Search Results (26)

This study utilized the FVCOM model to establish a hydrodynamic model for the waters from Haikou to Danzhou. Based on this framework, a numerical model for oil spill drift and diffusion was developed using the Lagrangian particle method, incorporating processes such as advection, diffusion, spreading, emulsification, dissolution, volatilization, and shoreline adsorption. Sea experiments involving drifters and dye were conducted to validate the oil spill model. The model was subsequently applied to analyze the impacts of tidal phases and wind fields on oil spill trajectories, predict affected areas, and assess risks to environmentally sensitive zones. The results demonstrate that the hydrodynamic model accurately reproduces the tidal current characteristics of the study area. Validation using drifter and dye experiments confirmed that the model’s predictive error remains within 20%, meeting operational forecasting standards. Potential sources of error include uncertainties in wind–wave–current interactions and discrepancies in windage coefficients between oil spills and drifters. Tidal currents and wind fields were identified as the dominant drivers of oil spill drift and diffusion. Under southerly wind conditions, the oil spill exhibited the largest spatial extent, covering 995.25 km² with a trajectory length of 226.92 km. A sensitivity analysis highlighted the Lingao Silverlip Pearl Oyster Marine Protected Area and Shatu Bay Beach as high-risk regions. The developed model provides critical technical support for oil spill emergency response under diverse environmental conditions, enabling proactive pathway forecasting and preventive measures to mitigate ecological damage. Full article

Oil spills represent a significant environmental hazard, particularly in marine ecosystems, where their impacts extend to coastal infrastructure, biodiversity, and economic activities. This study utilizes GNOME v.47.2 (General NOAA Operational Modeling Environment) and ADIOS2 v.2.10.2 (Automated Data Inquiry for Oil Spills) to simulate and analyze oil spill dynamics in the Romanian sector of the Black Sea, focusing on trajectory prediction, hydrocarbon weathering, and shoreline contamination risk assessment. The research explores multiple spill scenarios involving different hydrocarbon types (light vs. heavy oils), vessel dynamics, and real-time environmental variables (wind, currents, temperature). The findings reveal that lighter hydrocarbons (e.g., gasoline, aviation fuel) tend to evaporate quickly, while heavier fractions (e.g., crude oil, fuel oil #6) persist in the marine environment and pose a higher risk of coastal pollution. In the first case study, a spill of 10,000 metric tons of medium oil (Arabian Medium EXXON) was simulated using GNOME v.47.2, showing that after 22 h, the slick reached the shoreline. Under forecasted hydro-meteorological conditions, 27% evaporated, 1% dispersed, and 72% remained for mechanical or chemical intervention. In the second simulation, 10,000 metric tons of gasoline were released, and within 6 h, 98% evaporated, with only minor residues reaching the shore. A real-world validation case was also conducted using the December 2024 Kerch Strait oil spill incident, where the model accurately predicted the early arrival of light fractions and delayed coastal contamination by fuel oil carried by subsurface currents. These results emphasize the need for future research focused on the vertical dispersion dynamics of heavier hydrocarbon fractions. Full article

Oil spills represent a critical environmental hazard with far-reaching ecological and economic consequences, necessitating the development of sophisticated modelling approaches to predict, monitor, and mitigate their impacts. This study presents a computationally efficient and physically grounded modelling framework for simulating oil spill drift in marine environments, developed using Python coding. The proposed model integrates core physical processes—advection, diffusion, and degradation—within a simplified partial differential equation system, employing an integrator for numerical simulation. Building on recent advances in marine pollution modelling, the study incorporates real-time oceanographic data, satellite-based remote sensing, and subsurface dispersion dynamics into an enriched version of the simulation. The research is structured in two phases: (1) the development of a minimalist Python model to validate fundamental oil transport behaviours, and (2) the implementation of a comprehensive, multi-layered simulation that includes NOAA ocean currents, 3D vertical mixing, and support for inland and chemical spill modelling. The results confirm the model’s ability to reproduce realistic oil spill trajectories, diffusion patterns, and biodegradation effects under variable environmental conditions. The proposed framework demonstrates strong potential for real-time decision support in oil spill response, coastal protection, and environmental policy-making. This paperwork contributes to the field by bridging theoretical modelling with practical response needs, offering a scalable and adaptable tool for marine pollution forecasting. Future extensions may incorporate deep learning algorithms and high-resolution sensor data to further enhance predictive accuracy and operational readiness. Full article

