Abstract:
The influence of tropical and extratropical cyclones on coastal wetlands and marshes is highly variable in both space and time and depends on a number of climatic, geologic, and physical variables. The impacts storms can be either positive or negative with respect to the wetland and marsh ecosystems. Small to moderate amounts of inorganic sediment added during storms or other events helps to abate pressure from sea-level rise. However, if the volume of sediment is large and the resulting deposits thick, the organic substrate may compact causing submergence and a loss in elevation. Similarly, thick deposits of coarse inorganic sediment may also alter the hydrology of the site and impede vegetative processes. Alternative impacts associated with storms include shoreline erosion at the marsh edge as well as potential emergence. Predicting the outcome of these various responses and potential long-term implications can be obtained from a systematic assessment of both historical and recent event deposits. The objectives of this study are to 1) characterize the surficial sediment of the relict to recent washover fans and back-barrier marshes, and 2) characterize the sediment of 6 marsh cores from the back-barrier marshes and a single marsh island core near the mainland. These geologic data will be integrated with other remote sensing data collected along Assateague Island, Maryland / Virginia and assimilated into an assessment of coastal wetland response to storms.
Purpose:
The 14CTB_Grain-Size_Data.zip file includes Excel spreadsheets summarizing particle size analysis results from Assateague Island and the mainland of Maryland and Virginia, collected in March/April and October 2014 by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center.
Supplemental_Information:
Based upon visual inspection, samples with coarse material were dried at a constant 60°C. The dried samples were weighed and then dry-sieved through a number 18 (1000 microns [?m] or 1 mm) U.S. standard sieve, which meets the American Society for Testing and Materials (ASTM) E11 standard specifications for determining particle size using woven-wire test sieves. The two size fractions were weighed and bagged. Grain-size analyses were performed using a Coulter LS200 (
https://www.beckmancoulter.com/) particle-size analyzer, which uses laser diffraction to measure the size distribution of sediments ranging in size from 0.4 ?m to 2 mm (clay to very coarse-grained sand). In order to prevent shell fragments from damaging the LS200, particles greater than 1 mm in diameter were separated from all surface sediments (S) and marsh cores samples (M) prior to analysis using a number 18 U.S. standard sieve. If there was sediment > 1 mm, the material was dried and the dry weight was recorded. After the samples were washed through the sieve with filtered city water, a few milliliters of sodium hexametaphosphate solution was added to act as a deflocculant. The sediment slurry was sonicated with a wand sonicator for 30 – 60 seconds before being introduced into the Coulter LS200 to breakdown aggregated particles. The pre-sieved <1 mm dried overwash fan (W) fraction was introduced directly into the Coulter LS200. The raw grain-size data were processed with the free software program GRADISTAT ({Blott and Pye, 2001};
http://www.kpal.co.uk/gradistat), which calculates the mean, sorting, skewness, and kurtosis of each sample geometrically in metric units and logarithmically in phi units (?) ({Krumbein, 1934}) using the Folk and Ward ({Folk 1957}) method. GRADISTAT also calculates the fraction of sediment from each sample by size category (for example, clay, coarse silt, fine sand) based on a modified Wentworth ({Wentworth 1922}) size scale. A macro function in Microsoft Excel, developed by the USGS SPCMSC, was applied to the data to calculate average and standard deviation for each sample set (6 runs per sample), and highlight runs that varied from the set average by more than ± 1.5 standard deviations. Excessive deviations from the mean are likely the result of equipment error or extraneous organic material in the sample and are not considered representative of the sample. The highlighted runs were removed from the results and the sample average was recalculated using the remaining runs. The averaged results for all samples, including the number of runs included and the standard deviation of the averaged results were summarized in a series of Excel workbooks with tabs for each core location. These metadata are not complete with out the data dictionary (Grain_Size_Data_Dictionary.pdf) also included in this archive, which applies specifically to the summary statistics spreadsheets.
Theme:
Theme_Keyword_Thesaurus: USGS Metadata Identifier
Theme_Keyword: USGS:801c5ea4-41a6-4798-a25f-1c22ce4dcbca
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: marsh
Theme_Keyword: sediment
Theme_Keyword: subsurface
Theme_Keyword: grain size
Theme_Keyword: GRADISTAT
Theme_Keyword: mean
Theme_Keyword: sorting
Theme_Keyword: skewness
Theme_Keyword: kurtosis
Theme_Keyword: Folk and Ward
Theme_Keyword:
U.S. Geological Survey St. Petersburg Coastal and Marine Science Center
Theme_Keyword: U.S. Geological Survey
Theme_Keyword: USGS
Place:
Place_Keyword_Thesaurus: Geographic Names Information System (GNIS)
Place_Keyword: Maryland
Place_Keyword: Virginia
Place_Keyword: Assateague Island
The U.S. Geological Survey requests that it be acknowledged as the originator of this dataset in any future products or research derived from these data.
U.S. Geological Survey, Coastal and Marine Geology Program, St. Petersburg Coastal and Marine Science Center
Microsoft Windows Server 2008 R2 Version 6.1 (Build 7601XXXXX) Service Pack 1; Microsoft Excel Version 2010