Sea Surface Height Measurements Based on Multi-Antenna GNSS Buoys.

Sea level monitoring is an essential foundational project for studying global climate change and the rise in sea levels. Satellite radar altimeters, which can sometimes provide inaccurate sea surface height data near the coast, are affected by both the instrument itself and geophysical factors. Buoys equipped with GNSS receivers offer a relatively flexible deployment at sea, allowing for long-term, high-precision measurements of sea surface heights. When operating at sea, GNSS buoys undergo complex movements with multiple degrees of freedom. Attitude measurements are a crucial source of information for understanding the motion state of the buoy at sea, which is related to the buoy's stability and reliability during its development. In this study, we designed and deployed a four-antenna GNSS buoy with both position and attitude measurement capabilities near Jimiya Wharf in Qingdao, China, to conduct offshore sea surface monitoring activities. The GNSS data were processed using the Precise Point Positioning (PPK) method to obtain a time series of sea surface heights, and the accuracy was evaluated using synchronous observation data from a small sea surface height radar. The difference between the GNSS buoy and the full-time radar was calculated, resulting in a root-mean-square error (RMSE) of 1.15 cm. Concurrently, the attitude of the GNSS buoy was calculated using multi-antenna technology, and the vertical elevation of the GNSS buoy antenna was corrected using the obtained attitude data. The RMSE between the corrected GNSS buoy data and the high ground radar was 1.12 cm, indicating that the four-antenna GNSS buoy can not only acquire high-precision coastal sea level data but also achieve synchronous measurement of the buoy's attitude. Furthermore, the data accuracy was also improved after the sea level attitude correction.

Analysis of the Effect of Base Station Motion on Underwater Handovers for Base-Station-Based Underwater Wireless Acoustic Networks.

In base-station-based underwater wireless acoustic networks (B-UWANs), effective handover mechanisms are necessary to ensure seamless data services for mobile nodes such as autonomous underwater vehicles (AUVs). Unlike terrestrial base stations (BSs), moored buoy BSs in B-UWANs experience motion responses due to wave loads under environmental conditions, posing unique challenges to the handover process. This study examines how BS motion affects handover decision errors, which arise when AUVs incorrectly initiate handovers to unintended BSs due to BS motion. By utilizing the AUV-BS distance as a handover triggering parameter, our analysis reveals a significant increase in decision errors within the overlapping regions when both the current and target BSs are in motion, especially when moving in the same direction. In addition, these errors intensify with the magnitude of BS motion and are exacerbated by smaller BS network radii. Based on these simulation results, we present an analytical framework that not only measures the influence of BS motion on the AUV-BS distance but also provides strategic insights for refining underwater handover protocols, thereby enhancing operational reliability and service continuity in B-UWANs.

A Rust Extraction and Evaluation Method for Navigation Buoys Based on Improved U-Net and Hue, Saturation, and Value.

Abnormalities of navigation buoys include tilting, rusting, breaking, etc. Realizing automatic extraction and evaluation of rust on buoys is of great significance for maritime supervision. Severe rust may cause damage to the buoy itself. Therefore, a lightweight method based on machine vision is proposed for extracting and evaluating the rust of the buoy. The method integrates image segmentation and processing. Firstly, image segmentation technology is used to extract the metal part of the buoy based on an improved U-Net. Secondly, the RGB image is converted into an HSV image by preprocessing, and the transformation law of HSV channel color value is analyzed to obtain the best segmentation threshold and then the pixels of the rusted and the metal parts can be extracted. Finally, the rust ratio of the buoy is calculated to evaluate the rust level of the buoy. Results show that both the segmentation precision and recall are above 0.95, and the accuracy is nearly 1.00. Compared with the rust evaluation algorithm directly using the image processing method, the accuracy and processing speed of rust grade evaluation are greatly improved.

Positioning of Unmanned Underwater Vehicle Based on Autonomous Tracking Buoy.