This study investigated advancements in atmospheric forecasting by integrating real-time observational data into the Weather Research and Forecasting (WRF) model through the WRF-Data Assimilation (WRF-DA) framework. By refining atmospheric models, we aimed to improve regional high-resolution wave and hydrodynamic forecasts essential for environmental management. Focused on southern Greece, including Crete, the study applied a 3D-Var assimilation technique within WRF, downscaling forecasting data from the Global Forecast System (GFS) to resolutions of 9 km and 3 km. The results showed a 4.7% improvement in wind speed predictions, with significant gains during forecast hours 26–72, enhancing model accuracy across METAR validation locations. These results underscore the positive impact of the integration of additional observational data on model accuracy. This study also highlights the utility of refined atmospheric models for real-world applications through their use in forcing ocean circulation and wave models and subsequent Digital Twin of the Ocean applications. Two such applications—optimal ship routing to minimize CO₂ emissions and oil spill trajectory forecasting to mitigate marine pollution—demonstrate the practical utility of improved models through what-if scenarios in easily deployable, containerized formats. Full article

Oil spills over land and water bodies are some of the most relevant hazards that should be considered when implementing oil production and transport projects. However, the development of robust, versatile, and efficient tools for carrying out this type of hazard assessment is a challenge for geophysical modellers due to the complexity of the oil flow over hybrid terrain–water surfaces. This work presents a versatile Eulerian approach to simulating the transport of an oil layer flowing over steep terrain that may also be dragged by an underlying water flow, i.e., rivers, lakes, oceans, etc., if it exists. The model allows for the seamless simulation of spills that start on land and eventually impact a water body in a single simulation step. The focus here is paid to the integration of the drag shear stresses between the layers, responsible for the oil spreading over a moving water surface. This drag term is solved using a non-iterative implicit method that allows for robust and efficient solutions even with high coupling between both layers. Two synthetic test cases are simulated to demonstrate the accuracy and robustness of the proposed model, obtaining results that validate the model’s behaviour in high-coupling cases. Finally, the spreading hazard for a realistic oil production project is assessed. The results obtained verify the capability of the model to become a useful tool for oil spill forecasting over hybrid terrain–water surfaces. Full article

This paper presents an original approach to predicting oil slick movement and dispersion at the water surface. Special emphasis is placed on the impact of evolving hydro-meteorological conditions and the thickness of the oil spill layer. The main gap addressed by this study lies in the need for a comprehensive understanding of how changing environmental conditions and oil thickness interact to influence the movement and dispersion of oil slicks. By focusing on this aspect, this study aims to provide valuable insights into the complex dynamics of oil spill behaviour, enhancing the ability to predict and mitigate the environmental impacts of such incidents. Self-designed software was applied to develop and modify previously established mathematical probabilistic models for predicting changes in the shape of the oil trajectory. First, a semi-Markov model of the process is constructed, and the oil thickness is analysed at the sea surface over time. Next, a stochastic-based procedure to forecast the horizontal movement and dispersion of an oil slick in diverse hydro-meteorological conditions considering a varying oil layer thickness is presented. This involves determining the trajectory and movement of a slick domain, which consists of an elliptical combination of domains undergoing temporal changes. By applying the procedure and program, a short-term forecast of the horizontal movement and dispersion of an oil slick provided its trajectory at the Bornholm Basin of the Baltic Sea within two days. The research results obtained are preliminary prediction results, although the approach considered in this paper can help responders understand the scope of the problem and mitigate the effects of environmental damage if the oil discharge reaches sensitive ecosystems. Finally, further perspectives of this research are given. Full article

