Measurement and Analysis of Acoustic Backscatter Value for Bottom Classification of waters Tidung Island

Sediment in a water has an important role for organisms, namely as a habitat, a place for foraging for food, and a place for spawning. These sediment can affect the composition of organisms in the water. The purpose of this study is to calculate the value of acoustic backscatter for the classification of the bottom of the water and to see the effect of sediment grain size on the backscatter value obtained from a single beam acoustic instrument. Data collection was carried out from 10 to 12 June 2021 in the water of Tidung Island, Seribu Islands, using the SIMRAD EK-15 single beam, single frequency 200 kHz instrument. Sediment sampling was carried out at 13 stations. The results showed that the waters of Tidung Island were dominated by muddy substrate which was classified based on the Surface Backscattering Strength (SS) value. Meanwhile, the grain size of the sediment affects the SVb value, where the large the grain size of the bottom sediment, the SVb value will be higher. The higher SVb value the SS value will be higher. Keywords: Bottom Classification, Acoustic Backscatter, Tidung Island

A Deep-sea Sediment Sampling System—Design, Analysis and Experimental Verification

In order to meet the needs of the deep seabed sediment airtight sampling operation of the whole sea depth manned submersible (operating water depth of 11,000 meters). An airtight sampler with the function of holding pressure and coring was designed. Firstly, Using the sediment sampling test platform, taking high sampling rate as the goal and the motion speed of manipulator as the constraint condition, the sediment sampling rate (ratio of the sample actually retrieved by the sampling tube to the insertion depth of the sampling tube) test under different sampling tube inner diameters was carried out, respectively. Then, the pressure drop calculation and analysis of other components such as pressure retaining cylinder and sealing cylinder during the recovery of airtight sampler to the deck are carried out, and the pressure drop compensation during the recovery of airtight sampler is calculated and analyzed based on the pressure compensator. At last, the internal pressure test, high-pressure cabin test and adaptability test between sampler and manipulator are carried out by using the developed prototype of airtight sampler for sediments in the deep sea. The test results verify the feasibility of the design of airtight sampler for sediments in the deep sea, which will provide strong support for the deep seabed sampling operation of manned submersible in the deep sea.

Statistical Modeling of Fine Sediments Dredged Using a Variable Area Dredging Suction Head to Improve Water Quality

The changing climate affects the agricultural lands, and, in turn, the changes in agricultural lands alter the watershed. A major concern regarding waterbodies is the increased sedimentation rates due to climate change. To improve the water quality, it is crucial to remove fine sediments. Using current environmental dredging methods is challenging because of the sediment volumes that must be dredged, the absence of nearby disposal sites, and the shoreline infrastructure at the dredging locations. To address these issues, we used a surgical dredging method with a variable area suction head that can easily maneuver around the docks, pilings, and other infrastructures. It can also isolate the fine grain material to better manage the dredged volumes in the seabed where nutrients are typically adhered. To this end, a statistical analysis of the dredged samples is essential to improve the design efficiency. In this work, we collected several samples using a variable area suction head with different design settings. The collected samples using each design setting were then used to model the distributions of the different grain sizes in the dredged sediments. The proposed statistical model can be effectively used for the prediction of sediment sampling outcomes to improve the gradation of the fine sediments.

A Novel Acoustic Sediment Classification Method Based on the K-Mdoids Algorithm Using Multibeam Echosounder Backscatter Intensity

The modern discrimination of sediment is based on acoustic intensity (backscatter) information from high-resolution multibeam echo-sounder systems (MBES). The backscattering intensity, varying with the angle of incidence, reveals the characteristics of seabed sediment. In this study, we propose a novel unsupervised acoustic sediment classification method based on the K-medoids algorithm using multibeam backscattering intensity data. In this method, we use the Lurton parameters model, which is the relationship between the backscattering intensity and incidence, to obtain the backscattering angle corresponding curve, and we use the genetic algorithm to fit the curve by the least-squares method. After extracting the four relevant parameters of the model when the ideal fitting effect was achieved, we input the characteristic parameters obtained from the fitting to the K-medoids clustering model. To validate the proposed classification method, we compare it with the self-organizing map (SOM) neural network classification method under the same parameter settings. The results of the experiment show that when the seabed sediment category is less than or equal to 3, the results of the K-medoids algorithm and the SOM neural network are approximately identical. As the sediment category increases, the SOM neural network shows instability, and it is impossible to see the clear boundaries of the seabed sediment, while the K-medoids category is 5 and the seabed sediment classification is correct. After comparing with field in situ seabed sediment sampling along the MBES survey line, the sediment classification method based on K-medoids is consistent with the distribution of the field sediment sampling. The classification accuracies for bedrock, sandy clay, and silty sand are all above 90%; those for gravel and clay are nearly 80%, and the overall accuracy reaches 89.7%.

Monitoring sediment transport and grain size dynamics along the Israeli continental shelf with multibeam bathymetry and backscatter data

<p>In 2017, the Israel Oceanographic and Limnological Research (IOLR) started an annual seafloor monitoring program. The aim of the program is to evaluate the rate of erosion/deposition and the influence of man-made infrastructures on the seabed along the Israeli continental shelf south of Akko. The survey program onboard R/V Bat-Galim includes a multibeam (Kongsberg EM2040), sub-bottom (Knudsen 3260 Chirp) mapping and box-core sediment sampling along 13 transects across the shelf, from WD 10-100 m. The multibeam was operated at 400-kHz yielding a horizontal resolution of 0.25-1.0 m (depending on water depth), and vertical uncertainty of several centimeters. Using the QPS FMGT software, both angular response curves (ARA) and 0.5 m horizontal resolution of Backscatter data (BS) were derived. The multibeam acoustic return intensities (BS) were locally calibrated at selected reference areas using in-situ sediment sampling. <br>The main source of sediments along the Israeli continental shelf is the Nile Delta which undergoes erosion since 1960 when the Aswan dam was constructed. Along the Israeli inner-shelf, these sediments are transported northward and westward by wind-derived currents and storms. The analysis of the bathymetric surfaces from the consecutive years 2017-2020 shows that the shelf is stable in terms of sediment processes except along the marine infrastructures and natural seafloor features (e.g. rocky bottom outcrops) where patterns of sediment accumulation and erosion are observed. The variability along the marine infrastructures is mostly seen in the shallow water (less than 30 m) where yearly changes of up to +/-0.4 m of sediment accumulation/erosion in the vertical axis were measured.<br>The locally calibrated multibeam BS enabled grain size mode evaluation ranging from very fine gravel (-1 phi) to clay (9 phi). Additional in-situ sampling validated the reliability of the grain size classification method for the Israeli, continental shelf. Accordingly, we show that the Israeli continental shelf south of Haifa Bay is characterized by a sandy seafloor strip at WD 0-35 m and a muddy strip that extends west up to WD 100 m (in agreement with previous studies). Gravelly areas are identified at the coast-parallel Kurkar outcrops (Calcareous sandstone rocky ridges or rock patches) in water depths of 10-15m and 35-40m and in some places even at WD of 90 m. This demonstrates that grain size classification by locally calibrated multibeam BS is likely to be a very useful and fast method for monitoring changes in seafloor characteristics over large areas over time.</p><p> </p>