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Base station data were post-processed through the National Geodetic Survey (NGS) On-Line Positioning User Service (OPUS). The time-weighted position calculated from all base station occupations did not differ significantly from the NPS REST control coordinates; therefore, the control coordinates were used for post-processing. The base-station coordinates were imported into GrafNav, version 8.5 (NovAtel Waypoint Product Group), and the data from the rover GPS were post-processed to the concurrent base-station session data. During GPS data acquisition at core location P25-C07, a recording error occurred, and no concurrent base-station data were recorded at REST. Rover data from this location were instead post-processed to the concurrent data recorded at the NGS Continuously Operating Reference Station (CORS) ZNY1 on Long Island. The final core locations, including elevation, are the post-processed DGPS coordinates; baseline distances to all core locations were 21 km or less. These data are included in the site locations files accessible from Bernier and others (2018).
Each vibracore was split lengthwise, photographed with a Canon Powershot SX20 IS digital camera, described macroscopically using standard sediment-logging methods, and subsampled for grain-size analysis. Grain-size samples consisted of 2-cm sections sampled at varying intervals down-core depending on the number and thickness of the observed sedimentologic units. The core logs and photographs can be downloaded from Bernier and others (2018). Textural descriptions for the core logs are based on macroscopic observations; the quantitative grain-size data are represented by down-core plots on the core logs (fig. 5).
Figure 5. Example grain-size plots and log from vibracore P22-C14. Sediment color is based on the Munsell soil color system. Colored lines with dates indicate depths where the core intersected previously surveyed beach surfaces (beach elevation profiles) (value plotted is Dcomp (m), in 2016-322-FA_ProfElev_to_CoreDepth.pdf, also see figs. 6, 7, and 8). [cm, centimeter; mm, millimeter][Click figure to enlarge]
Grain-size analyses were performed using a Coulter LS 13 320 particle-size analyzer, which uses laser diffraction to measure the size distribution of sediments ranging in size from 0.4 micron (μm) to 2 millimeters (mm) (clay to very coarse-grained sand). A total of 315 samples were analyzed from 14 vibracores. Prior to analysis, each sample was dried at 40 degrees Celsius (C) for 24 hours.
Two subsamples (sets) from each sample were processed (four runs per set) through the LS 13 320 particle-size analyzer, which measures the particle-size distribution of each sample by passing sediment suspended in solution between two narrow panes of glass in front of a laser. Light is scattered by the particles into characteristic refraction patterns measured by an array of photodetectors as intensity per unit area and recorded as relative volume for 92 size-related channels (bins). To prevent shell fragments and coarse material from damaging the LS 13 320, particles greater than 2 mm in diameter were separated from each subsample prior to analysis using a number 10 (2,000 μm [2 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 fraction of sediment greater than 2 mm was recorded as a percentage of the subsample dry weight.
The raw grain-size data were run through GRADISTAT, version 8 (Blott and Pye, 2001), which calculates the geometric (in metric units) and logarithmic (in phi units, φ; Krumbein, 1934) mean, sorting, skewness, and kurtosis of each sample, using the Folk and Ward (1957) method as well as the cumulative particle-size distribution. 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 (1922) size scale. A macro developed by the USGS was applied to calculate the average and standard deviation of each sample (four runs per set, eight runs per sample) and highlight runs that varied from the set or sample average by more than plus or minus () 1.5 standard deviations. Excessive deviations from the mean are likely the result of equipment error or extraneous material in the sample and, therefore, are not considered representative of the sample. Those runs were removed from the results, and the sample average was recalculated using the remaining runs. The grain-size data are included as down-core plots with the core logs (fig. 5); the individual run statistics as well as the averaged sample statistics (summary statistics) and graphical representations of the data are also available from Bernier and others (2018).
