Narrow Waterways Research Articles

Spatial and seasonal variability of chlorophyll-a, total suspended matter, and colored dissolved organic matter in the Sundarban mangrove forest using earth observation and field data

The Sundarbans, the world's largest mangrove forest, confronts potential threats from various anthropogenic activities leading to degradation of its aquatic ecosystem. To examine the current status of the aquatic ecosystem, this study aimed to evaluate the spatial and seasonal fluctuation of three principal water quality attributes namely Chlorophyll-a (Chl-a), Total Suspended Matter (TSM), and Colored Dissolved Organic Matter (CDOM) in the complex tidal river systems of the Sundarban mangroves forest using earth observation and in-situ data. A set of two bio-optical algorithms, Ocean color-2 (OC-2) and Ocean color-3 (OC-3), were applied to measure Chl-a concentration, Green/NIR and the Red/NIR band ratio algorithms were used for TSM and the Case-2 Regional Coast Color (C2RCC) processor in the SNAP software was applied to obtain CDOM concentration in study area. A total of 50 in-situ samples were collected during post-monsoon and pre-monsoon to validate the results. Our results clearly demonstrated seasonal variability with higher Chl-a concentrations in post-monsoon than pre-monsoon. This was due to the OC-2 algorithm which produced better results with R2 = 0.73, RMSE = 0.27 for post-monsoon and R2 = 0.55, RMSE = 0.32 for pre-monsoon. Whilst, TSM concentration performed the best with R2 = 0.77; RMSE = 15.82 and R2 = 0.65; RMSE = 33.96 in post-monsoon and pre-monsoon according to the Green/NIR band ratio method. The nearshore and narrow waterway regions had the highest concentrations of TSM and Chl-a, whereas the offshore regions had the lowest. Strong association were observed between the in-situ and satellite derive absorption coefficient, aCDOM (m−1). The R2 for a CDOM during pre-monsoon was 0.65 and throughout the post-monsoon, it was 0.74. Pre-monsoon concentrations were found to be higher due to marine sources and higher wind speeds, possibly due to sediment resuspension. This kind of baseline evaluation will help to detect threats, direct preventive measures for the protection of biodiversity, and deepen our knowledge of these distinct ecosystems. The results will help develop flexible management and preservation plans that can adjust to both natural and man-made changes.

Advances in Navigability and Mooring

Considerable technological progress has been made in ship handling and mooring in recent years, especially progress generated by the needs imposed by the introduction of ever larger ships. These advancements exploit the economic scale and environmental efficiency of larger vessels, but also present unique challenges, particularly in narrow waterways and harbour approaches. Precise navigation in these environments requires highly accurate hydrographic measurements, high-quality electronic charts, and advanced navigation systems, such as modern electronic chart display and information systems (ECDIS). Safe and efficient port operations also depend on the optimised allocation of port resources and comprehensive queuing strategies. Modern ships are increasingly susceptible to interference with Global Navigation Satellite Systems (GNSS) and Automatic Identification Systems (AIS), necessitating the development of resilient technologies and procedures to ensure navigational safety. In addition, climate change is exacerbating the challenges of ship handling in ports, as larger vessels are particularly vulnerable to sudden gusts of wind and have difficulty maintaining their position in the quay in strong crosswinds. Training and simulation are crucial to overcoming these challenges. Ship-handling simulators are invaluable for training purposes, but development is still needed to accurately simulate tilt and lean effects, especially when ships are sailing in narrow channels with following currents and changing winds. Improving the accuracy of these simulators will improve the preparation of seafarers for real-life conditions and ultimately contribute to safer and more efficient ship operations.

A data-driven Ship Risk Profile model for Turkish Straits (TS-SRP) using Machine Learning

Marine accidents exhibit a higher frequency within ports, internal waters, and narrow waterways as compared to open seas, emphasizing the paramount concern of maritime authorities regarding the safe navigation of ships in congested waters. In response to this issue, coastal states, in addition to flag state and port state measures, institute preventive measures by conducting risk analyses in narrow waterways with geographical restrictions and high traffic density. To meet this need, this study aims to develop a Ship Risk Profile (SRP) model to monitor ships by evaluating the potential risks of the ships passing through narrow waterways and taking the necessary precautions proactively by Vessel Traffic Service (VTS) for mitigating the potential accident and environmental pollution risk. The Turkish Straits is determined as the application area for this paper. The proposed model employs Machine Learning (ML) methods and analyzes targeting factors from Port State Control (PSC), ship particulars obtained from Sailing Plan (SP)-1 reports specific to the Turkish Straits, as well as relevant environmental factors. The results demonstrate that the developed model holds promise for improving safety in Turkish Straits and can be adapted by VTSs in other sea regions by customizing it to suit their specific characteristics and conditions.

