Large Water Bodies Research Articles

Realizing the European Vertical Reference System using model-based hydrodynamic leveling data

All realizations of the European Vertical Reference System (EVRS) computed so far are solely based on geopotential differences obtained by spirit leveling/gravimetry. As such, there are no direct connections between height benchmarks separated by large water bodies. In this study, such connections are added by means of model-based hydrodynamic leveling resulting in a new, yet unofficial realization of the EVRS. The model-derived mean water levels used in computing the hydrodynamic leveling connections were obtained from the Nemo-Nordic (Baltic Sea) and 3D DCSM-FM (northwest European continental shelf) hydrodynamic models. The impact of model-based hydrodynamic leveling on the European Vertical Reference Frame is significant, especially for France and Great Britain. Compared to a solution which only uses spirit leveling/gravimetry, the differences in these countries reach tens to hundreds of hbox {kgal}, hbox {mm}. We also observed an improved agreement with normal heights obtained by differencing GNSS and the European gravimetric quasi-geoid 2015 (EGG2015) heights. In Great Britain, the south-north slope of 48 mm hbox {deg}^{-1} present in the solution which uses only spirit leveling/gravimetry data reduced to 2.2 mm hbox {deg}^{-1}. In France, the improvement is confined to the southwest. The choice of the period over which water levels are averaged has an impact on the results as it determines, among others, the set of tide gauges available to establish the hydrodynamic leveling connections. When using an averaging period that can be considered as the least preferred choice based on three established criteria, the positive impact for France has gone. For Great Britain, the estimated south-north slope became 12.6 mm hbox {deg}^{-1}. This is larger than the slope obtained using the most preferred averaging period but still substantially lower compared to the slope associated with a solution that uses only spirit leveling/gravimetry.

Diversity and larval habitats of mosquitoes (Diptera: Culicidae) in urban areas in Ha Noi, Vietnam

Although some mosquito-borne diseases have been thriving in Ha Noi city, Vietnam very few studies on mosquitoes have been conducted. Determining how the species composition and abundance of mosquito vectors depend on environmental resources in different habitats addresses where different types of vector control need to be applied. The present study aims to investigate the characteristics of larval habitats and to provide a composition of mosquitoes (Culicidae) in this city. Surveys of larval and adult mosquitoes were carried out from different habitats in urban areas during rainy seasons from 2018 to 2023. Overall, in almost all water containers that were surveyed (80.9%), immature mosquitoes were present. A total of 4593 mosquitoes including 3,950 larvae and 643 adults were collected from 16 sampling sites. Twelve mosquito species belonging to 6 genera were collected and identified. Aedes albopictus and Culex quinquefasciatus were the most common and abundant species, each accounting for 34% of the total collected larval specimens. Five species, Anopheles umbrosus, Culex cintellus, Armigeres subalbatus, Mansonia annulifera, and Lutzia fuscana were the first records for Ha Noi city. The species composition varied between different habitat types. Peri-domestic habitats were the most common breeding sites for mosquitoes in the study area. Noteworthy, species belonging to genus Aedes were abundant in domestic habitats created by anthropogenic materials while that of genus Culex was mainly thriving in large water bodies in both peri-domestic and natural habitats. The current results show a variation in the distribution and abundance of mosquitoes in urban areas of Ha Noi which should be considered for effective planning and implementing mosquito control programs in the city.

Sediment source and sink identification using Sentinel-2 and a small network of turbidimeters on the Vjosa River

