Lagrangian modelling of oil concentrations at sea: A sensitivity analysis to the grid resolution and number of Lagrangian elements.

This paper presents a novel method to select the optimal combination of grid resolution and number of Lagrangian elements (LEs) required in numerical modelling of oil concentrations at sea. A sensitivity analysis in terms of grid resolution and the number of LEs, was carried out to understand the uncertainty that these user-dependent parameters introduce in the numerical results. A dataset of 211,200 simulations performed under 400 metocean patterns, 6 initial volumes, 11 grid resolutions, and different numbers of LEs (100 to 500,000), was used to analyze the sensitivity of the model along different Thresholds of Concern.

Modelling the distribution of fishing-related floating marine litter within the Bay of Biscay and its marine protected areas.

Sea-based sources account for 32-50 % of total marine litter found at the European basins with the fisheries sector comprising almost 65 % of litter releases. In the south-east coastal waters of the Bay of Biscay this figure approaches the contribution of just the floating marine litter fraction. This study seeks to enhance knowledge on the distribution patterns of floating marine litter generated by the fisheries sector within the Bay of Biscay and in particular on target priority Marine Protected Areas (MPAs) to reinforce marine litter prevention and mitigation policies.

Deep oil spill hazard assessment based on spatio-temporal met-ocean patterns.

Oil spill risk assessments are important tools for the offshore oil and gas industries to minimize the consequences of deep spills. The stochastic modeling required in this kind of studies, is generally centered on surface transport and based on a Monte Carlo selection of hundreds or thousands of met-ocean scenarios from reanalysis databases, to create an ensemble of spill simulations. We propose a new integrated stochastic modeling methodology including both surface and subsurface transport, based on the specific selection of the most relevant environmental conditions through data-mining techniques.

Mid-long term oil spill forecast based on logistic regression modelling of met-ocean forcings.

Past major oil spill disasters, such as the Prestige or the Deepwater Horizon accidents, have shown that spilled oil may drift across the ocean for months before being controlled or reaching the coast. However, existing oil spill modelling systems can only provide short-term trajectory simulations, being limited by the typical met-ocean forecast time coverage. In this paper, we propose a methodology for mid-long term (1-6 months) probabilistic predictions of oil spill trajectories, based on a combination of data mining techniques, statistical pattern modelling and probabilistic Lagrangian simulations.

A methodology to assess the probability of marine litter accumulation in estuaries.

In this study, a general methodology that is based on numerical models and statistical analysis is developed to assist in the definition of marine litter cleanup and mitigation strategies at an estuarine scale. The methodology includes four main steps: k-means clustering to identify representative metocean scenarios; dynamic downscaling to obtain high-resolution drivers with which to force a transport model; numerical transport modelling to generate a database of potential litter trajectories; and a statistical analysis of this database to obtain probabilities of litter accumulation. The efficacy of this methodology is demonstrated by its application to an estuary along the northern coast of Spain by comparing the numerical results with field data.

Assessing the risk of marine litter accumulation in estuarine habitats.

Rivers and estuaries are among the main entrances of litter to the marine environment. This study characterizes marine litter deposits in three estuaries of the Gulf of Biscay, assesses its potential impact in estuarine habitats based on expert elucidation, and develops a methodology to estimate the associated environmental risk. Litter was ubiquitous in the estuaries of study, mostly represented by plastic debris and sanitary waste.

Operational oil spill trajectory modelling using HF radar currents: A northwest European continental shelf case study.

This paper presents a novel operational oil spill modelling system based on HF radar currents, implemented in a northwest European shelf sea. The system integrates Open Modal Analysis (OMA), Short Term Prediction algorithms (STPS) and an oil spill model to simulate oil spill trajectories. A set of 18 buoys was used to assess the accuracy of the system for trajectory forecast and to evaluate the benefits of HF radar data compared to the use of currents from a hydrodynamic model (HDM).

A high-resolution operational forecast system for oil spill response in Belfast Lough.

This paper presents a high-resolution operational forecast system for providing support to oil spill response in Belfast Lough. The system comprises an operational oceanographic module coupled to an oil spill forecast module that is integrated in a user-friendly web application. The oceanographic module is based on Delft3D model which uses daily boundary conditions and meteorological forcing obtained from COPERNICUS and from the UK Meteorological Office.

Analysis of the reliability of a statistical oil spill response model.

A statistical oil spill response model is developed and validated by means of actual oil slick observations reported during the Prestige accident and trajectories of drifter buoys. The model is based on the analysis of a database of hypothetical oil spill scenarios simulated by means of a Lagrangian transport model. To carry out the simulations, a re-analysis database consisting of 44-year hindcast dataset of wind and waves and climatologic daily mean surface currents is used.

Application of HF radar currents to oil spill modelling.

In this work, the benefits of high-frequency (HF) radar currents for oil spill modeling and trajectory analysis of floating objects are analyzed. The HF radar performance is evaluated by means of comparison between a drifter buoy trajectory and the one simulated using a Lagrangian trajectory model. A methodology to optimize the transport model performance and to calculate the search area of the predicted positions is proposed.