Douglas Channel is the principal shipping route between the town of Kitimat and the Pacific Ocean. Prediction of near-surface currents is crucial for safe tanker navigation and cleaning-up oil spills. Three years of current velocity data were collected at two moorings located 30 km apart. Spectral, wavelet, and harmonic analysis of measured currents throughout the upper (40-m) and lower (50–358 m) water columns indicated the predominant influence of semidiurnal (SD) tidal currents. In the upper layer, wind and density flows resulted in considerable seasonal and interannual variability of these currents. Analysis of the SD variance reveals three major components: barotropic, coherent baroclinic, and random baroclinic. The predictability of near-surface currents depends on the relative contribution and stability of the first two components. Tidal constants estimated for one year were used to predict currents for two other years; we found that at the mooring closer to the entrance of Douglas Channel, 80 to 89% of the SD energy in the upper layer and 89–93% in the lower layer can be forecasted, while closer to the two channel head, these numbers are smaller: 55–70% and 79–89%, respectively. Full article

Oil spills may have devastating effects on marine ecosystems, public health, the economy, and coastal communities. As a consequence, scientific literature contains various up-to-date, advanced oil spill predictive models, capable of simulating the trajectory and evolution of an oil slick generated by the accidental release from ships, hydrocarbon production, or other activities. To predict in near real time oil spill transport and fate with increased reliability, these models are usually coupled operationally to synoptic meteorological, hydrodynamic, and wave models. The present study reviews the available different met-ocean forcings that have been used in oil-spill modeling, simulating hypothetical or real oil spill scenarios, worldwide. Seven state-of-the-art oil-spill models are critically examined in terms of the met-ocean data used as forcing inputs in the simulation of twenty-three case studies. The results illustrate that most oil spill models are coupled to different resolution, forecasting meteorological and hydrodynamic models, posing, however, limited consideration in the forecasted wave field (expressed as the significant wave height, the wave period, and the Stokes drift) that may affect oil transport, especially at the coastal areas. Moreover, the majority of oil spill models lack any linkage to the background biogeochemical conditions; hence, limited consideration is given to processes such as oil biodegradation, photo-oxidation, and sedimentation. Future advancements in oil-spill modeling should be directed towards the full operational coupling with high-resolution atmospheric, hydrodynamic, wave, and biogeochemical models, improving our understanding of the relative impact of each physical and oil weathering process. Full article

The paper deals with an important issue related to the identification, modelling, and prediction of environmental pollution in aquatic ecosystems of the Baltic Sea caused by anthropopressure. Water ecosystems are in danger nowadays because of the negative influence of chemical releases in seas, oceans, or inland waters. The crucial issue is to prevent the oil spills and mitigate their consequences. Thus, there is a need for methods capable of reducing the water pollution and enhancing the effectiveness of port and marine environment preservation. The challenge in implementing actions to remove and prevent horizontal oil discharge lies in accurately determining its shape and direction of oil spreading. The author employed a self-designed software utilizing modified and developed mathematical probabilistic models to forecast the movement and dispersion of an oil spill in diverse hydrological and meteorological conditions. This involved determining the trajectory and movement of a spill domain, which consists of elliptical sub-domains undergoing temporal changes. The research results obtained are the initial results in the oil spill simulation problem. This approach represents an expanded and innovative method for determining the spill domain and tracking its movement, applicable to oceans and seas worldwide. It expands upon the methodologies firstly discussed, thereby broadening the range of available techniques in this field. A simple model of an oil spill trajectory simulation and a surface oil slick as an ellipse is illustrated using a time-series of selected hydro-meteorological factors that change at random times. The author proposes a Monte Carlo simulation method to determine the extent of an oil spill in an aquatic ecosystem, taking into account the influence of varying hydro-meteorological conditions. A semi-Markov model is defined to capture the dynamics of these conditions within the spill area and develop an enhanced algorithm for predicting changes in the shape and movement of the spill domain under changing these conditions. By applying the algorithm, a simulation is conducted to provide short-term prediction of the oil discharge trajectory in a selected Baltic Sea waterway. To enhance the accuracy of predicting the process of changing conditions, uniformly tested joint datasets from the open sea water area were incorporated. Finally, the potential future prospects and directions for further research in this field are discussed. Full article

