Search Results (99)

Waterborne transportation serves as a critical pillar of trunk-line freight systems, offering unparalleled advantages in transport capacity, energy efficiency, and cost-effectiveness. As cargo throughput demands escalate, optimizing lock capacity becomes imperative. This study investigates ship sinkage dynamics through computational fluid dynamics (CFD) simulations for a representative inland cargo vessel navigating the Three Gorges on the Yangtze River. We develop a predictive sinkage model that integrates four key hydrodynamic parameters: ship velocity, draft, water depth, and bank clearance, applicable to both open shallow water and lockage conditions. The model enables determination of maximum safe drafts for lock transit by analyzing upstream/downstream water levels and corresponding chamber depths. Our results demonstrate the technical feasibility of enhancing single-lock cargo capacity while maintaining safety margins. These findings provide (1) a scientifically grounded framework for draft control optimization, and (2) actionable insights for lock operation management. The study establishes a methodological foundation for balancing navigational safety with growing throughput requirements in constrained waterways. Full article

Inland waterway transport (IWT) is a key function of river systems worldwide. It is vulnerable to climate change, specifically to discharge extremes, and competes for water with multiple other functions. A clear framework describing its interests to inform decision-making during regular conditions as well as during climate extremes is as yet unavailable in the literature. To address this gap we examine how inland shipping is taken into account in waterway policies in the Netherlands. We apply the frame of reference method to ‘objectify’ current inland waterway transport (IWT) policies, addressing the themes of waterway capacity, safety, service level, and sustainability. By ‘objectifying’ we mean turning the implicit into an explicit ‘object’ of study on the one hand and revealing underlying ‘objectives’ on the other. We show that policies for waterway capacity and service level are well developed, while waterway safety policies are more implicit, and waterway resilience lacks a quantitative decision framework. We furthermore show that current policies mainly focus on regular conditions, leaving it unclear what changes under extreme river discharge conditions. The results provide important insights into shipping-related decision challenges during climate extremes, highlighting aspects that should be developed further to improve the climate resilience of inland shipping. While some of these implications are specific to the Dutch case, the method applied here can also be used for other river systems that support multiple functions. Full article

Aquatic pollution in the Bay of Bengal has become a major environmental issue with long-term impacts on fisheries, biodiversity, and ecosystems. The review paper examines the major pathways, sources, and ecological consequences of aquatic pollution in the Bay of Bengal. Pollutants such as heavy metals, pesticides, petroleum hydrocarbons, and microplastics have been reported at concerning levels in the soil and water in aquatic ecosystems. Rivers act as key routes, transporting pollutants from inland sources to the Bay of Bengal. These contaminants disrupt metabolic and physiological functions in fish and other aquatic species and pose serious threats to food safety and public health through bioaccumulation. Harmful algal blooms (HABs), caused by nutrient enrichment, further exacerbate ecosystem degradation in the Bay of Bengal. The review highlights the immediate need for strengthened pollution control regulations, real-time water quality monitoring, sustainable farming practices, and community-based policy interventions to preserve biodiversity and safeguard fisheries. Full article

The pilot study is devoted to the assessment of both the accumulation and spatial distribution of microplastics in the snow cover of the Zhetysu region. The height of snow cover in the study area varied from 4.0 to 80.5 cm, with a volume of melt water ranging from 1.5 to 143 L. The analysis of 53 snow samples taken at different altitudes (from 350 to 1500 m above sea level) showed the presence of microplastics in 92.6% of samples in concentrations from 1 to 12 particles per square meter. In total, 170 microplastic particles were identified. The main polymers identified by Raman spectroscopy were polyethylene (PE), polypropylene (PP), and polystyrene (PS). These are typical components of plastic waste. The spatial distribution of microplastics showed elevated concentrations near settlements and roads. Notable contaminations were also recorded in remote mountainous areas, confirming the significant role of long-range atmospheric transport. Particles smaller than 0.5 mm dominated, having high aerodynamic mobility and capable of long-range atmospheric transport. Quantitative and qualitative characteristics of microplastics in snow cover have been realized for the first time both in Kazakhstan and in the Central Asian region, which contributes to the formation of primary ideas and future approaches about microplastic pollution in continental inland regions. The obtained results demonstrate the importance of atmospheric transport in the distribution of microplastics. They indicate the need for further monitoring and microplastic pollution analyses in Central Asia, taking into account its detection even in hard-to-reach and remote areas. Full article