Abstract. Measurement of suspended sediment concentration (SSC) at a basin outlet yields a basin-integrated picture of sediment fluxes; however, it does not give a full spatial perspective on possible sediment pathways within the catchment. Spatially resolved estimates of SSC along river networks are needed to identify sediment sources and sinks, to track erosion gradients, and quantify anthropogenic effects on catchment-scale sediment production, e.g., by dam construction or erosion control. Here we explore the use of high-resolution Sentinel-2 satellite images for this purpose in narrow and morphologically complex mountain rivers, combined with ground station turbidity sensing for calibration and supported by a Lagrangian kayak-derived river profile measurement. The study is carried out on the Vjosa River in Albania, which is one of the last intact large river systems in Europe. We developed a workflow to estimate river turbidity profiles from Sentinel-2 images including atmospheric, cloud cover, and deepwater corrections for the period May 2019 to July 2021 (106 images). In situ turbidity measurements from four turbidity sensors located along the Vjosa River provided ground truthing. A multivariate linear regression model between turbidity and reflectance was fitted to this data. The extracted longitudinal river turbidity profiles were qualitatively validated with two descents of the river with a turbidity sensor attached to a kayak. The satellite-derived river profiles revealed variability in turbidity along the main stem with a strong seasonal signal, with the highest mean turbidity in winter along the entire length of the river. Most importantly, sediment sources and sinks could be identified and quantified from the river turbidity profiles, both for tributaries and within the reaches of the Vjosa. The river basin and network acted as a sediment source most of the time and significant sediment sinks were rare. Sediment sources were mostly tributaries following basin-wide rainfall, but within-reach sources in river beds and banks were also possible. Finally, we used the data to estimate the mean annual fine sediment yield at Dorez at ∼2.5±0.6 Mt yr−1, in line with previous studies, which reveals the importance of the Vjosa River as an important sediment source of the Adriatic Sea. This work presents a proof of concept that open-access high-resolution satellite data have potential for suspended sediment quantification not only in large waterbodies but also in smaller rivers. The potential applications are many, including identifying erosion hotspots, sediment activation processes, local point sources, glacial sediment inputs, and sediment fluxes in river deltas, with a necessary future research focus on improving accuracy and reducing uncertainty in such analyses.

Research Trends in Smart Cost-Effective Water Quality Monitoring and Modeling: Special Focus on Artificial Intelligence

Numerous conventional methods are available for analyzing various water quality parameters to determine the water quality index. However, ongoing surveillance is necessary for large bodies of water. A water quality monitoring system supports a robust surface and groundwater ecosystem. Various tactics are used to improve aquatic habitats: identification of the precise chemical pollutants released into the aquatic environment; advancements in assessing ecological effects; and working on ways to enhance water quality through informing the public, communities, businesses, etc. In order to save the marine ecosystem and those who entirely depend on these enormous bodies of water, it is also crucial to continuously handle many data sets of water quality metrics. To predict the water quality index, this review paper provides an overview of water quality monitoring, the modeling and numerous sensors employed, and various artificial intelligence approaches. Various water quality models were proposed to assess pH, a few components, and alkalinity. Additionally, handling raw information for surface and groundwater quality metrics was studied using artificial intelligence techniques like neural networks.

The ecology and fishery of the vendace (Coregonus albula) in the Baltic Sea.

Brackish water ecosystems often have high primary production, intermediate salinities, and fluctuating physical conditions and therefore provide challenging environments for many of their inhabitants. This is especially true of the Baltic Sea, which is a large body of brackish water under strong anthropogenic influence. One freshwater species that is able to cope under these conditions in the northern Baltic Sea is the vendace (Coregonus albula), a small salmonid fish. Here, we review the current knowledge of its ecology and fishery in this brackish water environment. The literature shows that, by competing for resources with other planktivores and being an important prey for a range of larger species, C. albula plays a notable role in the northern Baltic Sea ecosystem. It also sustains significant fisheries in the coastal waters of Sweden and Finland. We identify the need to better understand these C. albula populations in terms of the predator-prey interactions, distributions of anadromous and sea spawning populations and other putative (eco)morphs, extent of gene exchange between the populations, and effects of climate change on their future. In this regard, we recommend strengthening C. albula-related research and management efforts by improved collaboration and coordination between research institutions, other governmental agencies, and fishers, as well as by harmonization of fishery policies across national borders.

Spatiotemporal Information Mining for Emergency Response of Urban Flood Based on Social Media and Remote Sensing Data