Distributed Optimization-Based Path Planning for Multiple Unmanned Surface Vehicles to Pass through Narrow Waters

Safety and efficiency are important when Unmanned Surface Vehicles (USVs) pass through narrow waters in complex marine environments. This paper considers the issue of path planning for USVs passing through narrow waterways. We propose a distributed optimization algorithm based on a polymorphic network architecture, which maintains connectivity and avoids collisions between USVs while planning optimal paths. Firstly, the initial path through the narrow waterway is planned for each USV using the narrow water standard route method, and then the interpolating spline method is used to determine its corresponding functional form and rewrite the function as a local cost function for the USV. Secondly, a polymorphic network architecture and a distributed optimization algorithm were designed for multi-USVs to maintain connectivity and avoid collisions between USVs, and to optimize the initial paths of the multi-USV system. The effectiveness of the algorithm is demonstrated by Lyapunov stability analysis. Finally, Lingshui Harbor of Dalian Maritime University and a curved narrow waterway were selected for the simulation experiments, and the results demonstrate that the paths planned by multiple USVs were optimal and collision-free, with velocities achieving consistency within a finite time.

Evolution and extinction in a supercontinental world: did the breakup of Rodinia provide metazoans with evolutionary salvation?

A time discrepancy of at least 200–300 million years exists between the generally accepted onset of metazoan evolution as currently evidenced from fossils compared with that from studies at the molecular level. That temporal disparity coincides with the existence and subsequent breakup of the Rodinia Supercontinent when the earliest evolutionary crucibles were isolated intracratonic basins rather than the globally connected shallow seaways of subsequent eras. However, the discovery of fossil evidence to complement the extrapolations from molecular data has been, and continues to be, hampered, by both the geographical limitations of these isolated intracratonic basins and the fact that any such discovery would conflict with the global geological mindset that macrofossils of such age do not exist. Yet recently identified within the intracratonic Amadeus Basin of central Australia is a suite of macroscopic metazoan fossils that dates to ca 850–840 Ma, exemplifying an early attempt at animal evolution within the restrictions of the Rodinia Supercontinent. Such early metazoan evolution within such isolated crucibles, however, was extremely vulnerable to variations in climatic conditions, which threatened total extinction because the isolation of these basins limited metazoan distribution by denying them the possibility of migrating to safer havens. The Amadeus Basin evidence suggests that early metazoan evolution perhaps comprised cycles of about 10 million years when evolution flourished followed by climate change induced extinction and a subsequent evolutionary void of between 50 and 100 million years. Such cycles possibly characterised metazoan evolution until the Rodinia Supercontinent broke-up, after which connections between smaller oceans, shallow seas and narrow waterways provided metazoan life passageway to sanctuary during times of environmental stress. As the Amadeus Basin was just one of a number of isolated Rodinian-aged intracratonic basins, it is likely that similar fossils of the earliest metazoans are preserved elsewhere awaiting discovery.

Research on the Vanishing Point Detection Method Based on an Improved Lightweight AlexNet Network for Narrow Waterway Scenarios

When an unmanned surface vehicle (USV) navigates in narrow waterway scenarios, its ability to detect vanishing points accurately and quickly is highly important for safeguarding its navigation safety and realizing automated navigation. We propose a novel approach for detecting vanishing points based on an improved lightweight AlexNet. First, a similarity evaluation calculation method based on image texture features is proposed, by which some scenarios are selected from the filtered Google Street Road Dataset (GSRD). These filtered scenarios, together with the USV Inland Dataset (USVID), compose the training dataset, which is manually labeled according to a non-uniformly distributed grid level. Next, the classical AlexNet was adjusted and optimized by constructing sequential connections of four convolutional layers and four pooling layers and incorporating the Inception A and Inception C structures in the first two convolutional layers. During model training, we formulate vanishing point detection as a classification problem using an output layer with 225 discrete possible vanishing point locations. Finally, we compare and analyze the labeled vanishing point with the detected vanishing point. The experimental results show that the accuracy of our method and the state-of-the-art algorithmic vanishing point detector improves, indicating that our improved lightweight AlexNet can be applied in narrow waterway navigation scenarios and can provide a technical reference for autonomous navigation of USVs.

