A high-resolution operational forecast system for oil spill response in Belfast Lough. Issue 1 (15th January 2017)

• Record Type: Journal Article
• Authors: Abascal, Ana J.; Castanedo, Sonia; Núñez, Paula; Mellor, Adam; Clements, Annika; Pérez, Beatriz; Cárdenas, Mar; Chiri, Helios; Medina, Raúl
• Is Part Of: Marine pollution bulletin. Volume 114:Issue 1(2017:Jan.)
• Page Start: 302
• Page End: 314
• Publication Date: 2017-01-15
• Subjects: Oil spill modelling -- Operational oceanography -- Forecasting -- Drifting buoys -- Belfast Lough; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2016.09.042
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: 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. Downscaled currents and meteorological forecasts are used to provide short-term oil spill fate and trajectory predictions at local scales. Both components of the system are calibrated and validated with observational data, including ADCP data, sea level, temperature and salinity measurements and drifting buoys released in the study area. The transport model is calibrated using a novel methodology to obtain the model coefficients that optimize the numerical simulations. The results obtained show the good performance of the system and its capability for oil spill forecast. Graphical abstract: Highlights: Development of a local high-resolution operational system for oil spill response An extensive calibration and validation of the system based on observational data is carried out. A methodology is proposed to optimize the oil spill transport model performance. The results demonstrate the capability of the system for oil spill forecast.