The emergency response is crucial in preventing and mitigating urban floods. Both remote sensing and social media data offer distinct advantages in large-scale flood monitoring and near-real-time flood monitoring. However, current research lacks a thorough exploration of the application of social media data and remote sensing imagery in the urban flood emergency response. To address this issue, this paper, while extracting disaster information based on social media data, deeply mines the spatiotemporal distribution characteristics and dynamic spatial accessibility of rescue points. Furthermore, SAR imagery and social media data for monitoring urban flooding are compared. This study took the Zhengzhou 7.20 urban flood as a case study and created a methodological framework to quickly extract flood disaster information (flood, landslide, and rescue points) using these two types of data; spatiotemporal analysis and random forest classification were also conducted to mine valuable information. Temporally, the study revealed that disaster information did not increase proportionally with the amount of rainfall during the rainfall process. Spatially, specific regions with higher susceptibility to flooding, landslides, and rescue points were identified, such as the central region characterized by low drainage standards and high-density urban areas, as well as the eastern region with low-lying terrain. Moreover, this study examined the spatial accessibility of rescue resources in real flood scenarios and found that their service coverage varied throughout the day during and after the disaster. In addition, social media excelled in high-density urban areas’ flood point extraction, while SAR performed better in monitoring floods at the edges of low-density urban areas and large water bodies, allowing them to complement each other, to a certain extent. The findings of this study provide scientific reference value for the optimal selection of rescue paths and the allocation of resources in the emergency response to urban floods caused by extreme rainstorms.

Evaluation of Practices of Cage Culture in Chandil Dam in Jharkhand, India

Jharkhand, one of the rich natural resources states of India, is endowed with vast fresh water resources in the form of tanks/ponds, reservoirs and dams. Dams in Jharkhand play important role in fish farming, irrigation, power generation and a wonderful tourist place. There are more than 84 dams in Jharkhand of which Chandil dam is one of the popular dams located in the Seraikela-Kharsawan district stands on the Subarnrekha River. This dam has a height of about 56.80 meters and a length of about 720.10 meters. Chandil dam has a catchment area of ​​1,963 square kilometres having a total of 90 cages. Each cage is equipped with 20 batteries to facilitate fish farming. Pangasius and Tilapia are the most preferred species for cage culture in Chandil dam. Each cage contains 4,500 specimens of these fish species. The fish are fed twice daily pellets containing 31% crude protein at 4-6% of their body weight. In 7-8 months, these fish reach a weight of about 1.2 kilogram. The average fish production per cage in the Chandil and its Sanaua dam basins is 4,000 kg. This high productivity contributes to the success of caging, which utilizes large bodies of water and meets the state’s growing demand for animal protein. The fisherman earns Rs.34432 from per cage. It was observed that the cage culture in dam is an excellent way to maximize production potential and make efficient use of large bodies of water. The present study was carried out in Chandil dam with the objective to assess the cage culture practices and fish production status. The assessment was done using the NFDB guidelines of cage culture in inland open water bodies of India using 15 parameters. Interviews with officials of Department of Fisheries and fishers was done to enquire if the guidelines were followed using a 3 point scale. This was corroborated by observation and field visits, so as to adopt the triangulation method.

Nanoparticles, an Emerging Control Method for Harmful Algal Blooms: Current Technologies, Challenges, and Perspectives.

Harmful algal blooms (HABs) are a global concern because they harm aquatic ecosystems and pose a risk to human health. Various physical, chemical, and biological approaches have been explored to control HABs. However, these methods have limitations in terms of cost, environmental impact, and effectiveness, particularly for large water bodies. Recently, the use of nanoparticles has emerged as a promising strategy for controlling HABs. Briefly, nanoparticles can act as anti-algae agents via several mechanisms, including photocatalysis, flocculation, oxidation, adsorption, and nutrient recovery. Compared with traditional methods, nanoparticle-based approaches offer advantages in terms of environmental friendliness, effectiveness, and specificity. However, the challenges and risks associated with nanoparticles, such as their toxicity and ecological impact, must be considered. In this review, we summarize recent research progress concerning the use of nanoparticles to control HABs, compare the advantages and disadvantages of different types of nanoparticles, discuss the factors influencing their effectiveness and environmental impact, and suggest future directions for research and development in this field. Additionally, we explore the causes of algal blooms, their harmful effects, and various treatment methods, including restricting eutrophication, biological control, and disrupting living conditions. The potential of photocatalysis for generating reactive oxygen species and nutrient control methods using nanomaterials are also discussed in detail. Moreover, the application of flocculants/coagulants for algal removal is highlighted, along with the challenges and potential solutions associated with their use. This comprehensive overview aims to contribute to the development of efficient and sustainable strategies for controlling HAB control.

Organochlorine Compounds in the Amur (Heilong) River Basin (2000-2020): A Review.