This paper presents a novel method for the dynamic positioning of an unmanned underwater vehicle (UUV) with unknown trajectories based on an autonomous tracking buoy (PUVV-ATB) that indirectly positions the UUV using ultra-short baseline measurements. The method employs a spatial location geometric model and divides the positioning process into four steps, including data preprocessing to detect geometric errors and apply mean filtering, direction capture, position tracking, and position synchronization. To achieve these steps, a new adaptive tracking control algorithm is proposed that does not require trajectory prediction and is applied to the last three steps. The algorithm is deployed to the buoy for tracking simulation and sea trial experiments, and the results are compared with those of a model predictive control algorithm. The autonomous tracking buoy based on the adaptive tracking control algorithm runs more stably and can better complete the precise tracking task for the UUV with a positioning error of less than 10 cm. This method breaks the premise of trajectory prediction based on traditional tracking control algorithms, providing a new direction for further research on UUV localization. Furthermore, the conclusion of this paper has important reference value for other research and application fields related to UUV.

High-resolution temporal detection of cyanobacterial blooms in a deep and oligotrophic lake by high-frequency buoy data.

Cyanobacterial blooms are increasing in magnitude, frequency, and duration worldwide. However, our knowledge of cyanobacterial blooms dynamics and driving mechanisms is still limited due to their high spatiotemporal variability. To determine the potential driving mechanisms of cyanobacterial blooms in oligotrophic lakes, we collected a high-frequency depth profile of chlorophyll fluorescence (ChlF) and synchronous water quality, hydrometeorological data in early spring 2016 in oligotrophic Lake Qiandaohu. The vertical distribution of ChlF exhibited two patterns, "aggregated" and "discrete", using Morisita's index, and the aggregated ChlF presented subsurface chlorophyll maxima during the thermal stratification period. The ChlF concentration was positively correlated with water temperature and negatively correlated with turbidity. Significantly linear relationships were observed between ChlF vertical structure parameters (e.g., Morisita's index, subsurface chlorophyll maxima depth and thickness) and thermal stratification parameters (e.g., mixing layer depth and relative water column stability). After rainstorm floods, the ChlF pattern suddenly change from "aggregated" to "discrete" and a ChlF concentration <1 µg/L was observed for 7-11 days with a significant increase in the mixing depth layer and turbidity. The results suggest that cyanobacterial blooms are robustly associated with thermal stratification and rainstorm floods in the deep and oligotrophic lake. Thermal stratification boosts surface phytoplankton accumulation by increasing water temperature, enhancing light availability and restricting phytoplankton vertical distribution. Rainstorm floods interrupt the accumulation by disrupting thermal stratification and decreasing the available light. Furthermore, wind speed and air temperature both regulate the phytoplankton dynamics by affecting thermal stratification. Our research quantifies the cyanobacterial bloom dynamics and their relationship between environmental factors, improving our knowledge of the driving mechanisms of cyanobacterial bloom for the protection of drinking water safety and aquatic organism health in lakes.

Developments of GNSS buoy for a synthetic geohazard monitoring system.

A global navigation satellite system (GNSS) buoy system for early tsunami warnings has been developed for more than 20 years. The first GNSS buoy system using a real-time kinematic algorithm (RTK) was implemented in the Nationwide Ocean Wave information network for Ports and HArbourS (NOWPHAS) wave monitoring system in Japan in 2008. The records of NOWPHAS were used to update the tsunami alert by the Japan Meteorological Agency (JMA), owing to the tsunami generated by the 2011 Tohoku-oki earthquake (Mw9.0). However, considering that the distance limit is less than 20 km for the RTK algorithm, a new system was designed by introducing a new positioning algorithm and satellite data transmission to place the buoy much farther from the coast. A new technique for the continuous monitoring of ocean-bottom crustal movements was also implemented in the new system. The new buoy system can be used for weather forecasting and ionospheric monitoring as well.

Ocean Wind Observation Based on the Mean Square Slope Using a Self-Developed Miniature Wave Buoy.

