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Density currents generated by marine brine discharges, e.g., from desalination plants, can have a negative impact on marine 6 ecosystems. It is therefore important to accurately predict their behavior. Predictions are often made using computational hydrodynamic 7 models, which should be validated using field or laboratory measurements. This paper focuses on the setup and validation of three-8 dimensional (3D) models for estimating the transport and mixing processes that occur in these types of flows. Through a comprehensive 9 sensitivity analysis based on the reproduction of several laboratory-generated density currents, a set of recommendations are made regarding 10 the modeling aspects, including the domain discretization, the treatment of momentum at the density current source, the hydrostatic 11 hypothesis and the selection of turbulence closure models. Finally, the proposed numerical model setup is validated using different exper-12 imental data showing good agreement in terms of the main variables considered: errors of less than 1.3% for dilution and of 6% for velocity. 13 This study serves as a first step toward the full validation of these 3D hydrodynamic models for the simulation of field-scale density currents.

299685:

No abstract

This paper presents two methodologies to provide short-term and medium-term forecast of oil spill trajectories at local and regional scales. For short-term predictions (within 48 hours), a high-resolution operational oil spill forecast system is developed in Belfast Lough (Northern Ireland). Hydrodynamics are based on a Delft3D model which uses daily boundary conditions and meteorological forcing obtained from Copernicus Marine Environment Monitoring Service (CMEMS) and from the UK Meteorological Office. Downscaled currents and meteorological forecasts are used to provide short-term oil spill fate and trajectory predictions in the Lough using the oil spill numerical model TESEO. The system is integrated in a user-friendly web application that allows end users to launch the oil spill model both in case of pollution threat and for training purposes. For mid-term predictions (15–60 days), a stochastic methodology to provide probabilistic oil spill forecasts is presented and applied to the Bay of Biscay (Northern Spain). The method encompasses the following steps: 1) Classification of representative atmospheric patterns using principal component analysis and the k-means technique; 2) Setup of an autoregressive logistic model taking into account seasonality, covariates, long-term trends and autoregressive terms. In the case of an accident, we sample the evolution of the metocean conditions using the autoregressive model, which provides us with possible evolution patterns for these conditions during the forecasting period. These results are used to force the oil spill transport model TESEO allowing the characterization of trajectories in probabilistic terms. Drifting buoys released in Belfast Lough and observations reported during the Prestige accident have been used to validate the operational system and the medium-term forecasting methodologies.