Change in salinity exposure of salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy

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What does this data set describe?

Title:
Change in salinity exposure of salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy
Abstract:
As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services. Edwin B. Forsythe National Wildlife Refuge (EBFNWR), New Jersey, was selected as a pilot study area.
As part of this data synthesis effort, hydrodynamic and sediment transport modeling of Barnegat Bay Little Egg Harbor (BBLEH) has been used to create the following wetland data layers in Edwin B. Forsythe National Wildlife Refuge (EBFNWR), New Jersey: 1) Hydrodynamic residence time , 2) salinity change and 3) salinity exposure change in wetlands, and 4) sediment supply to wetlands. The residence time layer was based on the hydrodynamic and particle tracking modeling of the period 3/1/2012 to 5/1/2012 by Defne and Ganju (2015). For this data layer, the residence time map of estuarine water has been projected over the EBFNWR salt marshes. The rest of the layers were derived from the BBLEH hydrodynamic modeling for the Hurricane Sandy period that spans from 10/27/2012 to 11/04/2012 (Defne and Ganju, 2016a). The model estimated changes in salinity and sediment concentrations over the salt marshes caused by storm-induced coastal flooding. The results are summarized over the previously determined conceptual salt marsh unit polygons (Defne and Ganju, 2016b).
  1. How might this data set be cited?
    Defne, Zafer, and Ganju, Neil K., 2017, Change in salinity exposure of salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy: data release DOI:10.5066/F7K64GZT, U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center, Woods Hole, MA.

    Online Links:

    This is part of the following larger work.

    Defne, Zafer, and Ganju, Neil K., 2017, Wetland data layers derived from Barnegat Bay Little Egg Harbor hydrodynamic model: data release DOI:10.5066/F7K64GZT, U.S. Geological Survey, Reston, Virginia.

    Online Links:

    Other_Citation_Details:
    Suggested citation: Defne, Zafer, and Ganju, N.K., 2017, Wetland data layers derived from Barnegat Bay Little Egg Harbor hydrodynamic model: U.S. Geological Survey data release, https://doi.org/10.5066/F7K64GZT.
  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -74.484623118
    East_Bounding_Coordinate: -74.051158122
    North_Bounding_Coordinate: 40.053798801
    South_Bounding_Coordinate: 39.435117592
  3. What does it look like?
    https://www.sciencebase.gov/catalog/file/get/59655223e4b0d1f9f05b3685?name=mu_SEC_EBFNWRp.png (PNG)
    Graphic that shows the change in salinity exposure during Hurricane Sandy in the EBFNWR salt marsh complex overlaying Esri Shaded World Relief Map.
  4. Does the data set describe conditions during a particular time period?
    Calendar_Date: 2017
    Currentness_Reference:
    publication date
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Vector Digital Data Set (Polygon)
  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):
      • G-polygon (1338)
    2. What coordinate system is used to represent geographic features?
      The map projection used is WGS 1984 Web Mercator Auxiliary Sphere (ESRI Full Name: WGS_1984_Web_Mercator_Auxiliary_Sphere).
      Projection parameters:
      Standard_Parallel: 0.0
      Longitude_of_Central_Meridian: 0.0
      False_Easting: 0.0
      False_Northing: 0.0
      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.6096
      Ordinates (y-coordinates) are specified to the nearest 0.6096
      Planar coordinates are specified in Meter
      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.
  7. How does the data set describe geographic features?
    mu_SEC_EBFNWRp
    Attribute information associated with the change in salinity exposure of the conceptual marsh units of EBFNWR salt marsh complex. (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.
    FID_CMU
    Sequential unique whole numbers that represents the identification number for each conceptual marsh units. (Source: USGS)
    Range of values
    Minimum:0
    Maximum:1337
    MEAN
    Change in depth-averaged salinity exposure in each marsh unit (Source: USGS)
    Range of values
    Minimum:0.253841012716293
    Maximum:114.945999145508
    Units:psu days
    Entity_and_Attribute_Overview:
    In this dataset, change in depth-averaged salinity exposure of salt marsh vegetation during hurricane Sandy is averaged over each conceptual marsh unit in EBFNWR. Change in salinity exposure is estimated based on the hydrodynamic modeling of Barnegat Bay - Little Egg Harbor (BBLEH) estuary from 10/27/2012 to 11/04/2012. Net change in salinity exposure is calculated by subtracting the depth-averaged salinity exposure in the water column during non-storm conditions from those during Hurricane Sandy. The salinity of sub-aerial regions during non-storm conditions is assumed to be zero. Decimal values in the attribute table are a result of double precision calculations while significant digits are considered in defining the attribute measurement resolutions. Therefore, the smallest unit increment for change in salinity exposure can be assumed to be a practical value such as 0.01 psu days.
    Entity_and_Attribute_Detail_Citation: U.S. Geological Survey