Real-time, continuous, and long-term marine monitoring data benefits ocean research. This study developed a low-cost, multi-parameter, miniature wave buoy. High spatial and temporal resolution of sea surface parameters, including wind, waves, and current, can be obtained at low cost through the deployment of numerous buoys, thus forming an observation array. Tested in the laboratory water tank, the relative error of water surface slope measurement of the buoy was approximately 5.6% when the slope angle was less than 15°. For frequencies between 0.1 and 1.0 Hz, the measurement of slope spectrum was almost identical to that of the wave gauge. The buoy underestimated the slope spectrum between 1.0−1.56 Hz. A good relationship (r2 = 0.75) was obtained between wind speed at 10 m above sea surface (U10) and the low-pass-filtered mean square slope (LPMSS). After incorporating the wave age into the U10 inversion process, the root mean square error (RMSE) and BIAS were reduced to 1.15 m/s and 0.02 m/s, respectively. The 2D distribution of buoy-measured slope components was used to detect the wind direction, with an RMSE of 23.7°. The spectral tail slope steepened with increasing wind speed at low wind speeds (<7 m/s). A technical flow chart of the miniature wave buoy is proposed to observe the sea surface parameters. This miniature buoy will play an essential complementary role in the growing demand for sea state monitoring, especially in nearshore oceans.

Open and Cost-Effective Digital Ecosystem for Lake Water Quality Monitoring.

In some sectors of the water resources management, the digital revolution process is slowed by some blocking factors such as costs, lack of digital expertise, resistance to change, etc. In addition, in the era of Big Data, many are the sources of information available in this field, but they are often not fully integrated. The adoption of different proprietary solutions to sense, collect and manage data is one of the main problems that hampers the availability of a fully integrated system. In this context, the aim of the project is to verify if a fully open, cost-effective and replicable digital ecosystem for lake monitoring can fill this gap and help the digitalization process using cloud based technology and an Automatic High-Frequency Monitoring System (AHFM) built using open hardware and software components. Once developed, the system is tested and validated in a real case scenario by integrating the historical databases and by checking the performance of the AHFM system. The solution applied the edge computing paradigm in order to move some computational work from server to the edge and fully exploiting the potential offered by low power consuming devices.

Monopole Antenna with Enhanced Bandwidth and Stable Radiation Patterns Using Metasurface and Cross-Ground Structure.

In this paper, a printed monopole antenna with stable omnidirectional radiation patterns is presented for applications in ocean buoy and the marine Internet of Things (IoT). The antenna is composed of a rectangular patch, a cross-ground structure, and two frequency-selective surface (FSS) unit cells. The cross-ground structure is incorporated into the antenna design to maintain consistent monopole-like radiation patterns over the antenna's operating band, and the FSS unit cells are placed at the backside of the antenna to improve the antenna gain aiming at the L-band. In addition, the FSS unit cells exhibit resonance characteristics that, when incorporated with the cross-ground structure, result in a broader impedance bandwidth compared to the conventional monopole antenna. To validate the structure, a prototype is fabricated and measured. Good agreement between the simulated and measured results show that the proposed antenna exhibits an impedance bandwidth of 83.2% from 1.65 to 4 GHz, compared to the conventional printed monopole antenna. The proposed antenna realizes a peak gain of 4.57 dBi and a total efficiency of 97% at 1.8 GHz.

Short-Term Drift Prediction of Multi-Functional Buoys in Inland Rivers Based on Deep Learning.

The multi-functional buoy is an important facility for assisting the navigation of inland waterway ships. Therefore, real-time tracking of its position is an essential process to ensure the safety of ship navigation. Aiming at the problem of the low accuracy of multi-functional buoy drift prediction, an integrated deep learning model incorporating the attention mechanism and ResNet-GRU (RGA) to predict short-term drift values of buoys is proposed. The model has the strong feature expression capability of ResNet and the temporal memory capability of GRU, and the attention mechanism can capture important information adaptively, which can solve the nonlinear time series drift prediction problem well. In this paper, the data collected from multi-functional buoy #4 at Nantong anchorage No. 2 in the Yangtze River waters in China were studied as an example, and first linear interpolation was used for filling in missing values; then, input variables were selected based on Pearson correlation analysis, and finally, the model structure was designed for training and testing. The experimental results show that the mean square error, mean absolute error, root mean square error and mean percentage error of the RGA model on the test set are 5.113036, 1.609969, 2.261202 and 15.575886, respectively, which are significantly better than other models. This study provides a new idea for predicting the short-term drift of multi-functional buoys, which is helpful for their tracking and management.

