CHAPTER 7 . The Implications of Oceanographic Chaos for Coastal Management
131
et al. 1996). For reliable predictions it was necessary to introduce other processes previously not incorporated in these models, such as the high turbulence in the free shear
layer shed at the flow separation points (Wolanski et al. 1996). The final simulation,
shown in Anim. 4, reproduces within 80% the size and intensity of the observed eddy.
The Rattray Island study demonstrates that the flow behind a single island leads to
patchiness at horizontal scales varying in time. There is no unique length scale of the island wake because it is continuously changing. Over a few tidal cycles the processes are
even more complex. Indeed, models predict that small eddies merge into large eddies and
that these large eddies can recirculate back and forth around the island and merge in a
process apparently akin to that of strange attractors (see Anim 5 that results from the
model of Furukawa and Wolanski 1998). This leads to a chaotic distribution of vorticity.
Topographically generated patchiness in the flow field does not require that the
obstacle emerges from the water, it also forms in a system of shoals and channels such
as the Dutch Wadden Sea (Riddenrikhof 1995). In its simple form this circulation consists of periodic tidal currents superimposed on a lattice of residual eddies the size of
the chaotic region. This simple representation, valid for the Dutch Wadden Sea, breaks
down when widespread chaotic advection occurs, which happens when the bathymetry
varies significantly within a tidal excursion length (typically a few km). This occurs
commonly throughout the Great Barrier Reef as well as in many rugged coastlines with
headlands and islands. For such rugged systems the flows are fully chaotic. This is shown
in Anim. 6, generated from the model of King and Wolanski (1996b) for the tide- and
wind-driven flows through the Great Barrier Reef. The flow field resembles an everchanging mosaic of eddies, jets and stagnation zones. Model verification is only possible in open waters far from obstacles, where the flows vary smoothly. In the presence
of topographic complexity it is not realistic to ensemble-average to obtain mean currents or mean flushing rates for large areas; every area has its own dynamics.
Chaotic circulation leads to patchiness in the distribution of passive tracers. Shown
in Anim. 7 is the result of two plume releases, one in the open water and the other one
in the reef matrix. It can be seen that the open water plume remains coherent and that
its width increases in time as mixing progresses in all directions. This behaviour is to
be expected from mixing models based on a fairly uniform flow field (Fischer et al.
1979). However the reef matrix plume rapidly becomes chaotic.
To cope with this patchiness, the classical engineering technique would be to use
ensemble-averaging. This would be counterproductive for the users of such models,
e.g. biologists, because chaotic water circulation drives the chaotic distribution of the
biology. Indeed, Hamner and Hauri (1977) noted that water in an headland eddy over
a coral reef contained a different population of zooplankton than did the free stream
water flowing over a sandy bottom. In a process sketched in Anim. 5, the eddy was
ejected back into the free stream when the tides reversed and became a patch of reef
water rich in zooplankton surrounded by plankton-poor shelf waters. The patch retained its reef zooplankton for as long as it was tracked it (a few hours). When many
reefs are present, such as on the Great Barrier Reef and near a rugged coastline, the
coastal sea becomes a mosaic of patches. This chaos is apparent in biological properties (e.g., chlorophyll) measured from ships and satellite (Wolanski 1994).
Ensemble-averaging tlris chaos to produce simple statistics such as a mean value and a
standard deviation for various parameters (e.g. nutrients and chlorophyll) is not useful because each patch has its own ecosystem dyna.m,jcs (Hassel et al. 1991; McCook 1994).
131
et al. 1996). For reliable predictions it was necessary to introduce other processes previously not incorporated in these models, such as the high turbulence in the free shear
layer shed at the flow separation points (Wolanski et al. 1996). The final simulation,
shown in Anim. 4, reproduces within 80% the size and intensity of the observed eddy.
The Rattray Island study demonstrates that the flow behind a single island leads to
patchiness at horizontal scales varying in time. There is no unique length scale of the island wake because it is continuously changing. Over a few tidal cycles the processes are
even more complex. Indeed, models predict that small eddies merge into large eddies and
that these large eddies can recirculate back and forth around the island and merge in a
process apparently akin to that of strange attractors (see Anim 5 that results from the
model of Furukawa and Wolanski 1998). This leads to a chaotic distribution of vorticity.
Topographically generated patchiness in the flow field does not require that the
obstacle emerges from the water, it also forms in a system of shoals and channels such
as the Dutch Wadden Sea (Riddenrikhof 1995). In its simple form this circulation consists of periodic tidal currents superimposed on a lattice of residual eddies the size of
the chaotic region. This simple representation, valid for the Dutch Wadden Sea, breaks
down when widespread chaotic advection occurs, which happens when the bathymetry
varies significantly within a tidal excursion length (typically a few km). This occurs
commonly throughout the Great Barrier Reef as well as in many rugged coastlines with
headlands and islands. For such rugged systems the flows are fully chaotic. This is shown
in Anim. 6, generated from the model of King and Wolanski (1996b) for the tide- and
wind-driven flows through the Great Barrier Reef. The flow field resembles an everchanging mosaic of eddies, jets and stagnation zones. Model verification is only possible in open waters far from obstacles, where the flows vary smoothly. In the presence
of topographic complexity it is not realistic to ensemble-average to obtain mean currents or mean flushing rates for large areas; every area has its own dynamics.
Chaotic circulation leads to patchiness in the distribution of passive tracers. Shown
in Anim. 7 is the result of two plume releases, one in the open water and the other one
in the reef matrix. It can be seen that the open water plume remains coherent and that
its width increases in time as mixing progresses in all directions. This behaviour is to
be expected from mixing models based on a fairly uniform flow field (Fischer et al.
1979). However the reef matrix plume rapidly becomes chaotic.
To cope with this patchiness, the classical engineering technique would be to use
ensemble-averaging. This would be counterproductive for the users of such models,
e.g. biologists, because chaotic water circulation drives the chaotic distribution of the
biology. Indeed, Hamner and Hauri (1977) noted that water in an headland eddy over
a coral reef contained a different population of zooplankton than did the free stream
water flowing over a sandy bottom. In a process sketched in Anim. 5, the eddy was
ejected back into the free stream when the tides reversed and became a patch of reef
water rich in zooplankton surrounded by plankton-poor shelf waters. The patch retained its reef zooplankton for as long as it was tracked it (a few hours). When many
reefs are present, such as on the Great Barrier Reef and near a rugged coastline, the
coastal sea becomes a mosaic of patches. This chaos is apparent in biological properties (e.g., chlorophyll) measured from ships and satellite (Wolanski 1994).
Ensemble-averaging tlris chaos to produce simple statistics such as a mean value and a
standard deviation for various parameters (e.g. nutrients and chlorophyll) is not useful because each patch has its own ecosystem dyna.m,jcs (Hassel et al. 1991; McCook 1994).