3.2.2 Operational application

This study's objective was to produce an operational tool to forecast the fate of a possible oil spill in Alexandroupolis gulf and contribute to manage environmental crises from such pollution, after the Burgas-Alexandroupolis pipeline would be constructed. It was clearly very important to make this oil spill dispersion forecasting system user-friendly and easily accessible by all the involved authorities (e.g., the Ministry of Mercantile Marine/Oil Spill Prevention Department, Prefecture of Evros, local port authorities, etc.).

The required input data are the initial time and location of the oil spill, the oil quantity, and quality characteristics (oil type). These data can be introduced to

Figure 8. Graphical and statistical results of the oil spill operational transport model (DIAVLOS).

DIAVLOS forecasting system's Website on-line by the user. The information is processed by the wave-atmospheric-hydrodynamic forecasting system. The oil spill dispersion model runs for 48 hrs and provides hourly images in less than 3–4 minutes. The system can also provide an updated forecast if updated input information is available (in less than 48 hrs). The model computes the hydrodynamic flow and the 3D oil spill evolution and returns to the user the following information (in percentages): surface and subsurface dispersion, evaporation, emulsification (or water content), and beaching of the oil. The output of the model, as Figure 8 shows, contains a graphical representation of the hypothetical oil spill accident area, as well as the horizontal dispersion of the oil, depicted by different colors (surface, subsurface, or beached). Additionally, the University of Athens provides 60-hr high-resolution atmospheric and oceanic forecasting at the region, to facilitate operations to contain oil spill spreading, and beaching and cleaning operations. Wind, wave, and oceanic circulation forecasts are available on DIAVLOS Website by the Ocean Physics and Modelling Group and the Atmospheric Modelling and Weather Prediction Group of the University of Athens. The password-protected and interactive Website (http://diavlos.oc.phys.uoa.gr) was created and offered to public in May 2008, combining efficiency and simplicity.

The system was also tested against field observations of special drifting floats that monitor the fate and evolution of oil spills. These "smart drifters," were especially designed for this project by MARAC Electronics Co. (Greece) in cooperation with the University of the Aegean, co-flowing and transmitting along with the oil slick. The model proved to give satisfactory results and in most cases the forecasting error is quite small, allowing the operational use of the system.

### 3.3 BSB Net-Eco—SLICKNEW

This latest study utilizes another upgraded version of PARCEL and 3D Sea and Oil Slick (SOSM) models, developed by the Aristotle University of Thessaloniki [16, 17]. The newly formalized model was tested in the Aegean Sea [35] and adjusted to the characteristics to the Black Sea, and more particularly to the Azov Sea [36].

#### 3.3.1 Model construction

The model suite comprises of a Lagrangian (tracer) model for the transport and physicochemical evolution of an oil slick [37]. The input requirements of the model are surface wind velocities, air temperature, vertical and horizontal diffusion coefficients, surface currents, wave characteristics (height, period, direction), and, in terms of the oil transport, the initial coordinates of each parcel, its initial volume and mean density and droplet diameter, as well as evaporation rate and parameters relevant to the oil type and identity. The POSEIDON system [19], which is utilized in this modeling effort, provides information on wind speed and direction, atmospheric pressure, air temperature, wave parameters, current speed and direction, water temperature, salinity, dissolved oxygen, chlorophyll-a, and radiation. The observational basis of the system is a network of oceanographic 11 buoys (7 SEAWATCH, 3 Wavescan and 1 deepwater SEAWATCH module), operating in the Aegean Sea since June 1999. The suggested oil spill model utilizes the POSEIDON wave and wind datasets, to produce the sea velocity fields due to currents and waves. The wave, generated near surface, velocity field is computed from the classical Stokes' drift formulae [20], based on the local values of wave height Hs and wave period Ts.

