J. of Marine Env. Eng., Vol. 8, pp. 155-160
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Identifying Coastal Vulnerability
Due to Climate Changes
E. DOUKAKIS*
School of Rural and Surveying Engineering, Higher Geodesy Laboratory
National Technical University of Athens
9 Iroon Polytechniou Str., Zografos, Athens, Greece
related factors. Levels of carbon dioxide,
methane and nitrous oxide gases are rising
mainly as a result of human activities. Carbon
dioxide is being dumped in the atmosphere at
an alarming rate. Since the industrial
revolution, humans have been pumping out
huge quantities of carbon dioxide, raising its
concentration by 30%. These gases are
accumulating in the atmosphere and trapping
the sun’s radiation heat. The increasing
concentrations of greenhouse gases in the
atmosphere are likely to raise the average
temperature of the earth from 2.5 to 5.5o C
this century. The level of the sea is also
expected to rise with warming seas and the
melting of polar ice caps [1]. A pessimistic onemeter rise in sea level by the end of this century
could result in widespread economic,
environmental and social disruption.
The beaches of the world are the
continents’ defense against the rising sea. The
coasts can absorb the storms by changing
Global warming, enhanced beach erosion
and accelerated sea level rise constitute big
threats to the earth’s coastal zones due to
climate changes. Coastal vulnerability can be
identified using the Coastal Vulnerability
Index (CVI) taking into account six risk
variables. This study proposes a new
methodology to compute the CVI using
ranking criteria and weighting factors with
regard to the variables used. An example
proves the validity and usefulness of the
promoted methodology.
1. INTRODUCTION
Evidence is gathering that human activities
are changing the climate and this climate
change could have an important impact on our
lives. The Global temperatures have risen by
0.6o C in the last century and this rise leads to
huge impacts on a wide range of climate
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*E-mail: [email protected]
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their shapes and then rebuilding themselves
during periods of calm seas. Human activity
however interferes with the natural cycles of
the sea. When ground water is over pumped
and sedimentation interferes with ground
water and rivers, subsidence occurs and the
land begins to sink. The more populous the
region becomes, the more likely subsidence
will occur. Where humans interfere with river
systems, sediment is taken out to the sea or
blocked upriver, creating more severe
shoreline erosion and a relative increase in
sea level. The heavy development of beach
resorts and other coastal areas means that
few wetlands have the means and time to
slowly reestablish themselves upland.
Sea level rise and changes in the frequency
and intensity of extreme events (e.g. cyclones,
storm surges, tsunamis etc.) can cause:
a. inundation and displacement of lowlands
b. erosion and degradation of shorelines
c. increased coastal flooding and
d. salinization of estuaries and freshwater
aquifers.
Most coastal areas are vulnerable to such
impacts to some degree and an adaptation
will be necessary. Deltaic areas, small islands,
coastal wetlands and developed sandy shores
appear particular vulnerable to climate
change because of the large investment and
significant sand resources required to
maintain coastal regions and adjoining
infrastructure as sea level rises.
2. METHODS OF ASSESSING
COASTAL VULNERABILITY
Increasing global concern about climate
change and the possible impacts led to the
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establishment of the Intergovernmental Panel
on Climate Change (IPCC) in 1988 to assess
scientific information on different
components of the climate change issue and
also to formulate some reasonable response
strategies. The IPCC defines vulnerability of
a coastal system as the degree to which the
performance and the state of the coastal
system will be adversely affected by the
various agents of climate change [2]. The role
of vulnerability assessment using the IPCC
Common Methodology is to examine a
coastal nation’s ability to cope with the
consequences of global climate change,
including sea level rise [2]. It is therefore
important for a country to understand the
biophysical and socio-economic effects of
climate change and assess the costs and
benefits of alternative responses in order to
improve coastal zone planning and
management.
The prediction of coastal evolution is
not straightforward. There is no standard
methodology and even the kinds of data
required to make such predictions are the
subject of much scientific debate. A
number of predictive approaches have been
used including historical erosion rates,
static inundation, sea level rise induced
erosion, application of sediment dynamics
etc. One of the most common worldwide
method of assessing coastal vulnerability is
the Coastal Vulnerability Index (CVI) [3].
This approach combines the coastal
system’s susceptibility to change with its
natural ability to adapt to changing
environmental conditions and yields a
relative measure of the system’s natural
vulnerability to the effect of sea level rise
[4]. The vulnerability classification is based
upon the relative contributions and
interactions of six risk variables:
I D E N T I F Y I N G C O A S TA L V U L N E R A B I L I T Y D U E T O C L I M AT E C H A N G E S
1. Coastal Slope (CS): it is linked to the
susceptibility of a coast to inundation by
flooding and to the rapidity of shoreline
retreat.
2. Subsidence (S): it is deduced from a
network of tide gauge stations. The
relative sea level change at each locality is
a composite of the eustatic component
and other vertical land motions.
Subsiding coastal areas in excess of the
eustatic rate of sea level rise (SLR), face
greater inundation hazards.
3. Displacement (D): it is a measure of the
past tendency of a shoreline to retreat or
advance due to the SLR. Shores with
accretion have low risk and those with
erosion have correspondingly higher risk.
4. Geomorphology (G): it is associated with
the erosivity risk of a coastal area.
Beaches having silt size geology have
much more erosivity risk than beaches
made of boulders.
5. Wave Height (WH): waves and longshore
currents actively transform the shoreline
via shoreline transport. This variable is
an indicator of the amount of beach
materials that may be moved offshore
and thus be permanently removed from
the coastal sediment system. The risk
variable assigned for wave height is based
on the maximum significant wave height
for each coastal area.
