320
T. Soomere
pollution propagation in the marine environment. The forecast is usually provided
for the given location of the source, the amount and the properties of the spilled
oil, and modelled metocean conditions (e.g., French et al. 1997; Reed et al. 1999;
French-McCay 2004; Ambjörn 2008). The results definitely assist in taking countermeasures after an oil spill has occurred. The systematic use of the Lagrangian
approach makes it possible to estimate the probability of a region to be polluted, the
time it takes for the oil to reach a specific site, and the areas that could be a threat for
a given shoreline (Abascal et al. 2010). Sometimes backwards tracking of the drift
allows the origin of the spill to be determined and to catch the guilty party (Ambjörn
2008).
10.1.1 The Hidden Potential of Currents
The technique described in this chapter goes one step further. The goal is to establish for which release sites an oil spill will cause the least damage under the same
hydrometeorological conditions and to develop examples of engineering solutions
for optimizing some important activities accordingly.
Since the drift of oil is also affected by direct wind drag and wave-driven impact,
its adequate description generally presumes that these factors are considered. The
transport induced by wind drag and wave motion is mostly ‘downwind’ or ‘downwave’, respectively, and the odds for an area to be affected are roughly inversely
proportional to its distance from the pollution release site in those directions. The
regions associated with the lowest risk are thus as far ‘upwind/upwave’ from the
vulnerable location as possible. As the impact of wind and waves can be relatively
easily added to the model, the presentation here is limited to the quantification of
the current-driven transport. An example of the combined analysis of current-, windand wave-driven transport is presented in Chap. 11.
The current-driven transport has the largest unused potential for the reduction
of coastal pollution. A pattern of currents is an integral reaction of water masses
to a variety of forcing factors. It is usually highly complicated even if the wind is
stationary. The currents are often directed against wave-induced transport or wind
drag (e.g., Andrejev et al. 2004a; Gästgifvars et al. 2006). The forecast of currentinduced transport of drifters is only reliable within about 0.5 days (Vandenbulcke
et al. 2009). Even small errors in the initial location of drifters can drastically change
the calculated trajectories (Griffa et al. 2004).
A necessary prerequisite for undertaking a systematic search for an optimum
release site is the presence of nontrivial, anisotropic internal dynamics of surface
currents: otherwise different release sites can simply be graded according to their
distance from the vulnerable spots. The anisotropy of transport patterns intrinsically characterizes jet-like currents but has also been shown to hold for sea areas
with seemingly highly random dynamics such as the Baltic Sea (Meier 2007; Lu
et al. 2012). Although trajectories of water particles may be extremely complicated (see Fig. 9.6 in Chap. 9), they are never completely random. For example,
T. Soomere
pollution propagation in the marine environment. The forecast is usually provided
for the given location of the source, the amount and the properties of the spilled
oil, and modelled metocean conditions (e.g., French et al. 1997; Reed et al. 1999;
French-McCay 2004; Ambjörn 2008). The results definitely assist in taking countermeasures after an oil spill has occurred. The systematic use of the Lagrangian
approach makes it possible to estimate the probability of a region to be polluted, the
time it takes for the oil to reach a specific site, and the areas that could be a threat for
a given shoreline (Abascal et al. 2010). Sometimes backwards tracking of the drift
allows the origin of the spill to be determined and to catch the guilty party (Ambjörn
2008).
10.1.1 The Hidden Potential of Currents
The technique described in this chapter goes one step further. The goal is to establish for which release sites an oil spill will cause the least damage under the same
hydrometeorological conditions and to develop examples of engineering solutions
for optimizing some important activities accordingly.
Since the drift of oil is also affected by direct wind drag and wave-driven impact,
its adequate description generally presumes that these factors are considered. The
transport induced by wind drag and wave motion is mostly ‘downwind’ or ‘downwave’, respectively, and the odds for an area to be affected are roughly inversely
proportional to its distance from the pollution release site in those directions. The
regions associated with the lowest risk are thus as far ‘upwind/upwave’ from the
vulnerable location as possible. As the impact of wind and waves can be relatively
easily added to the model, the presentation here is limited to the quantification of
the current-driven transport. An example of the combined analysis of current-, windand wave-driven transport is presented in Chap. 11.
The current-driven transport has the largest unused potential for the reduction
of coastal pollution. A pattern of currents is an integral reaction of water masses
to a variety of forcing factors. It is usually highly complicated even if the wind is
stationary. The currents are often directed against wave-induced transport or wind
drag (e.g., Andrejev et al. 2004a; Gästgifvars et al. 2006). The forecast of currentinduced transport of drifters is only reliable within about 0.5 days (Vandenbulcke
et al. 2009). Even small errors in the initial location of drifters can drastically change
the calculated trajectories (Griffa et al. 2004).
A necessary prerequisite for undertaking a systematic search for an optimum
release site is the presence of nontrivial, anisotropic internal dynamics of surface
currents: otherwise different release sites can simply be graded according to their
distance from the vulnerable spots. The anisotropy of transport patterns intrinsically characterizes jet-like currents but has also been shown to hold for sea areas
with seemingly highly random dynamics such as the Baltic Sea (Meier 2007; Lu
et al. 2012). Although trajectories of water particles may be extremely complicated (see Fig. 9.6 in Chap. 9), they are never completely random. For example,