Method for identification and simulation of oil spill dispersion in coastal regions

Oil spills at sea pose a serious threat to the environment, affecting marine life and ecosystems while causing economic and social consequences. Predicting and managing these spills requires advanced tools like remote sensing and numerical modeling. This study presents a methodology for detecting and forecasting oil spills along the Brazilian coast using remote sensing data (SAR images) and the MEDSLIK II model. Results show that MEDSLIK II, when coupled with different hydrodynamic model results, predicts the trajectory and dispersion of oil slicks, with GLORYS124v1 products performing the best in the case study. The model's sensitivity to wind and currents emphasizes the need for accurate parameterization. The combination of remote sensing and numerical modeling is effective in detecting and forecasting oil spills, aiding more efficient management and response to environmental emergencies.