Part C | 32.6
738 Part C Coastal Design
a need for confidence limits to be placed on model
results. Too often model results are provided without
a real appreciation for the confidence that can be placed
on those results.
Quantifying Change. There are a number of approaches to quantifying change in response to a marine
outfall. One favored by the authors is the beyond BACI
(or multiple) approach [32.37]. BACI is an acronym
for before, after, control, impact. Sites close to, and
remote from, the outfall are monitored on several occasions both before and after commissioning of the
marine outfall. Perhaps the main reason that this is a favored approach is its emphasis on statistical power and
statistical error.
Statistical Errors. A Type I statistical error occurs
when the results of our analysis incorrectly predicts that
a change has occurred. We can protect against making
such a mistake by specifying the level of significance.
Usually this is set at 5% (equivalent to 95% confidence
limits), i. e., there is a 5% chance that our analysis
makes a Type I statistical error.
A Type II statistical error occurs when the results
of the analysis incorrectly predicts that a change has
not occurred. From an environmental point of view, this
is more insidious than a Type I error because it incorrectly leads us to believe that there is no environmental
problem. It is difficult to protect against a Type II error as this requires a priori knowledge of the variability
in the system being measured. Such knowledge is acquired only after the monitoring is complete. Therefore,
we need to use experience to estimate the system variability and design experiments accordingly. To protect
against making a Type II statistical error, we usually design our experiments to target statistical power above
80%. However, if statistical power is too high, very
small changes become statistically significant and we
question whether such small changes are meaningful. It
is critical to check the statistical power after the experiments have been completed.
Type III statistical errors occur when we arrive at
the correct answer but have asked the wrong question.
Some of the marine components measured to detect change as a result of a new marine outfall include
water quality, sediment quality and community studies
(such as intertidal, plankton, pelagic, benthic, and sessile communities). Marine community studies should
be tailored for specific outfalls and might include:
Intertidal community studies for shoreline or short
outfalls.
Subtidal settlement panel studies for marine outfall
in waters less than about 20 m depth (much deeper
than this and the light attenuation starts to inhibit
the growth of organisms on the settlement panels).
Fish, shellfish, and planktonic communities move
in, and with, marine waters. The variability among
control sites may be as much as the variability between putatively impacted sites and control sites.
Therefore, it may be difficult to isolate the marine
outfall as the cause of change in such communities.
Sediments have been used to assess the accumulation of contaminants and to examine infauna
community variations. Our experience is that such
studies have limited success. Unless the contaminant signal is very strong, it is unlikely to register in
a sediment sample.
Bioaccumulation studies are sometimes recommended as impact assessment indicators. However,
caution is needed when interpreting the results of
such studies because:
– Fish move, and it is not always possible to know
the region from where contaminants were accumulated. This necessitates fish home range
studies, which can be expensive and, perhaps,
inconclusive.
– Species that are caught at one particular time
and location may not be caught at other times
or locations and pooling into higher biological levels may be required. Different species
may accumulate different substances at different
rates and the pooling process may mask potential impacts.
– Moored systems comprising oysters or mussels
are often used in bioaccumulation studies. However, this may involve removing the animals
from their natural habitat thereby, adding stress
to the organisms and confounding the results
that are obtained.
32.6.3 Long-Term Monitoring
The pre- and post-construction monitoring program
will identify whether there has been a step change in
the baseline conditions as a result of the discharge from
the marine outfall. Long-term monitoring is used to
identify whether further change occurs well after the
marine outfall has been commissioned. It can be used
to extrapolate trends and, where necessary, design and
implement an appropriate mitigation strategy to prevent, or reverse, the trend. The three-pronged attack
described in Sect. 32.6.2 is also applicable to long-term
monitoring.
However, there is a temptation to simply implement
the bulk of the pre- and post-construction monitoring
program as part of the long-term monitoring program.
Apart from the expense associated in maintaining a de-
738 Part C Coastal Design
a need for confidence limits to be placed on model
results. Too often model results are provided without
a real appreciation for the confidence that can be placed
on those results.
Quantifying Change. There are a number of approaches to quantifying change in response to a marine
outfall. One favored by the authors is the beyond BACI
(or multiple) approach [32.37]. BACI is an acronym
for before, after, control, impact. Sites close to, and
remote from, the outfall are monitored on several occasions both before and after commissioning of the
marine outfall. Perhaps the main reason that this is a favored approach is its emphasis on statistical power and
statistical error.
Statistical Errors. A Type I statistical error occurs
when the results of our analysis incorrectly predicts that
a change has occurred. We can protect against making
such a mistake by specifying the level of significance.
Usually this is set at 5% (equivalent to 95% confidence
limits), i. e., there is a 5% chance that our analysis
makes a Type I statistical error.
A Type II statistical error occurs when the results
of the analysis incorrectly predicts that a change has
not occurred. From an environmental point of view, this
is more insidious than a Type I error because it incorrectly leads us to believe that there is no environmental
problem. It is difficult to protect against a Type II error as this requires a priori knowledge of the variability
in the system being measured. Such knowledge is acquired only after the monitoring is complete. Therefore,
we need to use experience to estimate the system variability and design experiments accordingly. To protect
against making a Type II statistical error, we usually design our experiments to target statistical power above
80%. However, if statistical power is too high, very
small changes become statistically significant and we
question whether such small changes are meaningful. It
is critical to check the statistical power after the experiments have been completed.
Type III statistical errors occur when we arrive at
the correct answer but have asked the wrong question.
Some of the marine components measured to detect change as a result of a new marine outfall include
water quality, sediment quality and community studies
(such as intertidal, plankton, pelagic, benthic, and sessile communities). Marine community studies should
be tailored for specific outfalls and might include:
Intertidal community studies for shoreline or short
outfalls.
Subtidal settlement panel studies for marine outfall
in waters less than about 20 m depth (much deeper
than this and the light attenuation starts to inhibit
the growth of organisms on the settlement panels).
Fish, shellfish, and planktonic communities move
in, and with, marine waters. The variability among
control sites may be as much as the variability between putatively impacted sites and control sites.
Therefore, it may be difficult to isolate the marine
outfall as the cause of change in such communities.
Sediments have been used to assess the accumulation of contaminants and to examine infauna
community variations. Our experience is that such
studies have limited success. Unless the contaminant signal is very strong, it is unlikely to register in
a sediment sample.
Bioaccumulation studies are sometimes recommended as impact assessment indicators. However,
caution is needed when interpreting the results of
such studies because:
– Fish move, and it is not always possible to know
the region from where contaminants were accumulated. This necessitates fish home range
studies, which can be expensive and, perhaps,
inconclusive.
– Species that are caught at one particular time
and location may not be caught at other times
or locations and pooling into higher biological levels may be required. Different species
may accumulate different substances at different
rates and the pooling process may mask potential impacts.
– Moored systems comprising oysters or mussels
are often used in bioaccumulation studies. However, this may involve removing the animals
from their natural habitat thereby, adding stress
to the organisms and confounding the results
that are obtained.
32.6.3 Long-Term Monitoring
The pre- and post-construction monitoring program
will identify whether there has been a step change in
the baseline conditions as a result of the discharge from
the marine outfall. Long-term monitoring is used to
identify whether further change occurs well after the
marine outfall has been commissioned. It can be used
to extrapolate trends and, where necessary, design and
implement an appropriate mitigation strategy to prevent, or reverse, the trend. The three-pronged attack
described in Sect. 32.6.2 is also applicable to long-term
monitoring.
However, there is a temptation to simply implement
the bulk of the pre- and post-construction monitoring
program as part of the long-term monitoring program.
Apart from the expense associated in maintaining a de-