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Featured researches published by Kelsey Fall.


Estuaries and Coasts | 2016

Sediment Suspension and Deposition Across Restored Oyster Reefs of Varying Orientation to Flow: Implications for Restoration

Allison M. Colden; Kelsey Fall; Grace M. Cartwright; Carl T. Friedrichs

The eastern oyster, Crassostrea virginica, is a prominent ecosystem engineer, whose reefs exhibit strikingly consistent morphologies at multiple spatial scales throughout its North American range. These distinct morphologies are thought to form by interactions of nascent reef structures with hydrodynamics. We carried out two field studies to determine if historical reef configurations applied in a restoration context would improve reef persistence and restoration outcomes. We collected seabed and water column observations across constructed reefs of three orientations representative of those found historically throughout the oyster’s range: parallel or perpendicular to tidal currents or circular. Areas adjacent to reefs were sites of fine sediment trapping, with lower flow velocities, evidence of particle settling, and more fine sediments on the seabed relative to off-reef reference sites. The water column above the reef crest exhibited higher acoustic backscatter, higher flow velocities, and larger particles in suspension, consistent with local erosion of flocculated fine sediment from the reef crest. Perpendicular reefs produced conditions that were more conducive to reef persistence and improved oyster performance, including high flow velocities and enhanced resuspension of sediments from the reef, compared to parallel or circular reefs. Particle trapping in areas between reefs has the potential to inhibit reef growth between existing reef structures, providing support for hypotheses of landscape-scale reef pattern formation. Oyster reef restoration efforts can benefit from this improved understanding of biophysical interactions arising from reef orientation that contribute to sediment dynamics on constructed oyster reefs.


Archive | 2017

Fractal floc properties in estuarine surface waters: insights from video settling, LISST, and pump sampling

Kelsey Fall; Carl T. Friedrichs; Grace M. Massey; David Bowers

Two definitions of floc density are frequently used when characterizing floc properties: (1) excess density = Δρ, determined from floc diameter (df) and settling velocity, and (2) apparent density = ρa, determined from floc bulk volume and filtered samples of total suspended solids (TSS). If one assumes fractal flocs are aggregates composed of interstitial water combined with primary particles of diameter, dp, and density, ρp (which contain no water), and that a given fractal dimension and (F) and ρp yields a specific Δρ for a given df, a quantitative relationship between excess density (Δρ) and apparent density (ρa) can be used to estimate ρp and dp. Another key measure of sediment density is (3) the dry density of filtered solids = ρTSS, calculated from the TSS organic fraction, Forg. If a single population of fractal flocs dominates a suspension, it follows from fractal theory that ρp as estimated above should be nearly equal to ρTSS, and the consistency of ρp and ρTSS can be used as a check on the validity of the fractal assumption. This novel set of calculations was applied to observations of near-surface particle properties collected in the York River estuary in fall 2014, 2015 and 2016 using a profiling system equipped with a Laser In-Situ Scattering and Transmissometry (LISST) 100X, a high-definition Particle Imaging Camera System (PICS) incorporating a video settling tube, and a highspeed pump sampler. When fractal flocs were present (i.e. ρp ≈ ρTSS), suspensions with lower Forg were composed of smaller, denser primary particles. In contrast, suspensions with higher Forg (i.e., lower ρTSS) were composed of larger, less dense primary particles. Floc fractal dimension (F) did not show a very strong of a relationship with Forg, suggesting it may not be as important to constrain as dp and ρp when assuming a fractal model. Alternatively, when ρp was not consistent with ρTSS, it was concluded that simple fractal behavior could not describe the floc populations present.


Archive | 2016

Identification of suspended resilient pellets in particles tracked by a Particle Image Camera System (PICS) in a muddy estuary