Ship Speed Optimization Method in Canal Environments Considering Waiting Times for Crossing Locks

The shipping industry faces a pressing challenge with carbon emissions, prompting a focus on speed optimization for energy conservation and emission reduction. While much research has centered on optimizing speeds in oceans and rivers, canals have received less attention, despite their unique challenges of narrow waterways and busy locks. This study fills this gap by establishing a fuel consumption prediction model integrating key environmental factors such as water depth, width, and flow velocity. Drawing upon established methodologies in speed optimization, this study augments these models with waiting time limits for each canal segment. To validate the efficacy of the model, three representative ships are selected as case studies. The findings reveal a high predictive capability of the fuel consumption model, as evidenced by R2 values exceeding 0.97 across all cases. Notably, the optimization approach yields a fuel consumption reduction ranging from 4% to 5% for short waiting times. Furthermore, compared to conventional methods, the proposed optimization strategy achieves an 8.19% enhancement in fuel consumption and carbon emission reduction for long waiting times, culminating in an overall optimization rate of 11.54%. These results underscore the significance of employing the proposed speed optimization methodology, particularly during peak periods of canal congestion.

Automatic Identification System-Based Prediction of Tanker and Cargo Estimated Time of Arrival in Narrow Waterways

In maritime logistics, accurately predicting the Estimated Time of Arrival (ETA) of vessels is pivotal for optimizing port operations and the global supply chain. This study proposes a machine learning method for predicting ETA, drawing on historical Automatic Identification System (AIS) data spanning 2018 to 2020. The proposed framework includes a preprocessing module for extracting, transforming, and applying feature engineering to raw AIS data, alongside a modeling module that employs an XGBoost model to accurately estimate vessel travel times. The framework’s efficacy was validated using AIS data from the Port of Houston, and the results indicate that the model can estimate travel times with a Mean Absolute Percentage Error (MAPE) of just 5%. Moreover, the model retains consistent accuracy in a simplified form, pointing towards the potential for reduced complexity and increased generalizability in maritime ETA predictions.

Variability in surge levels in communities adjacent to the Houston Ship Channel industrial Corridor to changes in Hurricane characteristics

ABSTRACT The sensitivity of hurricane-driven storm surge in the Houston Ship Channel Industrial Corridor to variations in storm characteristics is studied. Hurricane surge from Hurricane Ike from 2008 was simulated using the Delft3D Flexible Mesh model. Use of the HURDAT2 wind parameter database allowed alteration of relevant hurricane characteristics to develop these alternate scenarios. Moving the actual landfall location of Ike toward the southwest at a distance of 50 km yielded a 123% increase at Manchester relative to observations during the storm. Relocation of the landfall location 200 km further southwest caused a 40% decrease in water level at the Galveston Bay entrance relative to observed values, but with a corresponding 50% water level increase at Manchester. Reduction of the storm forward speed to 25% of the actual speed over the nearshore led to a 25% increase in water level in Manchester over recorded values, while a 57% reduction of the storm forward speed over land increased water levels in Manchester by 30%. Incorporating river flow also identified locations where Galena Park’s residual floodwater is likely to remain after flooding. The results of this work can be used to guide modeling efforts of storm impacts on areas with narrow waterways.