The Grand Canal serves as a vital water transportation route, a UNESCO World Cultural Heritage site, and an ecological corridor. It is currently undergoing coordinated transformation through infrastructure development, heritage preservation, and ecological restoration. However, existing research has primarily focused on either cultural heritage conservation or localized ecological issues, with limited attention to the spatial relationship between landscape patterns and ecological quality along the entire corridor. To address this gap, this study examines eight sections of the Grand Canal and develops a gradient analysis framework based on equidistant buffer zones. The framework integrates the Remote Sensing Ecological Index (RSEI) with landscape pattern indices to assess ecological responses across spatial gradients. A Multi-scale Geographically Weighted Regression (MGWR) model is applied to reveal the spatially heterogeneous effects of landscape patterns on ecological quality. From 2013 to 2023, landscape patterns showed a trend toward increasing agglomeration and regularity. This is indicated by a rise in the Aggregation Index (AI) from 91.24 to 91.38 and declines in both patch density (PD) from 8.45 to 8.20 and Landscape Shape Index (LSI) from 199.74 to 196.72. During the same period, ecological quality slightly declined, with RSEI decreasing from 0.66 to 0.57. The effects of PD and Shannon’s Diversity Index (SHDI) on ecological quality varied across canal sections. In highly urbanized areas such as the Tonghui River, these indices were positively correlated with ecological quality, whereas in less urbanized areas like the Huitong River, negative correlations were observed. Overall, the strength of these correlations tended to weaken with increasing buffer distance. This study provides a scientific foundation for the integrated development of ecological protection and spatial planning along the Grand Canal and offers theoretical insights for the refined management of other major inland waterways. Full article

Thunderstorms downbursts can be hazardous during aircraft landing and take-off. A warming climate increases low- to mid-level troposphere water vapor, typically transported from high sea-surface temperature regions. Consequently, the future occurrence and intensity of destructive wind gusts from wet microburst thunderstorms are expected to increase. Wet microbursts are downdrafts from heavily precipitating thunderstorms and are several kilometers in diameter, often producing near-surface extreme wind gusts. Brisbane airport recorded a wet microburst wind gust of 157 km/h in November 2016. Numerous locations in eastern Australia experience warm season (October to March) wet microbursts. Here, eight machine learning techniques comprising forward and backward linear regression, radial basis forward and backward support vector regression, polynomial-based forward and backward support vector regression, and forward and backward random forest selection were employed. They identified primary attributes for increased atmospheric instability by warm moist air influx from regions of high sea-surface temperatures. The climate drivers detected here are indicative of increased future eastern Australian warm season thunderstorm downbursts, occurring as wet microbursts. They suggest a greater frequency and intensity of impacts on aircraft safety and operations affecting major east coast airports, such as Sydney and Brisbane, and smaller aircraft at inland regional airports in southeastern Australia. Full article

Reliable coastal and offshore sediment transport data is a requirement for many engineering and environmental projects including port and harbour design, dredging and beach nourishment, sea shoreline protection, inland navigation, marine pollution monitoring, benthic habitat mapping, and offshore renewable energy (ORE). Novel sediment transport numerical modelling approaches allow engineers and scientists to investigate the physical interactions involved in these projects both in the near and far field. However, a lack of confidence in simulated sediment transport results is evident in many coastal and offshore studies, mainly due to limited access to validation datasets. This study addresses the need for cost-effective sediment validation datasets by investigating the applicability of four new suspended load validation techniques to a 2D model of the south-western Irish Sea. This involves integrating an estimated spatial time series of suspended solids concentration (${SSC}_{solids}$) derived from acoustic Doppler current profiler (ADCP) acoustic backscatter with several in situ water sample-based ${SSC}_{solids}$ datasets. Ultimately, a robust spatial time series of ADCP-based ${SSC}_{solids}$ was successfully calculated in this offshore, tidally dominated setting, where the correlation coefficient between estimated ${SSC}_{solids}$ and directly measured ${SSC}_{solids}$ is 0.87. Three out of the four assessed validation techniques are deemed advantageous in developing an accurate 2D suspended sediment transport model given the assumptions of the depth-integrated approach. These recommended techniques include (i) the validation of 2D modelled suspended sediment concentration (${SSC}_{sediment}$) using water sample-based ${SSC}_{solids}$, (ii) the validation of the flood–ebb characteristics of 2D modelled suspended load transport and ${SSC}_{sediment}$ using ADCP-based datasets, and (iii) the validation of the 2D modelled peak ${SSC}_{sediment}$ over a spring–neap cycle using the ADCP-based ${SSC}_{solids}$. Overall, the multi-disciplinary method of collecting in situ metocean and sediment dynamic data via acoustic instruments (ADCPs) is a cost-effective in situ data collection method for future ORE developments and other engineering and scientific projects. Full article

