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The in situ acoustic measurement of seafloor sediment is an important technical means to obtain the acoustic parameters of seafloor. The time‐of‐flight method is commonly used to calculate the sound speed in seafloor sediment. Accurate identification of signal feature points is essential for determining travel time or travel time difference of acoustic signals. However, the precise identification of feature points, such as the take‐off point of the first wave of a sound wave signal, is challenging. The conventional manual identification method is inefficient and prone to errors. The development of a feature point auto‐identification method is imperative for accurately calculating the travel time of acoustic signals. In this study, we employed the cross‐correlation method, the level threshold method and the short window‐long window energy ratio method to extract the acoustic travel time differences and calculate the sound speeds in seawater and in seafloor sediment. We then analysed the effectiveness of these calculated results. The sound speeds in seawater obtained through the aforementioned methods were compared with the sound speeds measured using a sound velocity profiler. The comparison revealed that these processing methods exhibit a high level of accuracy. The sound speed results in sediments show that the programme‐based auto‐identification methods significantly reduce the standard deviation compared to the manual identification method. This study successfully assessed the processing accuracy of different methods and expanded the processing methods for in situ acoustic signals of seafloor sediments. [ABSTRACT FROM AUTHOR]

The Sulu orogenic belt, formed by the collision between Sino‐Korean and South China blocks, has important geological implications due to its unique tectonic setting. To understand the deep crustal structure of the extension of the Sulu orogenic belt in the Yellow Sea, we presented a 220‐km long active‐source ocean‐bottom seismometer wide‐angle reflection/refraction profile across the Yellow Sea. The obtained P‐wave velocity structure exhibits significant horizontal and vertical variations. The middle and upper crustal regions of the north beneath the survey line exhibit a higher velocity and larger thickness than those of the south, whereas the opposite is the case with the lower crust. The lower crustal high‐velocity zone in the Northern Depression of the South Yellow Sea Basin is a manifestation of the mantle material upwelling and accretion to the lower crust. Magmatic intrusions occurred along the faults and formed a high‐velocity zone in the middle and upper crusts. Due to undulating Moho interface and varying crustal velocities, the Qingdao–Rongcheng fault is identified as a fault in the Sulu orogenic belt without the significance of tectonic zoning. This study shows that the Sino‐Korean Block, Sulu orogenic belt and South China Block are bounded by the Jimo–Muping faults (an extension to the sea), Qianliyan fault and deep fault of the South Yellow Sea. Furthermore, the Sulu orogenic belt may have been formed by the northward subduction of the South China Block beneath the Sino‐Korean Block during the Indosinian orogeny to the east of the Shandong Peninsula. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Based on the data of the acoustic and physical properties of seafloor sediments obtained on the continental shelf area of the East China Sea (ECS), prediction equations of the sediment sound speed based on single and dual parameters were established, and the correlation of the sound speed with physical parameters was discussed. The results show that the sediment sound speed (c) is strongly correlated with water content (w), density (ρ), void ratio (e), mean grain size (Mz) and median grain size (Md), and the coefficient of determination R2 of the empirical regression equation is generally greater than 0.80, while the empirical regression equation coefficient of determination R2 of the compression coefficient (a) and compression modulus (E) are slightly lower, with 0.79 and 0.73, respectively. The coefficients of determination of the dual parameter regression equations between sediment sound speed with physical property parameters are generally higher than those of the single parameter equations, which are all higher than 0.90 indicating better prediction performance. The sensitivity of the physical parameters to the sound speed was analyzed, and the result shows that the sequence of sensitivity from high to low influence on sediment sound speed is void ratio, density, compressibility coefficient, median grain size and mean grain size. The prediction equations established in this study are a good extension and supplement to marine geoacoustic models and is of great significance for obtaining the acoustic properties of the seafloor sediments on the shelf of the East China Sea. [ABSTRACT FROM AUTHOR]

The acoustic properties of seafloor sediments have always been important parameters in sound field analyses and exploration for marine resources, and the accurate acquisition of the acoustic properties of sediments is one of the difficulties in the study of underwater acoustics. In this study, sediment cores were taken from the northern South China Sea, and the acoustic properties were analyzed. Since traditional methods (such as regression equations or theoretical models) are difficult to apply in practical engineering applications, we applied remote sensing data to sound velocity prediction models for the first time. Based on the influencing mechanism of the acoustic properties of seafloor sediments, the sediments' source, type and physical properties have a great influence on the acoustic properties. Therefore, we replaced these influencing factors with easily accessible data and remote sensing data, such as parameters of granularity, distance to the nearest coast, decadal average sea surface productivity, water depth, etc., using deep neural networks (DNN) to develop a sound velocity prediction model. Compared with traditional mathematical analyses, the DNN model improved the accuracy of prediction and can be applied to practical engineering applications. [ABSTRACT FROM AUTHOR]