6. Tidal Range (TR): it is linked to both
permanent and episodic inundation
hazards. A large tidal range determines
the spatial extent of the coast that is
acted upon by waves. Areas with large
tidal waves have wide, near zero relief
intertidal zones and are susceptible to
permanent inundation following sea
level rise. Besides, they are susceptible
to episodic flooding associated with
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storm surges, particularly if these
coincide with high tide.
The aforementioned risk variables are
ranked on a linear scale from 1 to 5 in order
of increasing vulnerability due to sea level
rise. [3]. A value of 1 represents the lowest
risk and a value of 5 represents the highest
risk. These six risk variables are used to
formulate the CVI, which can be used to spot
coastal areas that are at risk to erosion and
permanent inundation. Several formulas are
proposed and tested for the derivation of the
CVI [5]. For reasons of completeness, we
represent the six more widely used formulas
parameterized according to our notification:
Product mean:
CVI1 = [CS × S × D × G × WH × TR]/ 6 (1)
Modified product mean (1):
CVI2 = [CS × S × (1/2 G) × (1/2 (WH + TR))] / 4 (2)
Average sum of squares:
CVI3 = [CS2 + S2 + D2 + G2 + WH2 + TR2] / 6 (3)
Modified product mean (2):
CVI4 = [CS × S × D × G × WH × TR] / 52 (4)
Square root of product mean:
CVI5 = √ [CVI1]
(5)
Sum of products:
CVI6 = 4×CS+4×S+4×D+2×G+2×WH+2×TR (6)
The sensitivity analysis of the above listed
CVIs calculation formulas has proved that [6]:
a. T h e p r o d u c t m e a n a n d m o d i f i e d
product mean CVI formulas are highly
sensitive to variations in the classification of the risk variables.
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TABLE 1
Ranking of the risk variables and their weights.
b. The average sum of the squares CVI
formula is insensitive to classification
variations.
c. The square root of product mean CVI
formula is relative insensitive to
variations to one risk factor and
d. The sum of products CVI formula has the
lower
sensitivity
overall
to
misclassification errors and missing data.
One can conclude that CVI 6 is in
preference compared to the rest CVIs and it
is evident that it includes a short of
“weighting factors ” for the six risk
variables. In practical words, the risk
variables associated with the coastal zone
(e.g. coastal slope, subsidence and
displacement) have double effect than the
risk variables associated with the water
dynamics (e.g. wave height, tidal range)
and coastal geomorphology. In our
reasoning, this is a wrong perception for a
general and wide application of assessing
coastal vulnerability using CVI. For
example, consider a microtidal coastal area
(tidal range less than 1 m. in the event of a
3 m storm surge, we will have an excess of
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2 m of the sea water and, consequently,
inundation up to the 2 m height contour
line. It is more than clear that the risk
variables have to be ranked (weighted)
according to their importance using criteria
according to their expected impacts on the
coastal area. The importance of the criteria
is connected with the effects each risk
variable exerts on the beach system. Table 1
lists the six variables, their ranking and
weight factor.
The Coastal Vulnerability Index can then
be calculated using the following formula:
CVI = 6 × CSs + 5 × Ss + 4 × Ds +
3 × Gs + 2 × TRs + 1 × WHs
(7)
Where superscript s denotes the standardized
score that is related to the respective variable.
For example, for the Coastal Slope (CS) the
standardized score reads:
CSs = raw score in the classification
/ maximum score
where maximum score is 5 according to the
classification [5].
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TABLE 2
The proposed CVI compared to existing ones.
Furthermore, we can determine the four
CVI categories, namely, low risk, moderate
risk, high risk and very high risk, on the base
of 25%, 50% and 75% quartiles. In case the
six risk variables lead to a CVI calculation in
a coastal area with a value between the 75%
and 100% quartiles, then the respective
coastal region is characterized “very high
vulnerable” and asks for immediate measures
of protection.
3. RESULTS
To validate the merit of our proposed CVI
calculation, let us consider a coastal region
with all six risk variables to score 3 out of
maximum 5 in the classification. The
calculation of the CVIs, the quartiles and the
characterization of the coastal region are
presented in Table 2.
be used for the characterization of the coastal
areas regarding their vulnerability due to sea
level rise and coastal erosion. Using criteria
of significance regarding the influence of the
six risk variables on the beach environment
and weighting factors, the character of the
coastal vulnerability can be deduced. The
proposed CVI formula is more rational since
it takes into account criteria of importance of
the risk variables used. Consequently, it is
proposed for applications on respective
studies since it is proved to have less
sensitivity to the risk variables. If more risk
variables are to be introduced (than the six
listed), the new variables have to be ranked
accordingly and the proposed CVI can be
used straightforward, thus proving its
robustness.
REFERENCES
[1]
Intergovernmental Panel on Climate Change (2001)
‘Third Assessment Report, Working Group 1 Summary
for Policy Makers’, Geneva, Switzerland.
[2]
Intergovernmental Panel on Climate Change (1996)
‘Climate Change 1995: Impacts, Adaptations and
Mitigation of Climate Change: Scientific-Technical
Analysis, Cambridge University Press, Cambridge, MA.
4. CONCLUSIONS
The results of this study evaluate a new
Coastal Vulnerability Index formulation to
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[3]
Gornitz, V. et all (1977) ‘A coastal hazards data base for
the US West Coast’, Goddard Institute for Space Studies,
NASA, Publ. No 4590.
[4]
Klein, R and R. Nicholls (1999) ‘Assessment of Coastal
Vulnerability to Climate Change, Ambio, 28(2): 182187.
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[5]
Gornitz, V and T, White (1991) ‘The global coastal
hazards data base, pp.214-224, in Future Climate Studies
and Radio-Active Waste Disposal, Safety Studies,
Norwich, England.
[6]
http://cdiac.esd.ornl.gov/epubs/ndp/ndp043/sec9.htm