Serving as critical sustainable transportation infrastructure, inland waterways provide dual socioeconomic and ecological value by (1) facilitating high-efficiency freight logistics through cost-effective bulk cargo transport while stimulating regional economic growth, and (2) delivering essential ecosystem services including flood regulation, water resource preservation, and biodiversity conservation. This study establishes a stakeholder-centered risk assessment framework to enhance decision-making of waterway engineering projects and promote the sustainable development of Inland Waterway Transport. We propose a three-layer approach: (1) identifying key stakeholders in the decision-making stage of waterway engineering projects through multi-dimensional criteria; (2) listing and classifying decision-making risks from the perspectives of managers, users, and other stakeholders; (3) applying the Decision-Making Trial and Evaluation Laboratory (DEMATEL) to prioritize key risks and proposing a risk assessment model based on fuzzy reasoning theory to evaluate decision-making risks under uncertain conditions. This framework was applied to the Yangtze River Trunk Line Wuhan–Anqing Waterway Regulation Project. The results show that the risk ranking is managers, users, and other stakeholders, among which the risk of engineering freight demand is particularly prominent. This suggests that we need to pay attention to optimizing material transportation and operational organization, promote the development of large-scale ships, and realize the diversification of ship types and transportation organizations. This study combines fuzzy reasoning with stakeholder theory, providing a replicable tool for the Waterway Management Authority to address the complex sustainability challenges in global waterway development projects. Full article

Inland water transport, a critical component of integrated transportation systems, relies on the unobstructed status of critical waterways to ensure network efficiency. Firstly, a weighted topological network was constructed based on waterway class and length. The Leiden algorithm was then employed to divide the inland waterway network into communities, with community bridges identified as critical waterways. Finally, attack simulation experiments were conducted to verify the methodology. Results revealed that the Jiangsu inland waterway network exhibits a distinct community structure, and the regional division is closely aligned with the actual river system. The rapid performance degradation under community bridge attacks confirmed the validity of the critical waterway identification method. Furthermore, a recommended method for waterway class assignment was explored in the inland waterway weighting network. The innovative identification and assessment of critical waterways from the perspective of community detection breaks through the limitations of traditional methods that rely on betweenness centrality and waterway class. Vessel traffic flow across different waterway classes was analyzed using the Automatic Identification System (AIS) data, enabling tailored management strategies for critical waterways. This research provides theoretical support for an in-depth understanding of the structure and function of the inland waterway network, guiding policymaking and promoting the efficiency and security of inland water transport. Full article

Alkali-activated slag-like powder (AASP) materials are a novel type of binder prepared by activating slag-like powder (SP) with alkaline activators, providing a sustainable alternative to traditional cement for construction in remote mountainous regions, as well as on islands and reefs far from the inland, reducing transportation costs, shortening construction timelines, and minimizing energy consumption. SP is locally produced from siliceous and calcareous materials through calcining, water quenching, and grinding, exhibiting reactivity similar to that of ground granulated blast-furnace slag. In this study, siliceous sand and ground calcium carbonate powder were utilized to produce SP, with sodium carbonate (Na₂CO₃), sodium hydroxide (NaOH), and their mixture serving as activators. The results indicated that the Ca/Si ratio in SP, along with the dosage of Na₂CO₃ (D_sc) and Na₂O content (N_c) in the activator, significantly affected the compressive strength of AASP materials at both early and late stages. The 28-day compressive strength reached up to 78.95 MPa, comparable to that of alkali-activated slag (AAS) materials. The optimum mix ratio for Na₂CO₃-NaOH based AASP materials was also determined to be 80% D_sc and 8% N_c (C8N2-8). Microscopic analyses were employed to investigate the changes in the macroscopic properties of AASP materials driven by hydration products, chemical group composition, and microstructure. Full article

Consumer-grade graphics processing units (GPUs) offer a potentially affordable and energy-efficient alternative to enterprise-class hardware for real-time image processing tasks, but systematic multi-criteria analyses of their suitability remain rare. This article fills that gap by evaluating the performance, power consumption, and cost-effectiveness of GPUs from three leading vendors, AMD, Intel, and Nvidia, in an inland water transport (ITW) context. The main objective is to assess the feasibility of using consumer GPUs for deep learning tasks involving navigational sign detection, a critical component for ensuring safe and efficient inland transportation. The evaluation includes the use of image datasets of inland water transport signs processed by widely used detector and classifier models such as YOLO (you only look once), ResNet (residual neural network l), and MobileNet. To achieve this, we propose a multi-criteria framework based on a weighted scoring method (WSM), covering 21 different characteristics such as compatibility, resting power, energy efficiency in learning and inference, and the financial threshold for technology adoption. The results confirm that consumer-grade GPUs can deliver competitive performance with lower initial costs and lower power consumption. The findings underscore the enduring value of our analysis, as its framework can be adapted for ongoing comparisons of evolving GPU technologies using the proposed methodology. Full article