Underwater Sound Source Localization Based on Passive Time-Reversal Mirror and Ray Theory.

This study investigates the performance of a passive time-reversal mirror (TRM) combined with acoustic ray theory in localizing underwater sound sources with high frequencies (3-7 kHz). The TRM was installed on a floating buoy and comprised four hydrophones. The ray-tracing code BELLHOP was used to determine the transfer function between a sound source and a field point. The transfer function in the frequency domain obtained from BELLHOP was transformed into the time domain. The pressure field was then obtained by taking the convolution of the transfer function in the time domain with the time-reversed signals that were received by the hydrophones in the TRM. The location with the maximum pressure value was designated as the location of the source. The performance of the proposed methodology for source localization was tested in a towing tank and in the ocean. The aforementioned tests revealed that even when the distances between a source and the TRM were up to 1600 m, the distance deviations between estimated and actual source locations were mostly less than 2 m. Errors originated mainly from inaccurate depth estimation, and the literature indicates that they can be reduced by increasing the number of TRM elements and their apertures.

Depth-Keeping Control for a Deep-Sea Self-Holding Intelligent Buoy System Based on Inversion Time Constraint Stability Strategy Optimization.

Based on the nonlinear disturbance observer (NDO), the inversion time-constraint stability strategy (ITCS) is designed to make the deep-sea self-holding intelligent buoy (DSIB) system hovered at an appointed depth within a specified time limit. However, it is very challenging to determine the optimal parameters of an ITCS depth controller. Firstly, a genetic algorithm based on quantum theory (QGA) is proposed to obtain the optimal parameter combination by using the individual expression form of quantum bit and the adjustment strategy of quantum rotary gate. To improve the speed and accuracy of global search in the QGA optimization process, taking the number of odd and even evolutions as the best combination point of the genetic and chaos particle swarm algorithm (GACPSO), an ITCS depth controller based on GACPSO strategy is proposed. Besides, the simulations and hardware-in-the-loop system experiments are conducted to examine the effectiveness and feasibility of the proposed QGA-ITCS and GACPSO-ITCS depth controller. The results show that the proposed GACPSO-ITCS depth controller provides higher stability with smaller steady-state error and less settling time in the depth-control process. The research of the proposed method can provide a stable operation condition for the marine sensors carried by the DSIB.

MASE: An Instrument Designed to Record Underwater Soundscape.

The study of sound in the natural environment provides interesting information for researchers and policy makers driving conservation policies in our society. The soundscape characterises the biophony, anthrophony and geophony of a particular area. The characterisation of these different sources can lead to changes in ecosystems and we need to identify these parameters in order to make the right decision in relation to the natural environment. These values could be extrapolated and potentially help different areas of ecoacoustic research. Technological advances have enabled the passive acoustic monitoring (PAM) of animal populations in their natural environment. Recordings can be made with little interference, avoiding anthropogenic effects, making it a very effective method for some species such as cetaceans and other marine species in addition to underwater noise studies. Passive acoustic monitoring can be used for population census, but also to understand the effect of human activities on animals. However, recording data over long periods of time requires large storage and processing capacity to handle all the acoustic events generated. In the case of marine environments, the installation of sensors and instruments can be costly in terms of money and maintenance effort. In addition, if they are placed offshore, a data communication problem arises with coverage and bandwidth. In this paper, we propose a low-cost instrument to monitor the soundscape of a marine area using ecoacoustic indices. The instrument is called MASE and provides three echo-acoustic indices at 10 min intervals that are available in real time, which drastically reduces the volume of data generated. It has been operating uninterruptedly for a year and a half since its deployment, except during maintenance periods. MASE has been able to operate uninterruptedly, and maintain an adequate temperature inside while preserving its structural integrity for long periods of time. This has allowed the monitoring and characterisation of the soundscape of the test area in Gando Bay, Gran Canaria Island (Spain) without the need for human intervention to access the data on the instrument itself. Thanks to its integration with an external server, this allows the long-term monitoring of the soundscape, and it is possible to observe changes in the soundscape. In addition, the instrument has made it possible to compare the period of acoustic inactivity during confinement and the return of anthropogenic acoustic activity at sea.