Heavy metal pollution in surface water bodies in provincial Khanh Hoa, Vietnam: Pollution and human health risk assessment, source quantification, and implications for sustainable management and development

The global issue of heavy metal pollution in surface water poses a significant concern, with the potential to harm public health through various pathways. Given that pollution levels are dependent on water bodies and seasons and their potential impacts on human health vary with children and adults, it is crucial to identify and quantify pollution sources for the development of sustainable management strategies. The current study aimed to evaluate pollution levels and associated health risks of heavy metals and to quantify their pollution sources in various surface water bodies in Khanh Hoa, Vietnam. Water samples were taken from three water bodies (reservoirs, rivers, and narrow waterways) during two seasons (dry and rainy) from 2016 to 2020 and analyzed for seven heavy metals. The results showed that iron had the highest concentration of 392.4 (μg L−1), followed by zinc (25.7 μg L−1), arsenic (3.93 μg L−1), copper (3.77 μg L−1), lead (2.77 μg L−1), chromium (2.71 μg L−1), and cadmium (0.57 μg L−1). Narrow waterways were more polluted with heavy metals (heavy metal pollution index, HPI = 29.5) than other water bodies, such as rivers (23.3) and reservoirs (21.7), and the dry season had a higher HPI (26.5) than the rainy season (24.0). The hazard index for children varied from 1.2 to 1.48, while that for adults was less than 1, suggesting that surface water may have adverse impacts on children's health. The factor analysis identified three primary sources of contamination, namely combustion emissions/street dust, agricultural run-off, and other sources. Cadmium is the most critical metal in determining HPI, while arsenic and chromium are the two key elements potentially influencing children's health. Managing pollution sources, reducing the metal concentration, and controlling the pathways through which metals enter the human body should be implemented for a healthier environment and long-term development.

Hydrodynamics and sediment transport in Poyang Lake under the effects of wind and backflow

Abstract The ecology of the aquatic environment in Poyang Lake, the largest fresh lake in China, is notably impacted by the backflow from the Yangtze River, which conveys a high flux of sediments. This study employs a widely recognized numerical model to replicate the backflow in 2007 (the strongest backflow after the operation initiation of the Three Gorges Dam) to investigate the contributions of wind and backflow to the sediment transport process. The results show that the influences of wind and backflow on flow patterns and sediment transport processes have significant spatial heterogeneity. In the narrow waterway leading to the central lake area, hydrodynamics is mainly driven by backflow. Conversely, the hydrodynamics of the open expanse of the lake is primarily influenced by wind forces. Dominant wind leads to the formation of gyres, which significantly alter flow paths and push sediment into the upstream areas. As a result, the suspended sediment area expands at an average rate of 20.1–21.3 km2 daily, marking a 75–85% surge compared to the no wind condition (11.5 km2). The study facilitates a deeper understanding of sediment transport processes in large lakes.

Navigable Area Detection and Perception-Guided Model Predictive Control for Autonomous Navigation in Narrow Waterways

Navigable Area Detection and Perception-Guided Model Predictive Control for Autonomous Navigation in Narrow Waterways

Density and abundance estimate of Antillean manatees (Trichechus manatus) within a landlocked lake in Southeastern México

Manatees are threatened along their range. In México, this species is listed as endangered. Manatee conservation strategies require density or occupancy estimates, especially in areas where species face survival risks. On turbid waters, like those found in rivers and lakes of the Southern Gulf of México coast, visual methods used to detect and count manatees underestimate actual numbers. Our goal was to estimate the density and abundance (N) of Antillean manatees in a small State Natural Protected Area, where a manatee population of unknown size inhabits. We performed line transects using a side scan sonar to detect animals and mark-recapture in the isolated population of manatees within Laguna de las Ilusiones, México, a landlocked lake that excludes transit. Using distance sampling from 14 boat trips, estimates of density and abundance were 15.5 manatees km-2 and 27 ± 5 manatees in the lake (CV ≈ 16.6 %). With MARK, from six capture events and 19 individual encounter records, the abundance estimated was 24 manatees (CV ≈ 16 to 24 %). Previous number of manatees were based only on visual surveys, which reported at least seven manatees. Density is lower than other similar studies along narrow waterways in important areas in México and other Central and South America countries. Studying this endangered subspecies is limited by cryptic habits, turbid waters, poor funding, and low densities, making density or abundance estimates difficult. However, within particular areas and established monitoring areas, these methods could be useful to generate baselines for conservation strategies.

