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Chris Bassett

Senior Mechanical Engineer





Research Interests

Passive noise studies, acoustic scattering, sea ice, marine renewable energy, fisheries acoustics, anthropogenic noise


Chris applies passive and active acoustic techniques to a variety of underwater applications. Some of his previous and ongoing studies include fisheries acoustics; high-frequency scattering from sea ice, crude oil, and physical oceanographic processes; measurements of anthropogenic noise; and ambient noise studies.

Department Affiliation

Ocean Engineering


B.S. Mechanical Engineering, University of Minnesota, 2007

M.S. Mechanical Engineering, University of Washington, 2010

Ph.D. Mechanical Engineering, University of Washington, 2013


Connecting to the Ocean's Power: Marine Energy Research at APL-UW

The U.S. Navy's support of the University of Washington, one of the nation's preeminent research universities, leverages APL-UW capabilities with university academic expertise to address a wide range of topics in marine energy through experimentation and evaluation in laboratory settings and field deployments of prototype systems.
Companion to the technical report, APL-UW TR 2301.

5 Jul 2023

Turbulence Generated by Tides in the Canal de Chacao, Chile

At a proposed tidal energy conversion site in southern Chile, APL-UW researchers are measuring the magnitude and scales of turbulence, both to aid in the design of turbines for the site and to understand the fundamental dynamics of flows through the channel.

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7 Mar 2013

Principal Investigator Jim Thomson chronicled all phases of the Chilean experiment through posts to the New York Times 'Scientist at Work' blog.

Sound Sounds: Listening to the Undersea Noise in Puget Sound

Doctoral student researcher Chris Bassett is analyzing a long time series of ambient noise data from Puget Sound. Vessel traffic is the most significant noise source, but breaking waves, precipitation, biology, and sediment moving on the seabed are other common underwater noise sources. The research is being pursued in conjunction with a program to assess the environmental impacts from a tidal energy conversion system placed on the seafloor.

13 Mar 2012


2000-present and while at APL-UW

Acoustic backscattering at a tidal intrusion front

Bassett, C., and 9 others including J. Thomson, "Acoustic backscattering at a tidal intrusion front," Prog. Oceanogr., EOR, doi:10.1016/j.pocean.2023.103167, 2023.

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8 Nov 2023

Strong spatial gradients and rapidly evolving, three-dimensional structure make estuarine fronts difficult to sample. Echosounders can be used near fronts to provide nearly synoptic images of water column processes and, with sufficient bandwidth, can provide quantitative information about dynamical variables derived from forward and inverse methods using acoustic backscattering measurements. This manuscript discusses measurements using broadband (50-420 kHz) echosounders from the James River (Virginia, USA) tidal intrusion front. The dominant backscattering mechanisms observed at the site include bubbles, turbulent microstructure, interfaces associated with stratification, suspended sediment, and biota. Existing analytical models are used to interpret contributions from these sources with acoustic inversions providing quantitative information about the physical structure and processes that compare favorably with conventional, in situ measurements. Supporting data sets for this analysis include measurements of temperature, salinity, velocity, and turbidity; X-band radar images of sea surface roughness; aerial optical imagery; Lagrangian measurements of waves, turbulence, and velocity structure; and Regional Ocean Modeling System circulation model simulations. A notable advantage of acoustic remote sensing is the ability to resolve processes at considerably higher spatial resolution (< 1 m horizontal; < 5 cm vertical) than other in situ sampling approaches.

Three-dimensional observations of tidal plume fronts in estuaries using a synthetic aperture sonar array

Marston, T.M., C. Bassett, D.S. Plotnick, A.N. Kidwell, and D.A. Honegger, "Three-dimensional observations of tidal plume fronts in estuaries using a synthetic aperture sonar array," J. Acoustic. Soc. Am., 154, 1124-1137, doi:10.1121/10.0020671
, 2023.

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22 Aug 2023

Synthetic aperture sonar (SAS) systems are designed to observe stationary scatterers located near the sediment interface. Less commonly, a SAS system may be used to observe scattering features located above the sonar in the water column. The Undersea Remote Sensing (USRS) project, sponsored by the Office of Naval Research, was a collaborative Directed Research Initiative (DRI) focused on studying dynamic estuarine water column features. During the USRS DRI, researchers from multiple institutions gathered to observe tidal features at various estuaries along the coast of the United States using both in situ and remote sensing techniques, including SAS. The first studied estuary was the mouth of the Connecticut River (CTR). Data captured by a SAS system deployed during a tidal event were post-processed to create three-dimensional observations of the structure of the leading edge of the CTR's ebb plume front. From these observations, lobed structures similar in scale to previously reported instabilities are revealed, with the present observations providing additional insight regarding the structure of the bubble distribution behind the front. Velocity estimates of plume features were also determined from SAS data and shown to compare favorably with concurrent marine radar estimates.

A Bayesian inverse approach to identify and quantify organisms from fisheries acoustic data

Urmy, S.S., A. De Robertis, and C. Bassett, "A Bayesian inverse approach to identify and quantify organisms from fisheries acoustic data," ICES J. Mar. Sci., EOR, doi:10.1093/icesjms/fsad102, 2023.

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7 Jul 2023

Identifying sound-scattering organisms is a perennial challenge in fisheries acoustics. Most practitioners classify backscatter based on direct sampling, frequency-difference thresholds, and expert judgement, then echo-integrate at a single frequency. However, this approach struggles with species mixtures, and discards multi-frequency information when integrating. Inversion methods do not have these limitations, but are not widely used because species identifications are often ambiguous and the algorithms are complicated to implement. We address these shortcomings using a probabilistic, Bayesian inversion method. Like other inversion methods, it handles species mixtures, uses all available frequencies, and extends naturally to broadband signals. Unlike previous approaches, it leverages Bayesian priors to rigorously incorporate information from direct sampling and biological knowledge, constraining the inversion and reducing ambiguity in species identification. Because it is probabilistic, a well-specified model should not produce solutions that are both wrong and confident. The model is based on physical scattering processes, so its output is fully interpretable, unlike some machine learning methods. Finally, the approach can be implemented using existing Bayesian libraries and is easily parallelized for large datasets. We present examples using simulations and field data from the Gulf of Alaska, and discuss possible applications and extensions of the method.

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Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center