Kathryn E.L. Smith
Joseph F. Terrano
20190430
Bathymetric Grid for a Wave Exposure Model of Grand Bay, Mississippi
raster digital data
U.S. Geological Survey Data Release
doi:10.5066/P9Z4ZPU3
St. Petersburg, Florida
U.S. Geological Survey
https://coastal.er.usgs.gov/data-release/doi-P9Z4ZPU3/data/Bathy_grid.zip
Kathryn E.L. Smith
Joseph F. Terrano
20190430
Wave Exposure Model for Grand Bay, Mississippi: Input and Validation Datasets
multimedia presentation
U.S. Geological Survey Data Release
doi:10.5066/P9Z4ZPU3
St. Petersburg, Florida
U.S. Geological Survey
https://doi.org/10.5066/P9Z4ZPU3
Coastal marshes are highly dynamic and ecologically important ecosystems that are subject to pervasive and often harmful disturbances, including shoreline erosion. Shoreline erosion can result in an overall loss of coastal marsh, particularly in estuaries with moderate- or high-wave energy. Not only can waves be important physical drivers of shoreline change they can also influence shore-proximal vertical accretion through sediment delivery. For these reasons, estimates of wave energy can provide a quantitative measure of wave effects on marsh shorelines. Since wave energy is difficult to measure at all locations, scientists and managers often rely on hydrodynamic models to estimate wave properties at different locations. The Wave Exposure Model (WEMo) is a simple tool that uses linear wave theory to estimate wave energy characteristics for enclosed and semi-enclosed estuaries (Malhotra and Fonseca, 2007). The interpretation of hydrodynamic models is improved if model results can be validated against measured data. The data presented in this publication are input and validation data for modeled and observed mean wave height for two temporary oceanographic stations established by the U.S. Geological Survey (USGS) in the Grand Bay National Estuarine Research Reserve, Mississippi.
The publication includes model input data (bathymetry, shorelines, and wind data) and values for both observed and modeled mean wave heights for 13 weeks from October 2016 to January 2017. The primary goal is to develop a model that examines the relationships between wave energy, shoreline erosion, and marsh sediment delivery and deposition.
Oceanographic and water quality measurements were collected in Grand Bay by the U.S. Geological Survey (USGS) from August 2016 to January 2017 under Field Activity Numbers (FAN) 2016-046-FA and 2017-006-FA. This data release only presents data from October 2016 to January 2017 for model validation purposes. For additional information see https://cmgds.marine.usgs.gov/fan_info.php?fan=2017-0406-FA. The bathymetric digital elevation model (DEM) was compiled through depth measurements obtained from multiple National Oceanic and Atmospheric Administration (NOAA) hydrographic surveys (H08647, H08648, H09118, F11621, H11620, and F00588) and single-beam bathymetry data collected by USGS under the FAN 2015-315-FA. For additional information see https://cmgds.marine.usgs.gov/fan_info.php?fan=2015-315-FA. Wind data were obtained from NOAA National Data Buoy (GDXM6) Crooked Bayou, Grand Bay Reserve, MS.
19610926
20150603
ground condition
As needed
-88.486411
-88.271674
30.407174
30.185720
USGS Metadata Identifier
USGS:58f4437b-24b1-4373-bd56-5f977628cd45
None
waves
oceanographic measurements
Wave Exposure Model (WEMo)
hydrodynamic modeling
USGS Thesaurus
coastal processes
ocean waves
hydrodynamics
bathymetry
digital elevation models
ISO 19115 Topic Category
oceans
environment
boundaries
geoscientificInformation
None
Grand Bay National Estuarine Research Reserve
Gulf of Mexico
USA
Mississippi
Alabama
MS
AL
None
Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. The U.S. Geological Survey requests to be acknowledged as originator of the data in future products or derivative research. This metadata record should be reviewed in its entirety to ensure data is used appropriately. Bathymetry data were developed exclusively for the development of a wave model and scientific research and should not be used for navigation purposes.
U.S. Geological Survey St Petersburg Coastal and Marine Science Center
Kathryn Smith
Research Ecologist
Mailing
600 4th Street South
St. Petersburg
Florida
33701
727-502-8073
727-502-8182
kelsmith@usgs.gov
Acknowledgment of the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center, as a data source would be appreciated in products developed from these data, and such acknowledgment as is standard for citation and legal practices. Sharing of new data layers developed directly from these data would also be appreciated by the U.S. Geological Survey staff. Users should be aware that comparisons with other datasets for the same area from other time periods may be inaccurate due to inconsistencies resulting from changes in photointerpretation, mapping conventions, and digital processes over time. These data are not legal documents and are not to be used as such.