Autonomous docking trajectory optimization for unmanned surface vehicle: A hierarchical method

Docking trajectory planning for unmanned surface vehicles is challenging due to complicated obstacle-avoidance in the harbor and highly nonlinear motion equations. In this paper, a two-stage (i.e., searching and optimization) hierarchical method is developed for a safe and efficient solution. In the searching stage, we establish a grid map for the harbor environment. The unmanned surface vehicle is represented by multiple featured discs and an artificially-guided Hybrid A* algorithm is implemented to search a coarse collision-free path. In the optimization stage, we first estimate the total sailing time under time-optimal maneuvering assumptions. Given the discretization scheme, we resample state and control variables along the coarse path by interpolation. Then, we construct a series of safe sailing corridors along the interpolated results. The within-corridor constraints are used to reformulate the optimal control problem, and the interpolated results are used for warm-start. The developed method is numerically validated by two docking scenarios, where high-quality trajectory as well as profiles of control inputs can be obtained with satisfactory computational efficiency. Meanwhile, it shows superiority in robustness over traditional planning techniques in the presence of narrow waterways and concave harbor shores. An animation of the simulation results is available at www.bilibili.com/video/BV14D4y1t7QL/.

Spatial and Statistical Analysis of Operational Conditions Contributing to Marine Accidents in the Singapore Strait

Narrow waterways are important connection hubs, also known as logistics transfer nodes, within maritime transport, where maritime traffic can become very dense and congested. Heavy traffic, unsuitable environmental conditions and human errors make narrow waterways risky areas for marine accident occurrence. Accidents in narrow waterways cause ship damage, loss of cargo, loss of life and environmental disasters, as well as interruption of maritime transport and negative impact on the economy. Thus, the sustainability of navigational safety in narrow waterways has been the focus of attention of all beneficiaries in the maritime industry. The Singapore Strait is one of the busiest narrow waterways in the world in terms of the number of ships transiting. Sustaining and safe maritime transport in the Singapore Strait is significantly important for the sustainability of the global trade. Therefore, it is vitally important to appropriately identify the threats to safety of navigation in the Singapore Strait. In this study, the operational conditions that have played a role in the occurrence of accidents in the Singapore Strait are examined. For this purpose, using the Geographical Information System (GIS), the areas where marine accidents are concentrated were determined by the Kernel Density Analysis method and a “Marine Accidents Density Map” was created for the Singapore Strait. The relationship between the dense areas in the marine accidents density map and the operational conditions that play a role in the accidents in the Singapore Strait were examined using the Chi-Square Test and expert opinions. The results of the study indicate that if there is a condition (e.g., turning, joining to the traffic stream, or failure in propulsion/steering systems) that directly or indirectly disturbs the normal flow of traffic in the Singapore Strait, the risk of having an accident increases. The results of this study can be used to determine the measures to be taken for the prevention of possible accidents, as well as to help manage the risks associated with the ships that pass through the region.

İstanbul Boğazı Gemi Boğaz Geçişi Kuyruk Teorisi Uygulaması ve Süreç Optimizasyonu

Dünya ekonomisi içerisinde deniz ulaşımının büyük etkisi olduğu yadsınamaz bir gerçektir. Deniz ulaşımı için gemiler ve limanlar kadar dar su yolları da önem arz etmektedir. Bu bağlamda dar su yollarının da dünya ekonomisi içerisinde etkili olduğunu söylemek mümkündür. İstanbul Boğazı dünya ekonomisi için etken rol oynayan dar su yollarının en önemlilerindendir. Her dar su yolunda olduğu gibi İstanbul Boğazı’nda da beklemeler oluşabilmekte, meydana gelen beklemeler dünya ekonomisini etkilemektedir. Bu çalışma ile İstanbul Boğazı gemi bekleme kuyruklarının mevcut durumu yasal mevzuat çerçevesinde değerlendirilmektedir. Güncel mevzuat göz önünde bulundurularak İstanbul Boğazı gemi geçişi için bir kuyruk modellemesi tasarlanmakta, 2020 yılı gemi geçiş verileri tanımlayıcı analizleri ile sürecin değerlendirilmesi sağlanmaktadır. Tasarlanan modelleme 2020 yılı gemi geçiş verileri ile kıyaslanarak mevcut durum ortaya konulmaktadır. Makalede bekleme kuyruklarının önüne geçmek amacıyla önerilerde bulunulmakta İstanbul Boğazı gemi geçişi için süreç optimizasyonu gerçekleştirilmektedir. Böylelikle İstanbul Boğazı deniz trafiği süreçlerinin optimizasyonunu sağlamak hedefinde dünya ekonomisine katkı sağlayacağı öngörülen önerilerde bulunmak amaçlanmaktadır.