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Zafer Defne
    • Neil K. Ganju
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    U.S. Geological Survey
    Attn: Zafer Defne
    Ocean Scientist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2254 (voice)
    508-457-2310 (FAX)
    zdefne@usgs.gov

Why was the data set created?

This polygon dataset facilitates quantifying the changes in salinity exposure of vegetation in the EBFNWR salt marsh complex by summarizing the results over the previously determined conceptual salt marsh unit polygons (Defne and Ganju, 2016b). Analysis of episodic change in salinity exposure is part of a comprehensive assessment to identify the factors and their weights in determining the vulnerability and resiliency of salt marshes. Salinity exposure was defined as the depth-averaged salinity times the duration of exposure. Change in salinity exposure has been estimated based on the hydrodynamic modeling of Barnegat Bay - Little Egg Harbor (BBLEH) estuary during Hurricane Sandy period from 10/27/2012 to 11/04/2012 (Defne and Ganju, 2016a).

How was the data set created?

  1. From what previous works were the data drawn?
    marshUnitsEBFp.shp (source 1 of 1)
    Defne, Zafer, and Ganju, Neil K., 2016, Conceptual salt marsh units for wetland synthesis: Edwin B. Forsythe National Wildlife Refuge, New Jersey: data release DOI:10.5066/F7QV3JPG, U.S. Geological Survey, Reston, VA.

    Online Links:

    Type_of_Source_Media: Online
    Source_Contribution:
    Downloaded and used the features in [marshUnitsEBFp.shp] to summarize change in exposure to salinity at each marsh unit during a storm
  2. How were the data generated, processed, and modified?
    Date: 2017 (process 1 of 6)
    This process step used ArcMap (ver. 10.3.1) using tools from ArcToolbox. Names of specific tools used are given in CAPITAL letters (any critical parameters used is given in parentheses, separated by a semicolon, immediately after the tool name). Input and output file names are provided in [square brackets] when necessary. Units for length and area calculations are meters (m) and square meters (m2) unless otherwise stated.
    Defne and Ganju (2016a) modeled estuarine circulation in BBLEH during Hurricane Sandy period that spans from 10/27/2012 to 11/04/2012 with a three-dimensional hydrodynamic model. The computational domain included a part of Great Bay to the south and Manasquan Inlet to the north in addition to Barnegat Bay and Little Egg Harbor. Net changes in salinity exposure were calculated by subtracting the salinity exposure during non-storm conditions from those during Hurricane Sandy. The salinity of sub-aerial regions during non-storm conditions is assumed to be zero.
    Import hydrodynamic model output and project it to Web Mercator coordinate system, which is preferred projection for web services. Create a raster layer from it.. Create a raster layer from it.
    a) MAKE XY EVENT LAYER('XY table'= 'SEC.txt'; X field='lon'; Y field='lat'; Z field='val'; Layer name='SEC_WGS84.shp'; Spatial reference='GCS_WGS_1984')
    b) PROJECT(Input dataset='SEC_WGS84.shp'; Output dataset='SEC.shp'; Output coordinate system='WGS_1984_Web_Mercator_Auxiliary_Sphere')
    c) IDW.SpatialAnalyst(Input feature='SEC.shp'; Output Cell Size=100 meters; Power=2; Search Radius=Variable; Number of Points=12; Output raster='SEC.tif') with the Raster processing extent same as the extent of the marsh unit polygons [marshUnitsEBFp.shp]. Person who carried out this activity:
    U.S. Geological Survey
    Attn: Zafer Defne
    Ocean Scientist
    384 Woods Hole Rd.
    Woods Hole, MA
    USA