Environment as of Metadata Creation: Microsoft Windows 10 Version 1709 (Build 16299.431); Esri ArcGIS 10.5.1 (Build 7333) Service Pack N/A (Build N/A)
Malhotra, A., and M.S. Fonseca
2007
WEMo (Wave Exposure Model): Formulation, Procedures and Validation
NOAA Technical Memorandum
NOS NCCOS #65
Beaufort, North Carolina
National Oceanic and Atmospheric Administration
Publication describing the wave model and parameterization
https://cdn.coastalscience.noaa.gov/page-attachments/products/WEMo/NOS_NCCOS_65.pdf
Nowacki, D.J., Suttles, S.E., Ganju, N.K., Montgomery, E.T. and Martini, M.A.
2018
Oceanographic and water quality measurements collected in Grand Bay, Alabama/Mississippi August 2016-January 2017
Woods Hole, Massachusetts
U.S. Geological Survey
Source of oceanographic data
https://doi.org/10.5066/P9UG9JYQ
No formal attribute accuracy tests were conducted.
Model and observed wave information were checked for completeness and accuracy.
Dataset is considered complete for the information presented. Some oceanographic data were not used as the full data record (August 4th, 2016 to January 26th, 2017) was longer than required for model validation. Users are advised to read the rest of the metadata record carefully for additional details.
A formal accuracy assessment of the horizontal positional information in the dataset has not been conducted. For additional information on data collection techniques see the source metadata.
A formal accuracy assessment of the vertical positional information in the dataset has not been conducted. For additional information on data collection techniques see the source metadata.
U.S. Geological Survey
2018
Oceanographic and water quality measurements collected in Grand Bay, Alabama/Mississippi - August 2016 - January 2017
NetCDF
Woods Hole, Massachusetts
U.S. Geological Survey
https://stellwagen.er.usgs.gov/grandbay.html
digital data
20161024
20170124
ground condition
RBR
Source of observed wave measurements
NOAA National Centers for Environmental Information
Unknown
Bathymetric Data Viewer
data portal
Unknown
National Oceanic and Atmospheric Administration
https://maps.ngdc.noaa.gov/viewers/bathymetry/
digital data
1962
1970
2006
2007
2010
ground condition
NGDC_bathy
Bathymetry for wave model
U.S. Geological Survey
20171201
Single-beam bathymetry data collected in 2015 from Grand Bay, Alabama-Mississippi
tabular digital data
St Petersburg, Florida
U.S. Geological Survey
https://doi.org/10.3133/ds1070
digital data
20150528
20150603
ground condition
USGS_bathy
Bathymetry for wave model
Grand Bay National Estuarine Research Reserve
Unknown
Grand Bay (GND) National Estuarine Research Reserve System-wide Monitoring Program: Crooked Bayou
tabular digital data
Columbia, South Carolina
Centralized Data Management Office
http://cdmo.baruch.sc.edu/get/realTime.cfm?stationCode=GNDCRMET
digital data
20161024
20170123
ground condition
GNDCRMET
Meteorological station provided wind speed and direction for wave model
U.S. Geological Survey
2018
A GIS Compilation of Vector Shorelines Derived from Aerial Imagery for the Grand Bay Region of Mississippi and Alabama: 2010 and 2012
vector digital data
St Petersburg, Florida
U.S. Geological Survey
https://doi.org/10.5066/F7VT1R8Q
digital data
20120909
ground condition
2012_shoreline
Shoreline used to create raster mask
Bathymetric data covering Grand Bay and Mississippi Sound were compiled and rasterized for wave model input. Data from hydrographic charts were downloaded from the NOAA Bathymetry Data Viewer. The following hydrographic surveys (with collection year) covered the study area: F00588 (2010), H11620 (2007), F11621 (2006), H09118 (1970), H08647 (1962), and H08648 (1962). In addition, the USGS single-beam bathymetry data collected in 2015 was included. The data were converted to a consistent tidal datum (Mean Lower Low Water (MLLW)) using Vdatum software (https://vdatum.noaa.gov/). Using latitude and longitude coordinates from each file, data were imported into ArcGIS (version 10.6) as shapefiles and merged into one file. Data were weighted based on date of survey, with recent surveys given a weight of 10 (2015 and 2010), recent past surveys a weight of 5 (2007 and 2006) and historical surveys a weight of 1 (1970 and 1962). Using the Inverse Distance Weighted tool in ArcGIS, a raster was created using the vertical elevation as the Z value input, a standard search radius of 50 to 100 nearest neighbors, and the weight field. The Focal Statistics tool was used to smooth the dataset using a circle radius of 20 cells. A raster mask was created by buffering the 2012 shoreline and enclosing the Grand Bay estuary and Mississippi Sound, out to the landward side of Petit Bois and Dauphin Islands.
