data gaps exist for coastlines in Puerto Rico without sandy beaches or rocky cliffs (such as mangroves or river deltas) where elevation metrics do not exist. In addition, gaps may be present where the modeled total water level was determined to be invalid by the analyst. 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

   Attn: Kara S. Doran

   600 4th Street South

   Saint Petersburg, FL
   

   727-502-8117 (voice)

   727-502-8182 (FAX)

   kdoran@usgs.gov

   Contact_Instructions: All of this report is available online.
   

2. What's the catalog number I need to order this data set?
3. What legal disclaimers am I supposed to read?
   Although these data have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. The USGS shall not be held liable for improper or incorrect use of the data described and/or contained herein. 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-P9N01XLQ/data/PR_PCOI_line.zip

   • Cost to order the data: None, if obtained online.

Who wrote the metadata?

Dates:

Last modified: 15-Aug-2022

Metadata author:

U.S. Geological Survey

Attn: Kara S. Doran

600 4th Street South

Saint Petersburg, FL

UNITED STATES

727-502-8117 (voice)

727-502-8182 (FAX)

kdoran@usgs.gov

Metadata standard:

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