Oil Spill Dispersion Forecasting Models DOI: http://dx.doi.org/10.5772/intechopen.81764

$$U\_m(z) = \left(\frac{\pi \cdot H\_s}{L\_0}\right)^2 \frac{\mathbb{C}\_0}{2} \frac{\cosh\left(2k(H\_s + z)\right)}{\sinh\left(k \cdot H\_s\right)^2} \tag{4}$$

where <sup>L</sup><sup>0</sup> <sup>¼</sup> <sup>g</sup> � <sup>T</sup><sup>2</sup> =2π, C<sup>0</sup> ¼ g � Ts=2π ¼ L0=Ts, and k ¼ 2π=L<sup>0</sup> (π = 3.14). The <sup>s</sup> horizontal diffusion coefficient Dh is estimated adopting the Smagorinsky formula [21, 38] as follows:

$$D\_h = \mathbf{C} \cdot d\mathbf{x} \cdot dy \cdot \left[ \left( \frac{\partial u}{\partial \mathbf{x}} \right)^2 + \mathbf{0}.5 \left( \frac{\partial v}{\partial \mathbf{x}} + \frac{\partial v}{\partial \mathbf{y}} \right)^2 + \left( \frac{\partial v}{\partial \mathbf{y}} \right)^2 \right]^{0.5} \tag{5}$$

where C the horizontal diffusion coefficient. This equation is used to estimate the velocity of each particle, if it is selected via a random number from a sample following the uniform distribution over a range {�Ur, +Ur}

$$U\_r = \sqrt{\frac{\mathbf{6} \cdot D\_h}{\Delta t}}\tag{6}$$

The generation of that sample of random velocity values is based on Monte Carlo sampling, a very common and powerful procedure in simulation theory [37]. The vertical displacement of the oil "particles" is considering the vertical diffusion due to currents and waves [39]:

$$D\_V = D\_{Vc} + D\_{Vw} \tag{7}$$

$$D\_{V\mathfrak{c}} = \mathbb{A} \cdot \mathfrak{h} \cdot \mathcal{W} \tag{8}$$

$$D\_{Vw} = 0.028 \cdot \frac{H\_s^2}{T\_s} \cdot e^{\frac{4\pi}{L\_0}}\tag{9}$$

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi where <sup>λ</sup> <sup>=</sup> 0.001; <sup>h</sup> the water depth; and <sup>W</sup> <sup>¼</sup> <sup>W</sup><sup>2</sup> <sup>þ</sup> <sup>W</sup><sup>2</sup> x y for Wx, Wy the given wind velocities in the x, y axes, respectively. Consequently, the vertical velocity due to buoyancy and diffusion of the oil "particles" is given, similar to the horizontal velocity [37], by

$$W\_r = \sqrt{\frac{6 \cdot D\_V}{\Delta t}}\tag{10}$$

With respect to the input requirements of the slick model, it also requires bathymetry data of the selected area, and a file containing the characterization of the coastal meshes, according to their oil-holding capacity and the open sea boundaries. Based on all that, new horizontal positions of the oil "particles" are estimated; some are "trapped" on the beach, others may be vertically displaced due to buoyancy and diffusion; a fraction of heavy classes of oil may be emulsified over a certain wave curvature, whereas a light oil fraction in sea or on coast may be evaporated. Among the oil weathering processes that take place in the sea is evaporation. It affects the surface oil particles, in sea or on coast. A complete review of various approaches in estimating the evaporated oil is presented in [40]. Thus, adopting the empirical equation of oil evaporation representative of the oil type "Barrow Island, Australia," the evaporation formula used in this model is described by the following equation:

$$\text{9\%}Ev = (4.67 + 0.045 \cdot T) \ln\left(t\right) \tag{11}$$

where T is the air temperature (°C) and t the time (in minutes). Another important oil weathering process is emulsification, which is expressed as a function qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi of the wind velocity <sup>W</sup> expressed as <sup>W</sup> <sup>¼</sup> <sup>W</sup><sup>2</sup> <sup>þ</sup> <sup>W</sup><sup>2</sup> and the temperature <sup>T</sup> [26]: x y

$$Em = \frac{1 - e^{-0.0000056\left(1 + W^2\right) \cdot T}}{1.25} \tag{12}$$

Different oil products react differently to these processes. Lighter oil fractions tend to evaporate, whereas heavier fractions tend to emulsify. Therefore, the model, taking that into account, can simulate different oil types according to their density and buoyancy velocity. The processes of photo-oxidation and biodegradation are not considered in this version of the model, as their effects are more significant at a later stage of a spill's evolution (see Figure 3). All particles are considered to spread at a single location, while they can be released all at the same time (instantaneous discharge), or in sequence over a given period of time (continuous discharge of specified duration).