Persistent organic pollutants (POPs) are well-known contaminants that raise serious concerns, even more than 20 years after they were banned. Their worldwide distribution and persistence necessitate continuous monitoring in all components of the environment. The most challenging issues of POP regulation are associated with international water resources because their solutions require international cooperation in environment protection. This review provides data on various POPs (DDT, HCH, endrin, dieldrin, and PCBs) and their concentrations in aquatic organisms inhabiting the Amur River basin, one of the most poorly explored regions of Northeast Asia. Most studies have been conducted in the Songhua River (China), a tributary of the Amur River, which indicates that large inland bodies of water, especially those of international importance, require more extensive research.

Facile fabrication and application of highly efficient reduced graphene oxide (rGO)-wrapped 3D foam for the removal of organic and inorganic water pollutants.

The pace of water contamination is increasing daily due to expanding industrialisation. Finding a feasible solution for effectively remediating various organic and inorganic pollutants from large water bodies remains challenging. However, a nano-engineered advanced hybrid material could provide a practical solution for the efficient removal of such pollutants. This work has reported the development of a highly efficient and reusable absorbent comprising a porous polyurethane (PU) and reduced graphene oxide (rGO) nanosheets (rGOPU) for the removal of different organic oils (industrial oil, engine oil and mustard oil), dyes (MB, MO, RB, EY and MV) and heavy metals (Pb(II), Cr(VI), Cd(II), Co(II) and As(V)). The structure, morphology and properties of the rGOPU hybrid absorbents were analysed by using Raman spectroscopy, field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and Brunner-Emitte-Teller (BET) analysis. The rGOPU possessed both superhydrophobicity and superoleophilicity with water and oil contact angles of about 164° and 0°, respectively. The prepared rGOPU has demonstrated an excellent oil-water separation ability (up to 99%), heavy metals removal efficiency (more than 75%), toxic dye adsorption (more than 55%), excellent recyclability (> 500 times for oils), extraordinary mechanical stability (90% compressible for > 1000 cycles) and high recoverability. This work presents the first demonstration of rGOPU's multifunctional absorbent capacity in large-scale wastewater treatment for effectively removing a wide variety of organic and inorganic contaminants.

Surface water expansion due to increasing water demand on the Loess Plateau

Study regionThe Loess Plateau in China Study focusLand surface water bodies are important to ensure water security for agricultural, industrial, domestic, and environmental sectors. In the Loess Plateau, changes in land surface water due to climate change and human activities are a concern. Dam and reservoir constructions are effective to combat erosion and water scarcity, but the impact on surface water dynamics is unclear. In this study, we employ a long-term satellite water product to detect the spatial-temporal variability in surface water at the regional scale on the Loess Plateau and identify the potential cause of climate change and human activities.New hydrological insights for the region: Over the past two decades, the area of permanent water has increased by approximately 800 km2. Surface water expansion is primarily associated with small water bodies (< 1 km2), as their number has roughly doubled, while the number and area of large water bodies have remained stable. This expansion has little correlation with precipitation variation but is highly correlated with water withdrawal for agricultural, industrial, and other sectors. Thus, it is primarily contributed by hydraulic project construction as a response to the increasing water demand. The above findings imply the positive role of hydraulic projects, but it is essential to note that the continuous expansion of surface water might not be sustainable because of natural constraints.

Generalizing Shallow Water Simulations with Dispersive Surface Waves

This paper introduces a novel method for simulating large bodies of water as a height field. At the start of each time step, we partition the waves into a bulk flow (which approximately satisfies the assumptions of the shallow water equations) and surface waves (which approximately satisfy the assumptions of Airy wave theory). We then solve the two wave regimes separately using appropriate state-of-the-art techniques, and re-combine the resulting wave velocities at the end of each step. This strategy leads to the first heightfield wave model capable of simulating complex interactions between both deep and shallow water effects, like the waves from a boat wake sloshing up onto a beach, or a dam break producing wave interference patterns and eddies. We also analyze the numerical dispersion created by our method and derive an exact correction factor for waves at a constant water depth, giving us a numerically perfect re-creation of theoretical water wave dispersion patterns.