    508-548-8700 x2254 (voice)
    508-457-2310 (FAX)
    zdefne@usgs.gov
    Data sources used in this process:
    • marshUnitsEBFp.shp
    Data sources produced in this process:
    • SEC.shp
    • SEC.tif
    Date: 2017 (process 2 of 6)
    Some part of the EBFNWR salt marsh system to south of the Great Bay and upstream of Mullica River is not covered by the hydrodynamic model. The salinity exposure values for the marsh units in these areas are determined from the nearest marsh units with values using an inverse distance method. First, the marsh units are grouped into two depending on whether they are inside or outside of the computational domain.
    a) Select features from [marshUnitsEBFp.shp] marsh polygons that are within the BBLEH computational domain and export as [mu_with_data.shp].
    b) Invert selection and export polygons outside the computational domain as [mu_no_data.shp]. Data sources used in this process:
    • marshUnitsEBFp.shp
    Data sources produced in this process:
    • mu_with_data.shp
    • mu_no_data.shp
    Date: 2017 (process 3 of 6)
    Calculate the salinity exposure values for marsh units using the ZONALTABLE2FEAT tool. This tool calculates the statistics (e.g. the mean value) for each marsh unit polygon from the underlying raster layer. ZONALTABLE2FEAT(Raster layer='SEC.tif'; Zone features='mu_with_data.shp'; Zone field='FID_CMU'; Statistics type='MEAN'; Table name='mu1'; Output='mu_with_SEC.shp') to calculate the mean salinity exposure for each marsh unit within the BBLEH domain. During this process the table name 'mu1' is prefixed to field names for [mu_with_SEC.shp] (as opposed to 'mu0' for the interior polygons in the following steps). Data sources used in this process:
    • SEC.tif
    • mu_with_data.shp
    Data sources produced in this process:
    • mu_with_SEC.shp
    Date: 2017 (process 4 of 6)
    Create a raster layer from the interior polygons and use it to estimate values for exterior marsh units.
    a) FEATURE TO POINT(Input features='mu_with_SEC.shp'; 'Output features='mu_with_SEC_pts.shp').
    b) IDW.SpatialAnalyst(Input features='mu_with_SEC_pts.shp'; Output Cell Size=100 meters; Power=2; Search Radius=Variable; Number of Points=12; Output raster='mu_no_SEC.tif') with Raster analysis extent set to the same extent with [marshUnitsEBFp.shp].
    c) ZONALTABLE2FEAT(Raster layer='mu_no_SEC.tif'; Zone features='mu_no_data.shp'; Zone field='FID_CMU'; Statistics type='MEAN'; Table name='mu0'; Output='mu_no_SEC.shp') to calculate the mean salinity exposure for the exterior marsh units. During this process the table name 'mu0' is prefixed to field names for [mu_no_SEC.shp]. Data sources used in this process:
    • mu_with_SEC.shp
    • mu_no_data.shp
    Data sources produced in this process:
    • mu_no_SEC.shp
    Date: 2017 (process 5 of 6)
    a) MERGE the interior [mu_with_SEC.shp] and exterior [mu_no_SEC.shp] polygon features and calculate a new 'MEAN' field by adding the values of the mean values from two feature sets 'MEAN' = 'mu0_MEAN' + 'm1_MEAN'.
    b) During geoprocessing a few polygons smaller than the raster analysis resolution might get assigned "NoData" values. Replace the missing value with the value from the closest polygon.
    c) Edit the fields and field names for clarity and EXPORT to obtain the final feature dataset [mu_SEC_EBFNWRp.shp]. Data sources used in this process:
    • mu_with_SEC.shp
    • mu_no_SEC.shp
    Data sources produced in this process:
    • mu_SEC_EBFNWRp.shp
    Date: 07-Aug-2020 (process 6 of 6)
    Added keywords section with USGS persistent identifier as theme keyword. Person who carried out this activity:
    U.S. Geological Survey
    Attn: VeeAnn A. Cross
    Marine Geologist
    384 Woods Hole Road
    Woods Hole, MA