Spatial and statistical analysis of operational conditions influencing accident formation in narrow waterways: A Case Study of Istanbul Strait and Dover Strait

Identifying accident-prone areas in narrow waterways, which are the nodal points of global maritime trade, assessing accident risks, and reviewing existing safety measures are essential for countries adjacent to narrow waterways as well as all other stakeholders of maritime trade. Furthermore, this is a requirement to ensure safety-sustainable maritime trade. In this study, marine accident density maps were generated utilizing Geographical Information Systems (GIS) software based on reports of collision, contact, grounding, and sinking accidents that occurred in Istanbul Strait (IS) and Dover Strait (DS) between 2004 and 2020. The Chi-Square independence test, one of the main statistical methods, was then used to determine if there were statistically significant relationships between the operational conditions and the accident type, the accident severity, and the Kernel density. Finally, the operational conditions and statistical results were presented to experts, who are familiar with the area, discussed, and then validated. As a result, marine accident density maps for IS and DS were presented and the hazards arising from operational conditions in these narrow waterways were determined. The results of the study will help to raise awareness about the current hazards arising from operational conditions in IS and DS, which are important hubs of maritime trade.

A new approach to narrow waterways traffic routing with potential flow theory and CFD

Navigational planning is crucial for safety of navigation in narrow waterways, both for the ships and the environment. The movement of the ships is very complex in narrow waterways, which are in curved form with surface current and counter-deep current. A TSS (traffic separation scheme), a maritime traffic management route system, has been established worldwide in most narrow waterways and turning points close to shore. The ships plan their routes under the TSS in the region they navigate. In this research, the aim of this study is to determine the optimum route by taking into account the depth, width, water flow rate, movement of the water in curved regions, and upper and lower currents in order to create proposed TSS model. For this purpose, a region with turning points in the Bosphorus and where accidents are frequent were selected. The two-dimensional potential flow theory was used to determine the velocity and pressure distribution at surface in the region where the accidents were intense, and results of the velocity and pressure distributions obtained with CFD were verified against the analytical data obtained from the potential flow theory. As a result of the study, it has been revealed that the data obtained using the two-dimensional potential flow theory and CFD are compatible with each other, and the flow dynamics obtained using the potential flow theory and/or CFD can be used to determine the dynamic TSS to navigable waterways, channels and rivers in worldwide.

Bridge in Narrow Waterway: Seismic Response and Liquefaction-Induced Deformations

Considerable bridge-ground interaction effects are involved when evaluating the consequences of liquefaction-induced deformations. Due to seismic excitation, liquefied soil layers may result in substantial accumulated permanent deformation due to the sloping ground near the abutments. Ultimately, global response of the bridge is dictated by soil-structure interaction considerations of the entire bridge-ground system. Of particular interest is the scenario of narrow waterways where interaction between downslope deformations at both ends of the bridge takes place. In order to highlight the involved salient mechanisms, this study investigates the longitudinal response of an overall bridge-ground system. For that purpose, a full three-dimensional (3D) finite-element (FE) model is developed, motivated by details of an existing narrow waterway bridge-ground configuration. As such, a realistic multilayer soil profile is considered with interbedded liquefiable/nonliquefiable strata. Specific attention is given to global response of the bridge structure as an integral entity due to ground deformation in the vicinity of the abutments. The overall results indicated that downslope deformations at both ends of the bridge may result in significant interference within the narrow waterway central section. As such, assessment of deformations at each slope separately might lead to unrealistic outcomes. Generally, the analysis technique as well as the derived insights are of significance for the seismic response of bridge systems with downslope ground deformations.

Quantifying Wide-Body Vessel Navigation Delay in Narrow Waterways: A Case Study at the Houston Ship Channel

Quantifying Wide-Body Vessel Navigation Delay in Narrow Waterways: A Case Study at the Houston Ship Channel