Sub-monthly time scale forecasting of harmful algal blooms intensity in Lake Erie using remote sensing and machine learning

Harmful algal blooms of cyanobacteria (CyanoHAB) have emerged as a serious environmental concern in large and small water bodies including many inland lakes. The growth dynamics of CyanoHAB can be chaotic at very short timescales but predictable at coarser timescales. In Lake Erie, cyanobacteria blooms occur in the spring-summer months, which, at annual timescale, are controlled by the total spring phosphorus (TP) load into the lake. This study aimed to forecast CyanoHAB cell count at sub-monthly (e.g., 10-day) timescales. Satellite-derived cyanobacterial index (CI) was used as a surrogate measure of CyanoHAB cell count. CI was related to the in-situ measured chlorophyll-a and phycocyanin concentrations and Microcystis biovolume in the lake. Using available data on environmental and lake hydrodynamics as predictor variables, four statistical models including LASSO (Least Absolute Shrinkage and Selection Operator), artificial neural network (ANN), random forest (RF), and an ensemble average of the three models (EA) were developed to forecast CI at 10-, 20- and 30-day lead times. The best predictions were obtained by using the RF and EA algorithms. It was found that CyanoHAB growth dynamics, even at sub-monthly timescales, are determined by coarser timescale variables. Meteorological, hydrological, and water quality variations at sub-monthly timescales exert lesser control over CyanoHAB growth dynamics. Nutrients discharged into the lake from rivers other than the Maumee River were also important in explaining the variations in CI. Surprisingly, to forecast CyanoHAB cell count, average solar radiation at 30 to 60 days lags were found to be more important than the average solar radiation at 0 to 30 days lag. Other important variables were TP discharged into the lake during the previous 10 years, TP and TKN discharged into the lake during the previous 120 days, the average water level at 10-day lag and 60-day lag.

Waterbody size predicts bank- and boat-angler efforts

Bank- and boat-angler efforts are logistically difficult and costly to estimate, preventing landscape-scale estimates that are required to address current and future challenges (e.g., climate change, invasive species) for inland recreational fisheries. Using a large Nebraska, USA, recreational fishery dataset (N = 67 waterbodies), we demonstrate that waterbody size can be used to predict bank- and boat-angler efforts across a heterogeneous landscape of extra small (< 104 ha) and large (> 647 ha) waterbodies. Bank and boat anglers respond to waterbody size, however these relationships appear to be unique between the two angler types. Boat-angler efforts increased as a function of waterbody size, whereas bank-angler efforts increased as a function of waterbody size for extra small waterbodies but not for large waterbodies. The ability to connect waterbody size and angler effort will be important for continued effective inland fisheries management.

A window into development of a complex ice-marginal lake prior to the Late Glacial Maximum (LGM) in Austria

Abstract Although the retreat process of glaciers from the Late Glacial Maximum (LGM) is well documented, high-resolution insight into conditions prior to the maximum is lacking in the eastern European Alps, resulting in a gap in our understanding about the processes associated with this important climatic tipping point. We describe an outstanding sand and gravel outcrop at Gröbming in the Enns Valley (Ennstal), Austria, that represents the development of a delta complex that debouched into a large body of water that we name paleo-Lake Gröbming, fed by a major valley glacier. The succession consists of sands bearing climbing ripples, parallel laminations, and supercritical bed forms (bottomsets) overlain by meter-scale gravelly foresets. Topsets comprise gravels. We argue that sustained accumulation of supercritical bed forms required a jet efflux feeder mechanism best explained by a direct glacial meltwater source. Complex vertical and lateral repetition of this tripartite succession is observed, with sequence stratigraphic analysis permitting us to argue that stratal complexity is attributable to base-level changes in paleo-Lake Gröbming resulting from dam breaches of the lake. Thus, application of well-established sequence stratigraphic approaches to Quaternary ice-marginal successions in the Alps has significant potential to yield unprecedented insights into conditions prior to the LGM.

Theater of India-China strategic rivalry: The Indian Ocean

The strategic importance of the Indian Ocean is increasing in the world in general and in India’s sub-continent in particular. The Indian Ocean is world’s third largest water body on the surface of the Earth and has increasingly become an area of contention between India and China. As their power, interests, capabilities, and economy increases, the competition between the two Asian giants also increases. This competition has the potential to endanger the stability of the region, which is significant for all key players in the region. This article presents the strategic importance of the Indian Ocean, gives an overview of India’s strategic interests and China’s growing ambitions in the Indian Ocean Region (IOR), analyzes the current power dynamics and gives recommendations on how India should approach and prioritize this strategically significant region.