Integrating environmental variability to broaden the research on coral responses to future ocean conditions.

Our understanding of the response of reef-building corals to changes in their physical environment is largely based on laboratory experiments, analysis of long-term field data, and model projections. Experimental data provide unique insights into how organisms respond to variation of environmental drivers. However, an assessment of how well experimental conditions cover the breadth of environmental conditions and variability where corals live successfully is missing. Here, we compiled and analyzed a globally distributed dataset of in-situ seasonal and diurnal variability of key environmental drivers (temperature, pCO2 , and O2 ) critical for the growth and livelihood of reef-building corals. Using a meta-analysis approach, we compared the variability of environmental conditions assayed in coral experimental studies to current and projected conditions in their natural habitats. We found that annual temperature profiles projected for the end of the 21st century were characterized by distributional shifts in temperatures with warmer winters and longer warm periods in the summer, not just peak temperatures. Furthermore, short-term hourly fluctuations of temperature and pCO2 may regularly expose corals to conditions beyond the projected average increases for the end of the 21st century. Coral reef sites varied in the degree of coupling between temperature, pCO2 , and dissolved O2 , which warrants site-specific, differentiated experimental approaches depending on the local hydrography and influence of biological processes on the carbonate system and O2 availability. Our analysis highlights that a large portion of the natural environmental variability at short and long timescales is underexplored in experimental designs, which may provide a path to extend our understanding on the response of corals to global climate change.

Design and Performance Evaluation of a "Fixed-Point" Spar Buoy Equipped with a Piezoelectric Energy Harvesting Unit for Floating Near-Shore Applications.

In the present work, a spar-buoy scaled model was designed and built through a "Lab-on-Sea" unit, equipped with an energy harvesting system. Such a system is based on deformable bands, which are loyal to the unit, to convert wave motion energy into electricity by means of piezo patch transducers. In a preliminary stage, the scaled model, suitable for tests in a controlled ripples-type wave motion channel, was tested in order to verify the "fixed-point" assumption in pitch and roll motions and, consequently, to optimize energy harvesting. A special type of structure was designed, numerically simulated, and experimentally verified. The proposed solution represents an advantageous compromise between the lightness of the used materials and the amount of recoverable energy. The energy, which was obtained from the piezo patch transducers during the simulations in the laboratory, was found to be enough to self-sustain the feasible on-board sensors and the remote data transmission system.

Estimation of Wave Period from Pitch and Roll of a Lidar Buoy.

This work proposes a new wave-period estimation (L-dB) method based on the power-spectral-density (PSD) estimation of pitch and roll motional time series of a Doppler wind lidar buoy under the assumption of small angles (±22 deg) and slow yaw drifts (1 min), and the neglection of translational motion. We revisit the buoy's simplified two-degrees-of-freedom (2-DoF) motional model and formulate the PSD associated with the eigenaxis tilt of the lidar buoy, which was modelled as a complex-number random process. From this, we present the L-dB method, which estimates the wave period as the average wavelength associated to the cutoff frequency span at which the spectral components drop off L decibels from the peak level. In the framework of the IJmuiden campaign (North Sea, 29 March-17 June 2015), the L-dB method is compared in reference to most common oceanographic wave-period estimation methods by using a TriaxysTM buoy. Parametric analysis showed good agreement (correlation coefficient, ρ = 0.86, root-mean-square error (RMSE) = 0.46 s, and mean difference, MD = 0.02 s) between the proposed L-dB method and the oceanographic zero-crossing method when the threshold L was set at 8 dB.

Design, Implementation, and Measurement Procedure of Underwater and Water Surface Antenna for LoRa Communication.