As a critical intervention for enhancing inland navigation efficiency, waterway regulation projects profoundly modify riverine hydrodynamic conditions while optimizing navigability. This study employs the MIKE21 hydrodynamic model to establish a two-dimensional numerical framework for assessing hydrological alterations induced by channel regulation in the Hui River, China. Through comparative simulations of pre- and post-project scenarios across dry, normal, and wet hydrological years, the research quantifies impacts on water levels, flow velocity distribution, and geomorphic stability. Results reveal that channel dredging and realignment reduced upstream water levels by up to 0.26 m during drought conditions, while concentrating flow velocities in the main channel by 0.5 m/s. However, localized hydrodynamic restructuring triggered bank erosion risks at cut-off bends and sedimentation in anchorage basins. The integrated analysis demonstrates that although regulation measures enhance flood conveyance and navigation capacity, they disrupt sediment transport equilibrium, destabilize riparian ecosystems, and compromise hydrological monitoring consistency. To mitigate these trade-offs, the study proposes design optimizations—including ecological revetments and adaptive dredging strategies—coupled with enhanced hydrodynamic monitoring and riparian habitat restoration. These findings provide a scientific foundation for balancing navigation improvements with the sustainable management of fluvial systems. Full article

Inland water transportation is regarded as a crucial component of global trade, yet its reliability has been increasingly challenged by uncertainties such as extreme weather, port congestion, and geopolitical tensions. Although substantial research has focused on the structural characteristics of inland water transportation networks, the dynamic responses of these networks to disruptions remain insufficiently explored. This gap in understanding is critical for enhancing the resilience of global transportation systems as trade volumes grow and risks intensify. In this study, percolation theory was applied to evaluate the reliability of the Yangtze River transportation network. Ship voyage data from 2019 were used to construct a complex network model, and simulations of node removal were performed to identify key vulnerabilities within the network. The results showed that the failure of specific nodes significantly impacts the network’s connectivity, suggesting which nodes should be prioritized for protection. This research offers a dynamic framework for the assessment of inland water transportation network reliability and provides new insights that could guide policy decisions to improve the resilience of critical waterway systems. By identifying potential points of failure, this study contributes to the development of a more robust global trade infrastructure. Full article

This study explores the potential of inland navigation as a key component of Poland’s sustainable transportation strategy, focusing on the Opole–Szczecin route. It emphasizes inland waterways as an eco-friendly and efficient alternative to road and rail transport, potentially revitalizing local economies and reducing dependency on more traditional transport modes. The use of the River Information Service (RIS) system is highlighted as to its role in enhancing the logistical efficiency and safety of inland water transport. The research includes a comparative analysis of cargo transport on the Opole–Szczecin route, using road, rail, and inland-waterway options, revealing the advantages of inland-waterway transport in terms of cost-effectiveness and environmental impact. Finally, the paper discusses the challenges and opportunities for the development of inland navigation in Poland, advocating for greater integration with other transport branches through innovative technologies like RIS. Full article

Inland waterway transport is an important mode of transportation for many countries and regions. Route planning optimization can reduce navigation time, avoid traffic congestion, and improve transportation efficiency. In actual operations, many vessels determine their navigation routes based on the experience of their shipowners. When the captain fails to obtain accurate information, experience-based routes may pose significant navigation risks and may not consider the overall economic efficiency. This study proposes a comprehensive method for optimizing inland waterway vessel routes using automatic identification system (AIS) data, considering the geographical characteristics of inland waterways and navigation constraints. First, AIS data from vessels in inland waters are collected, and the multi-objective Peak Douglas–Peucker (MPDP) algorithm is applied to compress the trajectory data. Compared to the traditional DP algorithm, the MPDP algorithm reduces the average compression rate by 5.27%, decreases length loss by 0.04%, optimizes Euclidean distance by 50.16%, and improves the mean deviations in heading and speed by 23.53% and 10.86%, respectively. Next, the Ordering Points to Identify the Clustering Structure (OPTICS) algorithm is used to perform cluster analysis on the compressed route points. Compared to the traditional DBSCAN algorithm, the OPTICS algorithm identifies more clusters that are both detailed and hierarchically structured, including some critical waypoints that DBSCAN may overlook. Based on the clustering results, the A* algorithm is used to determine the connectivity between clusters. Finally, the nondominated sorting genetic algorithm II is used to select suitable route points within the connected clusters, optimizing objectives, including path length and route congestion, to form an optimized complete route. Experiments using vessel data from the waters near Shuangshan Island indicate that, when compared to three classic original routes, the proposed method achieves path length optimizations of 4.28%, 1.67%, and 0.24%, respectively, and reduces congestion by 24.15%. These improvements significantly enhance the planning efficiency of inland waterway vessel routes. These findings provide a scientific basis and technical support for inland waterway transport. Full article