The mechanical structure, the function modules, the working principles, and a sea trial of the newly developed ballast in situ sediment acoustic measurement system are reported in this study. The system relies on its own weight to insert transducers into seafloor sediments and can accurately measure the penetration depth using a specially designed mechanism. The system comprises of an underwater position monitoring and working status judgment module and has two operation modes: self-contained measurement and real-time visualization. The designed maximum working water depth of the system is 3,000 m, and the maximum measured depth of seafloor sediment is 0.8 m. The system has one transmitting transducer with the transmitting frequency band of 20–35 kHz and three receiving transducers. The in situ acoustic measurement system was tested at 15 stations in the northern South China Sea, and repeated measurements in seawater demonstrated good working performance. Comparison with predictions from empirical equations indicated that the measured speed of sound and attenuation fell within the predicted range and that the in situ measured data were reliable.

Based on the acoustic and physical data of typical seafloor sediment samples collected in the East China Sea, this study on the super parameter selection and contribution of the characteristic factors of the machine learning model for predicting the sound speed of seafloor sediments was conducted using the eXtreme gradient boosting (XGBoost) algorithm. An XGBoost model for predicting the sound speed of seafloor sediments was established based on five physical parameters: density ($\rho$), water content ($w$), void ratio ($e$), sand content (S), and average grain size (M_z). The results demonstrated that the model had the highest accuracy when n_estimator was 75 and max_depth was 5. The model training goodness of fit (R²) was as high as 0.92, and the mean absolute error and mean absolute percent error of the model prediction were 7.99 m/s and 0.51%, respectively. The results demonstrated that, in the study area, the XGBoost prediction method for the sound speed of seafloor sediments was superior to the traditional single- and two-parameter regressional equation prediction methods, with higher prediction accuracy, thus providing a new approach to predict the sound speed of seafloor sediments.

The acoustic characteristics of three fine-grained sediments (silty sand, silt, silty clay) in the South China Sea (SCS) were measured and analyzed at high frequency range of 27–247 kHz. The measurement results show that the sound speed dispersion is a positive linear relation at the measured frequency range, and the attenuation follows nonlinear frequency dependence, α = kfⁿ, where n ranges from 0.59 to 0.85 for the three different sediments in the SCS. The frequency dependence of sound speed and attenuation were compared with the published literature. It was found that for silty clay, clayey silt, silt, and silty sand, the dispersion characteristics of these four sediments are basically consistent; in general, the dispersion of coarse particles is significant, and that of fine particles is weak, and permeability is the key parameter that determines the inflection point of high frequency to low frequency. By modeling these sediments with the Biot–Stoll model, it was found that the Biot–Stoll model can better predict the frequency-dependent characteristics of sound attenuation in a high-frequency band under the matching constraints of sound speed dispersion characteristics, indicating that the Biot–Stoll model has good applicability to different types of sediments in a high-frequency band.

The acoustic properties of seafloor sediments on continental slopes play a crucial role in underwater acoustic propagation, communication, and detection. To investigate the acoustic characteristics and spatial distribution patterns of sediments on the continental slope, a geoacoustic experiment was conducted in the northwestern South China Sea. The experiment covered two sections: one crossing the shelf and slope in the downslope direction, and the other near the shelf break in the along-slope direction. In situ techniques, sediment sampling, and laboratory measurements were used to acquire data on sediment acoustic properties (such as sound speed and attenuation) and physical properties (including particle composition, density, porosity, and mean grain size). The experimental findings revealed several key points: (1) Acoustic properties of shallow water coarse-grained sediments and deep-sea sediments were higher when measured in the laboratory compared to in situ measurements. (2) Relationships between measured attenuation and physical properties, as well as between sound speed and mean grain size, showed deviations from previous empirical equations. (3) Sediment acoustic and physical properties exhibited significant variations in the downslope direction, while showing gradual variations in the along-slope direction. These variations can be attributed to sedimentary environmental factors such as material sources, hydrodynamic conditions, and water depth.

Based on multibeam bathymetric data and high-resolution shallow sub-bottom profiles acquired during China’s 10th Arctic Scientific Expedition Cruise in 2019, a sediment wave field was found on the western slope of the Chukchi Rise, in the Arctic Ocean. This sediment wave field developed on the lower slope with water depths of between 1200 m and 1800 m and stretched 15 km in the downslope direction. It comprised several parallel sediment waves, with wavelengths ranging from 700 m to 3400 m and wave heights from 12 m to 70 m. In the vertical direction, well-stratified deposits, tens of meters thick, were affected by sediment waves, which exhibit asymmetric waveforms and upslope migration trends. The morphological and seismostratigraphic characteristics of the sediment waves suggested their genesis as a result of the interaction between the bottom current and seafloor morphology, which was also supported by hydrographical data adjacent to the sediment wave field. It was infered that this bottom current was related to the Arctic Circumpolar Boundary Current, which many researchers suggest flows through the study area.