Vibracores were collected repeatedly along previously occupied beach-profile elevation transects (profiles 10, 11, 22, 25, 26, and 29; fig. 3; beach elevation profile data, see U.S. Geological Survey, undated). The depth at which each core penetrated older beach surfaces (fig. 6), if preserved, is labeled on the core logs (fig. 5 and Core Viewer). Not all previously surveyed beach surfaces are preserved in the cores because beach width and elevation vary seasonally and in response to storms (Hapke and others, 2013; Brenner and others, 2018). Erosion of beach sediments can be identified by comparing the beach elevation profiles at a given location: if the elevation of a younger (more recent) survey is less than that of an older survey, the beach surface represented by the older survey will not be preserved in the sedimentary record. Conversely, if beach elevations increase between survey dates, the sediments that accumulated between those surveys will be preserved, and chronostratigraphic depositional packages can be identified.
the depth (Duncomp) of each preserved beach surface was converted to the compacted core-depth framework (equivalent to depth in the core barrel, Dcomp) by multiplying by the percentage core compaction at that core location.
Figure 6. Example of plot showing vibracore intersecting previously surveyed beach elevation profiles. [m, meter; NAVD88, North American Vertical Datum of 1988] [Click figure to enlarge]
Figure 7. Illustration showing relations of core length, penetration, and compaction with calculations to translate beach elevation profiles to compacted depths of cores. [surf, surface; Dcomp, depth compacted; Duncomp, depth uncompacted; Z, elevation; L, core length; P, core penetration; %, percentage] [Click figure to enlarge]
You may be familiar with the classic GRADISTAT for calculating particle size statistics. It is a set of macros written into a Microsoft Excel spreadsheet by Kenneth Pye and Simon Blott. At the time of writing it was last updated for use with Microsoft Excel 2007, and is becoming increasingly difficult to use with newer versions of Excel. After recently troubleshooting some odd GRADISTAT outputs for one of our lab users, I decided to see if there were alternatives available.
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The fishing port covers an area of c. 0.35 km2 and encompasses several harbor infrastructure facilities (fishing, oil tanks, etc.), three main piers and artificial sand piles for tetrapod production (Figs. 1B, 2). The recreational Miss Veedol beach, protected by seawalls, is located south of the main port area. Outside the southern greater port area, the small Mikawame creek flows into the sea incising the forest and dunes.
Photographs and visual representation of all stratigraphic profiles from transect T8 (top) and T3 (bottom). Profiles show thinning inland (left to right) of the 2011 tsunami sand deposits as well as a change in composition (to organic material). The tsunami deposits are marked by a blue band in the background, while upper and lower contacts of the tsunami deposits are indicated by dashed white lines. Shown data has been plotted using Microsoft Excel 365 ( ) and is illustrated using Adobe Illustrator (Creative Cloud version 2020, ).
The stratigraphy of the Geoslicer profiles within the forest contains the former coastal dune sands overlaid by a humic soil developed by the forest. The dune sediments consist mainly of sand with varying coloration and corresponding content of silt or heavy minerals, as well as varying degrees of compactions and bioturbation (roots). Within or above the dark brown and organic-rich soil, a continuous sand layer laid by the 2011 Tohoku-oki tsunami contrasts trough sharp bottom contacts from the stratigraphy (Fig. 3). The stratigraphy reflects observations by Nakamura et al.20 north of the harbor area.
The sediment profiles located closest to the coast of transects T3 and T8 contrast each other significantly in the contribution of short-chained n-alkanes within their 2011 tsunami layer. In profiles MIS 37 to MIS 38 the tsunami layer has the significantly highest short-chained n-alkane concentration, only in MIS 40 where the sand deposit disappeared no strong indication of short-chained n-alkanes is visible. The terrigenous/aquatic ratio (TAR), an indicator to determine relative amounts of terrestrial versus aquatic n-alkanes in a sediment30, responds in relation to the total long-chained and short-chained n-alkane concentration. In most tsunami samples across both transects, the TAR can be used to differentiate the tsunami layer from the surrounding terrestrial sediments through a lower terrestrial and increased marine signal.
While the detection of the sandy tsunami deposits across the forest is straight forward based upon reports, field observations and analytical results, the detection of the woody and organic tsunami layer composed of eroded forest material and transported further inland than the sand layer is more complex. Even though Nakamura et al.20 described that the 2011 tsunami deposit was covered by leaves that have been stripped from trees by the seawater inundation, no further analyses or descriptions of this layer have been made. At first, this layer was not apparent, neither during field work, nor in the later acquired analytical data. The discovery of floatable plastic particles in MIS 17 embedded within this woody and organic material (Figs. 2D, 3), however, changed the interpretation as the brighter and finer organic layer must have obviously be the result of the inundating water masses inside the forest.
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