With MEDSLIK the oil spill is modelled using a Monte Carlo method. The pollutant is divided into a large number of

Lagrangian parcels, up to 500,000, of equal size. For this work 100,000 parcels were used, with the size of each parcel being 0.01 m3. The advective velocity of each oil parcel is a sum of the mean and turbulent fluctuation components of the drift velocity. The advection of the oil slick is caused by the combined action of currents, wind, as well as the Stoke drift. MEDSLIK uses a drift factor approach, which is considered HSP inhibitor to be the most practical approach for adjusting the advection of the oil slicks coming from low resolution hydrodynamic models. With this method the mean drift velocity of the surface oil is considered to be a weighted sum of the wind velocity and the surface Eulerian velocity field. At each time step, each parcel is given a convective and a diffusive displacement. The www.selleckchem.com/products/ABT-263.html oil spills modelled in MEDSLIK consider a light evaporative component and a heavy non-evaporative component. Emulsification is also simulated, and any viscosity changes in the oil are computed according to the amounts of emulsification and evaporation.

Evaporation of the lighter oil fractions follows Mackay et al. (1980b) algorithm, whereas emulsification uses Mackay et al. (1980a) concepts. Beaching on the coast and absorption depending on the type and nature of the shoreline (see Shen et al., 1987 after Torgrimson, 1980). The MEDSLICK model,

in addition to its successful use in real oil spill incidents, has received inter-comparison data with other oil spill models using surface drifters (Brostrom et al., 2008, De Dominicis et al., 2010 and Zodiatis et al., 2014b). In a third step, DTM and their derivatives, Cell Penetrating Peptide geological data and the current direction used in oil slick simulations were imported into ArcGIS 10’s Iso Cluster Unsupervised Classification package to compile oil spill hazard maps (see Irvin et al., 1997 and Murthy et al., 2003). This is a method of multivariate statistical analysis, searching the relationships among different type of attributes. It is similar to cluster analysis, assigning observations to the same class due to their similar values. It is useful in cases of no pre-existing field data and when the training datasets cannot be accurately specified. In the analysis in this paper the larger weights have been given to the current direction raster and the derivatives of the DTM, because these parameters control the dispersion of oil spills when an accident occurs near the shore. The output rasters corresponding to the hazard maps of the two selected areas (offshore Ierapetra and in Kaloi Limenes-South Heraklion) are classified in four and five classes respectively and are tied to shoreline sensitivity data (see Section 6).