Grace M. Massey; Kelsey Fall; Carl T. Friedrichs; S.J. Smith

Abstract The Particle Imaging Camera System (PICS) was designed to allow for the measurement of the settling velocity of individual particles in situ by using the smaller particles (<30 microns) to remove the affects of water velocity due to boat/water motion (Smith, 2010). Smith and Friedrichs (2011) took advantage of this system to identify the in situ size and settling velocities of cohesive flocs and suspended sediment aggregates in a trailing suction hopper dredge plume. They characterized the particles of each 30s video into three groups: flocs (density ≤ 1150kg/m), primary mineral particles (density ≥ 1800 kg/m) and bed aggregates (1150mg/m < density < 1800kg/m). This classification system, while adequate for suspended dredge plumes, needs to be revisited when the PICS is used in a muddy estuary, such as the York River Estuary, Virginia. Figure 1B shows the settling velocities of particles tracked within a video captured 2.5m from the surface in the Clay Bank region of the York River, plotted against their equivalent spherical diameters. While most of the particles are classified as flocs, as indicated by the blue dots in Figure 1C and the peak in the relative number of particles in Figure 1E, there is still a large number of particles classified as “bed aggregates” (red dots). This number of higher density particles may be unexpected, as this video was captured 4.25m over a “muddy bed” in a natural system with a flood current of 40cm/s. However, biologically compacted mud in the form of resilient pellets (see Figure 2) may be the answer. Bed sediments from five sediment cruises during this study period (Aug 2012 – Nov 2014) were found to be comprised of 86-96% mud (Figure 3A). However, 9-14% of the mud was packaged as resilient pellets (Figure 3B). Sediment captured 38cm above the bed by traps deployed on tripods were found to have 92-98% mud, with 4-14% of the mud packaged as resilient pellets (Figures 3A and B). Pellets isolated from the Apr to Jul 2014 trap were sampled with the PICS to determine the distribution of settling velocities (Ws), particle densities, and the ratio of the long and short axis of the particles. This will be used to identify the pellets in PICS videos captured during the five 6h anchor stations (black lines in Figure 3) where three depths were sampled each hour.


Archive | 2014

Cruise: YR130612, Stations: S5127- S5138, York River Estuary and Pamunkey River, Virginia, MUDBED Longitudinal Profiler Station Survey bracketing a Flood Tide.

Kelsey Fall; Grace M. Cartwright; Carl T. Friedrichs; David Bowers

During each station in the survey, while anchored, a profile time series was collected with a suite of instrumentation mounted on the CHSD profiler including: a YSI 6600 CTD, a Sequia LISST 100X, PICS floc camera system, a Nortek Vector, and a Sontek ADVOcean. The raw data of profile stations are processed to provide a smooth profile of data throughout the water column and a series of between 2 to 5 minute bursts from various heights in the water column. Total Suspended Solids (and fixed solids) were sampled from depth to calibrate the acoustic backscatter. Additional water samples were collected and analyzed for Chlorophyll A. Simultaneously, at each station, a burst was collected with a bow mounted, downward looking, RDI 1200 KHz ADCP. After each deployment of the profiler, a Trios RAMSES hyperspectral radiometer was deployed while drifting across the station location. The “logbook” is the hand written field notes and instrument setup documents. The “Profiler Set up” is a log of the location and serial number of the instruments mounted on the profiler. The “Consecutive Station Log” is an excel spreadsheet of the metadata associated with each station in the survey. Excel spreadsheet “Averaged Data” contains burst averaged data and statistics from the water column and bottom bursts. Raw and processed data from each instrument are zipped in a folder, or series of folders, identified by the type and serial number of the instrument. All times are Eastern Standard Time (EST).


Journal of Marine Science and Engineering | 2014

Model Behavior and Sensitivity in an Application of the Cohesive Bed Component of the Community Sediment Transport Modeling System for the York River Estuary, VA, USA

Kelsey Fall; Courtney K. Harris; Carl T. Friedrichs; J. Paul Rinehimer; Christopher R. Sherwood


Archive | 2013

Controls on particle settling velocity and bed erodibility in the presence of muddy flocs and pellets as inferred by ADVs, York River estuary, Virginia, USA

Kelsey Fall; Carl T. Friedrichs; Grace M. Cartwright


Archive | 2016

Relationships among estuarine floc size, optical properties, organic content, and settling velocity: insights gained from combining LISST and a particle imaging camera system

Kelsey Fall; Carl T. Friedrichs; Grace M. Cartwright; David Bowers


Archive | 2016

Influence of suspended particle properties on optical properties and resultant water clarity along a partially-mixed estuary, York River, Virginia, USA

Kelsey Fall; Carl T. Friedrichs; Grace M. Cartwright; David Bowers


Archive | 2016

Fractal floc size, density, settling velocity, and implications for water clarity in partially mixed-estuaries: The role of small, organic-rich particles

Kelsey Fall; Carl T. Friedrichs; Grace M. Massey; Jessie Turner


Archive | 2016

What controls bed erodibility in muddy, partially-mixed estuaries? Insights from the York River, Virginia

Carl T. Friedrichs; Grace M. Cartwright; Patrick J. Dickhudt; Kelsey Fall

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Grace M. Cartwright

Virginia Institute of Marine Science

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Courtney K. Harris

Virginia Institute of Marine Science

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Allison M. Colden

Virginia Institute of Marine Science

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Christopher R. Sherwood

Virginia Institute of Marine Science

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J. Paul Rinehimer

United States Geological Survey

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Malcolm E. Scully

Woods Hole Oceanographic Institution

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Patrick J. Dickhudt

United States Geological Survey

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William C. Boicourt

University of Maryland Center for Environmental Science

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