Document Type



Virginia Institute of Marine Science

Publication Date



13th International Conference on Cohesive Sediment Transport Processes (INTERCOH), Leuven, Belgium


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 (< density < 1800kg/m3 ). 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.

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.