NGDC_bathy
USGS_bathy
2012_shoreline
2018
bathy_grid
raster_mask
Kathryn Smith
Research Ecologist
mailing and physical
600 4th Street South
St.Petersburg
FL
33701
USA
727-502-8073
kelsmith@usgs.gov
Wind data for 2016 and 2017 were downloaded for the Crooked Bayou meteorological station from the National Estuarine Research Reserve's Centralized Data Management Office (CDMO). Using Excel (version 1803), the data for both years were appended. Wind speed was corrected for gauge height using the Power Law Method (described here: https://www.ndbc.noaa.gov/adjust_wind.shtml) and processed for model input using the WEMo Wind Analysis tool. WEMo calculates the wind speed and corresponding frequency for every 6.43 degrees (56 rays) angular resolution and is resampled or linearly interpolated for any other angular resolution. Wind frequency for a direction is defined as the ratio of the number of hours the wind blows from that direction and the total number of hours of wind data. Wind data for each week (beginning with October 24th, 2016 and ending on January 24th, 2017) are exported as representative wind energy (RWE) wind files for model input. Files were named "GB_wind_<start date>_<end date>_corr.Wind_RWE". RWE files are formatted specifically for WEMo input but can be viewed in any text editing software. For more information, see WEMo documentation (Malhotra and Fonseca 2007).
GNDCRMET
2018
RWE_wind
Kathryn Smith
Research Ecologist
mailing and physical
600 4th Street South
St.Petersburg
FL
33701
USA
727-502-8073
kelsmith@usgs.gov
Mean wave height was calculated for the same location as two USGS observational wave stations in Grand Bay. A shapefile of the station locations was created in ArcGIS by obtaining latitude and longitude coordinates from the KML file located on the data publication (Nowacki and others, 2018). Stations used in this study include 1078 and 1076. Several stations were excluded because they were either located within a river mouth and lack bathymetry data or adjacent to the shoreline and may be impacted by refractive waves. Wave height is estimated by the model through a series of wave propagation and dissipation steps, using the wind speed and direction data (RWE wind), along with depth (bathy grid) and shoreline (2012 shoreline). Wave generation equations are modified to account for limited fetch and wave dissipation factors that account for wave friction, shoaling and breaking due to shallow water. For details on model parameterization and calculations, see Malhotra and Fonseca (2007). Mean wave height for each weekly model run was populated in an Excel file.
RWE_wind
2012_shoreline
bathy_grid
2018
Mean_Hs
Kathryn Smith
Research Ecologist
mailing and physical
600 4th Street South
St.Petersburg
FL
33701
USA
727-502-8073
kelsmith@usgs.gov
Mean wave height was calculated from the observational wave data for two wave sensors. NetCDF datasets containing wave height data were downloaded from the data publication (Nowacki and others, 2018). Only data for the RBR virtuoso D|wave sensor at sites 1076 and 1078 was used (data file '10763Bdws-a.nc' and '10781Baqd-a.nc') because (1)the sensor provides the most accurate wave height data, (2) bathymetry data was available for those locations, and (3) the sensor is located far enough from the shoreline to reduce impact of refractive waves. The datasets were imported into R version 3.5.1 (https://www.r-project.org/about.html) and weekly mean wave height were calculated from observational measurements. Data was entered into the Excel spreadsheet containing modeled mean wave height. The Excel spreadsheet was exported as a non-proprietary, tab-delimited text file for publication purposes.
RBR
Mean_Hs
2018
Mean_Hs.txt
Kathryn Smith
Research Ecologist
mailing and physical
600 4th Street South
St.Petersburg
FL
33701
USA
727-502-8073
kelsmith@usgs.gov
Added keywords section with USGS persistent identifier as theme keyword.
20201013
U.S. Geological Survey
VeeAnn A. Cross
Marine Geologist
Mailing and Physical
384 Woods Hole Road
Woods Hole
MA
02543-1598
508-548-8700 x2251
508-457-2310
vatnipp@usgs.gov
Raster
Grid Cell
2430
2036
1
Universal Transverse Mercator
16
0.9996
-87.0
0.0
500000.0
0.0
row and column
10
10
meter
NAD83 North American Datum 1983
GRS 1980
6378137.0
298.257222101
MLLW
0.10
meter
Implicit coordinate
U.S. Geological Survey St Petersburg Coastal and Marine Science Center
Kathryn Smith
Research Ecologist
Mailing
600 4th Street South
St. Petersburg
FL
33701
727-502-8073
727-502-8182
kelsmith@usgs.gov
bathy_grid.img
This digital publication was prepared by an agency of the United States Government. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, nor shall the act of distribution imply any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and (or) contained herein. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.
ERDAS Imagine file
https://coastal.er.usgs.gov/data-release/doi-P9Z4ZPU3/data/bathy_grid.zip
None. No fees are applicable for obtaining the dataset.
The bathymetry grid is provided as a .img file, which is proprietary format; however, ERDAS Imagine files can be read and written by ArcGIS Desktop and other Esri applications. It is also supported by Safe Software's FME engine for format conversion and can be viewed in GeoViewer, freely downloadable from LizardTech. A free desktop viewer, ERDAS ER Viewer, is available from Hexagon Geospatial or ERDAS_IMG files.
20201013
U.S. Geological Survey St Petersburg Coastal and Marine Science Center
Kathryn Smith
Research Ecologist
Mailing
600 4th Street South
St. Petersburg
FL
33701
727-502-8073
727-502-8182
kelsmith@usgs.gov
Content Standard for Digital Geospatial Metadata
FGDC-STD-001-1998
local time