Based on the data of the sound speed and the physical–mechanical properties of 300 seafloor sediment samples collected in the middle area of the Southern Yellow Sea, a backpropagation (BP) neural network algorithm is used herein to study the neural network topology and the corresponding neuron characteristic factors. A neural network model for predicting the sound speed of the seafloor sediment based on density, water content, porosity, void ratio, liquid limit, plastic limit, and clay content in the middle area of the Southern Yellow Sea is established. The results show that the sound speed prediction accuracy is the highest when the network model contains seven input layer neurons, ten hidden layer neurons, and one output node. According to the prediction results, the MAE(Mean Absolute Error) and the MAPE(Mean Absolute Percentage Error) are 13.19 m s−1 and 0.85%, respectively. The prediction results illustrate that the established BP neural network prediction method for the seafloor sediment sound speed is better than the traditional single, two and multi-parameter prediction equations. [ABSTRACT FROM AUTHOR]

To measure and characterize the roughness spectrum of sea-bottom, which is an important input parameter of the bottom acoustic backscattering model, an underwater laser three-dimensional (3D) scanning system for measuring seafloor microtopography has been developed successfully. The proposed underwater laser 3D scanning system can provide 3D seafloor microtopography with the resolution of millimeter levels in both horizontal and vertical directions and obtain the roughness spectrum of sea-bottom further. Two sets of data, which were suitable to model low- and mid-frequency acoustic backscattering at 6–24 kHz, were collected in two sites of sandy bottom during the acoustic scattering experiment in the southern Yellow Sea. The one-dimensional (1D) and two-dimensional (2D) roughness spectrum of the seafloor have been calculated at the two sites named S1 and S2, respectively. The result shows that calculated 2D spectral indices and spectral intensities, respectively, were 3.45 and 2.17 × 10−4 m4 at S1 and 3.33 and 4.66 × 10−4 m4 at S2. 2 D roughness spectrum parameters were used to model the acoustic scattering at S1, and the result indicates that the measurement results of the seafloor roughness spectrum is suitable for modeling bottom acoustic scattering. [ABSTRACT FROM AUTHOR]

Acoustic models are effective methods for inverting the geo-acoustic properties of seafloor sediments. To investigate the main sediment types in the northern South China Sea, 221 sediment core samples containing three sediment types (clayey silt, silty clay, muddy sand) were collected, and the geo-acoustic properties of the sediments were measured and analyzed. The results show that the same sediment type, shows different acoustic properties for different sedimentary environments. To verify the applications of different acoustic models, three acoustic models (the BS, EDFM and VGS model) were used to invert the sound velocities. It was observed that when porosity is less than about 0.75, the predicted velocity values from the three models are close to the measured values. As the porosity increases, the variation trend of VGS model is more in line with the measured data, while the BS and EDFM model has a relatively large error with the measured data.It seems that the VGS model, which incorporates the properties of both fluids and elastic solids, has a relatively broader scope of application. while the BS and EDFM models are susceptible to the porosity and particle size of the sediment. [ABSTRACT FROM AUTHOR]

This study evaluated the possibility of using Oocystis borgei to prevent and control harmful algae blooms. Firstly, Microcystis aeruginosa and O. borgei were co-cultured to assess the competition for nutrients between them. Different physiological and biochemical parameters, such as growth, cell membrane permeability and esterase activities were determined in exudate culture experiment to investigate allelopathic effects of O. borgei culture and mixed cultures (O. borgei and M. aeruginosa) at different growth phase on harmful microalgae (M. aeruginosa). Results showed that O. borgei could significantly inhibited M. aeruginosa when volume ratios were 4:1 and 1:1 (M. aeruginosa: O. borgei) in co-culture experiment. Further, it was found that the membrane system of M. aeruginosa was disintegrated by the culture filtrate of O. borgei at exponential phase. In addition, esterase activities and photorespiration were significantly inhibited. In conclusion, O. borgei exhibited different allelopathic effects at different growth phase. Its exponential phase showed a significant inhibitory effect, while no inhibitory effect was observed at the decline phase. [ABSTRACT FROM AUTHOR]

The shear wave characteristics of shallow seafloor sediment are vital to marine acoustic study and ocean engineering exploration. We analyzed the shear wave speed and the physical properties of the southern Yellow Sea sediment based on the Grain-Shearing (GS) model. The results show that: (1) The shear wave speed of the high-porosity sediment is lower than that of the low-porosity sediment; (2) The shear wave speed of the fine-grained sediment is lower than that of the coarse-grained sediment; (3) The burial depth of the sediment has a significant influence on the shear wave speed of the seafloor sediment. The GS model agrees well with the measurement data from the southern Yellow Sea. However, the quantitative analysis of the impact of input parameters on the GS model requires further research. [ABSTRACT FROM AUTHOR]

The high-frequency acoustic properties of seafloor sediments are very significant in seafloor study and underwater acoustic study field. In order to measure the sound speed and the attenuation for the small-scale sediment cores more accurately, this study developed a water coupled acoustic laboratory measurement system based on Richardson-Briggs technique. This method used the correlation comparison of waveforms received in sediment core and in identical reference tubes filled with water to measure sound speed and attenuation. The sound speed and attenuation of a clayey silt sediment sample were measured using the water coupled acoustic laboratory measurement system. This frequency dependence of the sound speed and attenuation showed that the clayey silt sediment has a weak positive sound speed dispersion, while the attenuation increases with a strong positive gradient within the measurement frequency range. This study also noted that the measured sound speed ratio match well with the empirical equations from literature. The measured attenuation factor data can fall in the Hamilton's empirical prediction range. [ABSTRACT FROM AUTHOR]