    508-548-8700 x2251 (voice)
    508-457-2310 (FAX)
    vatnipp@usgs.gov
  3. What similar or related data should the user be aware of?
    Defne, Zafer, and Ganju, Neil K., 2016, Conceptual salt marsh units for wetland synthesis: Edwin B. Forsythe National Wildlife Refuge, New Jersey: data release DOI:10.5066/F7QV3JPG, U.S. Geological Survey, Reston, Virginia.

    Online Links:

    Defne, Zafer, and Ganju, Neil K., 2016, Storm-induced geomorphological changes in a shallow, back-barrier estuary.

    Online Links:

    Other_Citation_Details:
    American Geophysical Union Ocean Sciences Meeting, New Orleans, LA, USA
    Defne, Zafer, and Ganju, Neil K., 2015, Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: application of hydrodynamic and particle tracking models: Estuaries and Coasts Volume 38, Springer US, New York, NY.

    Online Links:

    Other_Citation_Details: pages 1719-1734

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

  1. How well have the observations been checked?
    Water-land boundary and marsh unit boundaries inherit accuracy from the accuracy of source data - conceptual marsh units. Change in the salinity exposure dataset is calculated by resampling the hydrodynamic model output at a higher horizontal resolution of 0.0003 degrees (~30 meters) prior to averaging over each marsh unit.
  2. How accurate are the geographic locations?
    Horizontal accuracy for the polygon boundaries is inherited from the source layer, conceptual marsh units, and considered to be greater than ~3 meters. The point cloud used for calculating salinity change had variable horizontal resolution (~40 to ~300 meters) that was interpolated over a ~30-meter raster. The raster dataset was resampled at 3 meter resolution to enhance the conformity with the marsh unit boundaries prior to calculating zonal statistics.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    The polygon outlines for this dataset are defined by the conceptual marsh unit boundaries in the source dataset. That is the boundaries of the EBFNWR areas that include unvegetated and vegetated areas. A detailed on-the-ground analysis of a single site may result in a different interpretation of the wetland and marsh unit boundaries than established through this analysis.
  5. How consistent are the relationships among the observations, including topology?
    Simulated salinity ranges between fresh water and ocean water salinity in the computational domain. The simulated duration eight days. The maximum change in salinity exposure does not violate the maximum possible range.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints: None
Use_Constraints:
The change in salinity exposure values in this dataset are defined for scientific research purposes and should not be used as a sole source of reference for any regulations and policy making. Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey as the source of this information.
  1. Who distributes the data set? (Distributor 1 of 1)
    U.S. Geological Survey - ScienceBase
    Denver Federal Center, Building 810, Mail Stop 302
    Denver, CO

    1-888-275-8747 (voice)
    sciencebase@usgs.gov
  2. What's the catalog number I need to order this data set? mu_SEC_EBFNWRp.zip contains mu_SEC_EBFNWRp.shp (together with shapefile components, browse graphic, and associated FGDC CSDGM metadata in XML, TEXT, and HTML formats with the same file name).
  3. What legal disclaimers am I supposed to read?
    Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Not for navigational use.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 07-Aug-2020
Metadata author:
U.S. Geological Survey
Attn: Zafer Defne
Ocean Scientist
384 Woods Hole Road
Woods Hole, MA

508-548-8700 x2254 (voice)
508-457-2310 (FAX)
zdefne@usgs.gov
Metadata standard:
FGDC Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)

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