This study provides, to the best of our knowledge, the first detailed analysis of how surface oil modifies air–sea interactions in a two-way coupled model, i.e., the coupled–ocean–atmosphere–wave–sediment–transport (COAWST) model, modified to account for oil-related changes in air–sea fluxes. This study investigates the effects of oil on surface roughness, surface wind, surface and near-surface temperature differences, and boundary-layer stability and how those conditions ultimately affect surface stress. We first conducted twin-coupled modeling simulations with and without the influence of oil over the Deepwater Horizon (DWH) oil spill period (20 April to 5 May 2010) in the Gulf of Mexico. Then, we compared the results by using a modularized flux model with parameterizations selected to match those selected in the coupled model adapted to either ignore or account for different atmospheric/oceanic processes in calculating surface stress. When non-oil inputs to the bulk formula were treated as being unchanged by oil, the surface stress changes were always negative because of oil-related dampening of the surface roughness alone. However, the oil-related changes to 10 m wind speeds and boundary-layer stability were found to play a dominant role in surface stress changes relative to those due to the oil-related surface roughness changes, highlighting that most of the changes in surface stress were due to oil-related changes in wind speed and boundary-layer stability. Finally, the oil-related changes in surface stress due to the combined oil-related changes in surface roughness, surface wind, and boundary-layer stability were not large enough to have a major impact on the surface current and surface oil transport, indicating that the feedback from the surface oil to the surface oil movement itself is insignificant in forecasting surface oil transport unless the fractional oil coverage is much larger than the value found in this study. Full article

Oil spills are one of the most hazardous pollutants in marine environments with potentially devastating impacts on ecosystems, human health, and socio-economic sectors. Therefore, it is of the utmost importance to establish a prompt and efficient system for forecasting and monitoring such spills, in order to minimize their impacts. The present work focuses on the numerical simulation of the drift and spread of oil slicks in marine environments. The specific area of interest is the Azemmour estuary, located on Morocco’s Atlantic Coast. According to the environmental sensitivity index (ESI), given its geographical location at the intersection of the World’s Shipping Lines of oil transport, this area, as with many other sites in Morocco, has been classified as a high-risk area for oil spill accidents. By taking into account a range of factors, including the ocean currents, the weather conditions, and the oil properties, detailed numerical simulations were conducted, using the hydrodynamic TELEMAC-2D model, to predict the behavior and spread of an oil spill event in the aforementioned coastal region. The simulation results help to understand the spatial–temporal evolution of the spilled oil, the effect of wind on the spreading process, as well as the coastal areas that are most likely to be affected in the event of an oil spill accident. The simulations were performed with and without wind effects. The results showed that three days after the oil spill only 31% of the spilled oil remained on the sea surface. The wind was found to be the main factor responsible for oil drifting offshore. The results indicated that rapid action is needed to address the oil spill before it causes significant environmental damage and makes the oil cleanup process more challenging and expensive. The results of the present study are highly valuable for the management and prevention of environmental disasters in the Azemmour estuary area. The findings can be used to assess the efficacy of various response strategies, such as containment and cleanup measures, and to develop more effective emergency response plans. Full article