There is an increasing interest in water bodies, which make up more that seventy percent of our planet. It is thus imperative that the water environment should be remotely monitored. Radio frequency (RF) signals have higher bandwidth and lower latency compared to acoustic signals. However, water has high permittivity and conductivity which presents a challenge for the implementation of RF technology. In this work, we undertook a novel design, fabrication, measurement and implementation of an antenna for a sensor node with dual ability of underwater and water surface long range (LoRa) communication at 868 MHz. It was observed that the antenna's performance deteriorated underwater without -10 dB effective bandwidth between 668 MHz and 1068 MHz. The introduction of an oil-impregnated paper buffer around the antenna resulted in an effective 400 MHz bandwidth within the same frequency span. The sensor node with the buffered antenna was able to achieve a distance of 6 m underwater and 160 m over water surface communication to a data gateway node. The sensor node without the buffered antenna was only able to achieve 80 m over water surface communication. These experimental results show the feasibility of using the LoRa 868 MHz frequency in underwater and water surface communication.

Photosynthesis enhancement in four marine microalgal species exposed to expanded polystyrene leachate.

Due to its widespread use, large amounts of expanded polystyrene (EPS) have been released into the marine environment, where it is broken down into small pieces with large surface areas. As such, chemical additives may be released into the environment, which can affect marine organisms; however, studies of the effects of such additives are lacking. We assessed the effects of leachate from EPS on the photosynthetic activities of four microalgal species (Dunaliella salina, Scenedesmus rubescens, Chlorella saccharophila, and Stichococcus bacillaris). They were exposed to EPS leachate for seven days and their photosynthetic activities were analyzed based on seven parameters. Overall, leachate exposure increased photosynthetic activity in all four species, albeit to different degrees and showing slightly different trends among the seven parameters. Based on chemical analysis, hexabromocyclododecane concentrations were higher in small-fragment leachate, whereas UV326 concentrations were higher in low-concentration-large-sphere leachate; bisphenol-A and total organic carbon showed no major differences among leachates. Thus, we speculate that exposure to trace chemicals influenced microalgal photosynthesis and overall growth. These results support further investigation of the impacts of plastic debris and chemical additives on marine ecosystems and organisms.

Stepped Coastal Water Warming Revealed by Multiparametric Monitoring at NW Mediterranean Fixed Stations.

Since 2014, the global land and sea surface temperature has scaled 0.23 °C above the decadal average (2009-2018). Reports indicate that Mediterranean Sea temperatures have been rising at faster rates than in the global ocean. Oceanographic time series of physical and biogeochemical data collected from an onboard and a multisensor mooring array in the northwestern Mediterranean Sea (Blanes submarine canyon, Balearic Sea) during 2009-2018 revealed an abrupt temperature rising since 2014, in line with regional and global warming. Since 2014, the oligotrophic conditions of the water column have intensified, with temperature increasing 0.61 °C on the surface and 0.47 °C in the whole water column in continental shelf waters. Water transparency has increased due to a decrease in turbidity anomaly of -0.1 FTU. Since 2013, inshore chlorophyll a concentration remained below the average (-0.15 mg·l-1) and silicates showed a declining trend. The mixed layer depth showed deepening in winter and remained steady in summer. The net surface heat fluxes did not show any trend linked to the local warming, probably due to the influence of incoming offshore waters produced by the interaction between the Northern Current and the submarine canyon. Present regional and global water heating pattern is increasing the stress of highly diverse coastal ecosystems at unprecedented levels, as reported by the literature. The strengthening of the oligotrophic conditions in the study area may also apply as a cautionary warning to similar coastal ecosystems around the world following the global warming trend.

Ocean Surface Drifting Buoy System Based on UAV-Enabled Wireless Powered Relay Network.

We design an ocean surface drifting buoy system based on an unmanned aerial vehicle (UAV)-enabled wireless powered relay network in which the UAV acts as mobile hybrid access point that broadcasts energy to all buoys in the downlink and forwards information from the buoys to a ship signal tower (ST) in the uplink. In order to maximize the resource allocation efficiency of the system, due to the different initial energy reserve of the buoys, a novel communication mode selection strategy is proposed. In the direct transmission mode (DT mode), an energy-sufficient buoy transmits information directly to the ST, and in the relay transmission mode (RT mode), an energy-insufficient buoy relays information to the ST through the UAV. By applying the block coordinate descent and successive convex optimization, a joint UAV trajectory and resource allocation algorithm is proposed to maximize the minimum throughput of the buoys to work in the RT mode. Simulation results show that the proposed algorithm can significantly improve the minimum throughput of the ocean surface drifting buoys.