How Does Wind Influence Near-Nadir and Low-Incidence Ka-Band Radar Backscatter and Coherence from Small Inland Water Bodies?

While many studies have been conducted regarding wind-driven Ka-band scattering on the ocean and sea surfaces, few have identified the impacts of Ka-band scattering on small inland water bodies, and fewer have identified the influence of wind on coherence over water. These previous studies have been limited in spatial scale, covering only large water bodies &gt;25 km2. The recently launched Surface Water and Ocean Topography (SWOT) mission is the first Ka-band InSAR satellite designed for mapping water surface elevations and open water areas for rivers as narrow as 100 m and lakes as small as 0.0625 km2. Because measurements of these types are novel, there remains some uncertainty about expected backscatter amplitudes given wind-driven water surface roughness variability. A previous study using the airborne complement to SWOT, AirSWOT, found that low backscatter and low coherence values were indicative of higher errors in the water surface elevation products, recommending minimum thresholds for backscatter and coherence for filtering the data to increase the accuracy of averaged data for lakes and rivers. We determined that the global average wind speed over lakes is 4 m/s, and after comparing AirSWOT backscatter and coherence data with ERA-5 wind speeds, we found that the minimum required speed to retrieve high backscatter and coherence is 3 m/s. We examined 11,072 lakes across Canada and Alaska, with sizes ranging from 350 m2 to 156 km2, significantly smaller than what could be measured with previous Ka-band instruments in orbit. We found that small lakes (0.0625–0.25 km2) have significantly lower backscatter (3–5 dB) and 0.20–0.25 lower coherence than larger lakes (&gt;1 km2). These results suggest that approximately 75% of SWOT observable lake areas around the globe will have consistently high-accuracy water surface elevations, though seasonal wind variability should remain an important consideration. Despite very small lakes presenting lower average backscatter and coherence, this study asserts that SWOT will be able to accurately resolve the water surface elevations and water surface extents for significantly smaller water bodies than have been previously recorded from satellite altimeters. This study additionally lays the foundation for future high-resolution inland water wind speed studies using SWOT data, when the data become available, as the relationships between wind speed and Ka-band backscatter reflect those of traditional scatterometers designed for oceanic studies.

Perceived Impact of Affect Labeling and Social Sharing in Healthcare: Insights from a Pilot Study and Opportunities for Future Investigation

Perceived Impact of Affect Labeling and Social Sharing in Healthcare: Insights from a Pilot Study and Opportunities for Future Investigation

TO THE QUESTION OF INFLUENCE OF ABIOTIC AND ANTHROPOGENIC FACTORS ON THE DAILY VERTICAL MIGRATION ACTIVITY ON THE AQUATIC ORGANISMS OF LAKE BAIKAL

Daily vertical migration (DVM) of aquatic organisms is a widespread phenomenon in both small and large water bodies. It is observed, including in the deepest lake in the world – Baikal. Unique Baikal amphipods and lower crustaceans (Cladocera, Copepoda, Ostracoda) are the main representatives of the nocturnal migratory complex. As part of this study, it was found that artifi cial lighting and changes in the lake water level can aff ect the nighttime migratory activity of aquatic organisms.

Recent advances in acoustic technology for aquaculture: A review

AbstractAcoustic technology has great application prospects in aquaculture. In particular, two indispensable, critical technologies for the future aquaculture industry are multi‐sensor acquisition that can achieve multi‐scale information fusion, collection and establishment of a global acoustic fish database and highly developed deep learning intelligent algorithms that can establish a correlation mechanism between fish acoustic and behaviour characteristics. Acoustic technology offers remarkable advantages in large and turbid water bodies for studying spatial and temporal distribution patterns of aquatic organism populations, developing on‐demand feeding systems and estimating biomass. This article reviews the development of acoustic technology and its application in aquaculture over the last 30 years. It further analyses, in detail, the advantages and disadvantages of acoustic technology in evaluating aquatic organism biomass and morphological and physical indicators, aquatic organism behaviour and welfare improvement. Challenges of acoustic technology in acquiring dynamic target data accurately, building a global acoustic fish database and establishing connections between fish behaviour and acoustic characteristics are also discussed. In brief, this article aims to help researchers and practitioners better understand the current state‐of‐the‐art acoustic technologies, which can provide strong support for smart aquaculture applications.