Over the latest decades, oil marine pollution has posed a vital threat for global ocean health, since spillages of any scale are related to environmental, social and financial impacts. The worldwide increase in oil and gas demand, and the parallel rise in oil and gas production, exploiting particularly coastal and offshore marine deposits, have significantly increased the risk of accidental oil release to the sea. In the present study, an operational oil spill model was applied to test the oil dispersive properties and to reveal the relative magnitude of weathering processes, after an accidental oil spill release along the main tanker transportation route in the North Aegean Sea. Numerical simulations were implemented using the OpenOil transport and fate numerical model, a subclass of the OpenDrift open-source trajectory framework. This model integrates algorithms with several physical processes, such as oil entrainment, vertical mixing, oil resurfacing and oil emulsification. The oil dispersion model was coupled to real-time met-ocean forecasts received from NOAA-GFS and CMEMS. Present simulation results have focused on the impact of turbulent kinetic energy, induced by the background flow field, on the horizontal spreading of particles, as well as on the evolution of oil mass balance and oil mass properties. Full article

Scientists in the marine domain process satellite images in order to extract information that can be used for monitoring, understanding, and forecasting of marine phenomena, such as turbidity, algal blooms and oil spills. The growing need for effective retrieval of related information has motivated the adoption of semantically aware strategies on satellite images with different spatio-temporal and spectral characteristics. A big issue of these approaches is the lack of coincidence between the information that can be extracted from the visual data and the interpretation that the same data have for a user in a given situation. In this work, we bridge this semantic gap by connecting the quantitative elements of the Earth Observation satellite images with the qualitative information, modelling this knowledge in a marine phenomena ontology and developing a question answering mechanism based on natural language that enables the retrieval of the most appropriate data for each user’s needs. The main objective of the presented methodology is to realize the content-based search of Earth Observation images related to the marine application domain on an application-specific basis that can answer queries such as “Find oil spills that occurred this year in the Adriatic Sea”. Full article

Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China Sea was hindcast simulated using the oil particle-tracing method. Sea-surface winds from the European Centre for Medium-Range Weather Forecasts (ECMWF), currents simulated from the Finite-Volume Community Ocean Model (FVCOM), and waves simulated from the Simulating WAves Nearshore (SWAN) were employed as background marine dynamics fields. In particular, the oil spill simulation was compared with the detection from Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) images. The validation of the SWAN-simulated significant wave height (SWH) against measurements from the Jason-2 altimeter showed a 0.58 m root mean square error (RMSE) with a 0.93 correlation (COR). Further, the sea-surface current was compared with that from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2), yielding a 0.08 m/s RMSE and a 0.71 COR. Under these circumstances, we think the model-simulated sea-surface currents and waves are reliable for this work. A hindcast simulation of the tracks of oil slicks spilled from the Sanchi shipwreck was conducted during the period of 14–17 January 2018. It was found that the general track of the simulated oil slicks was consistent with the observations from the collected GF-3 SAR images. However, the details from the GF-3 SAR images were more obvious. The spatial coverage of oil slicks between the SAR-detected and simulated results was about 1 km². In summary, we conclude that combining numerical simulation and SAR remote sensing is a promising technique for real-time oil spill monitoring and the prediction of oil spreading. Full article

Several oil spill simulation models exist in the literature, which are used worldwide to simulate the evolution of an oil slick created from marine traffic, petroleum production, or other sources. These models may range from simple parametric calculations to advanced, new-generation, operational, three-dimensional numerical models, coupled to meteorological, hydrodynamic, and wave models, forecasting in high-resolution and with high precision the transport and fate of oil. This study presents a review of the transport and oil weathering processes and their parameterization and critically examines eighteen state-of-the-art oil spill models in terms of their capacity (a) to simulate these processes, (b) to consider oil released from surface or submerged sources, (c) to assimilate real-time field data for model initiation and forcing, and (d) to assess uncertainty in the produced predictions. Based on our review, the most common oil weathering processes involved are spreading, advection, diffusion, evaporation, emulsification, and dispersion. The majority of existing oil spill models do not consider significant physical processes, such as oil dissolution, photo-oxidation, biodegradation, and vertical mixing. Moreover, timely response to oil spills is lacking in the new generation of oil spill models. Further improvements in oil spill modeling should emphasize more comprehensive parametrization of oil dissolution, biodegradation, entrainment, and prediction of oil particles size distribution following wave action and well blow outs. Full article