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Assessing the Impact of Sea Level Rise on Vulnerable Coastal Communities in a Remote Sensing Environment.

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Inundation and the episodic flooding caused by spring tide in low-lying coastal environments are expected to increase due to sea level rise caused by global warming. This development threatens both human settlement and natural habitats within such vulnerable areas. Sea level rise is a significant and growing danger to the coastal communities worldwide. The impact of sea level rise will be more pronounced in developing countries where data for sustainable managing the coastal environment is scarce. This paper presents a comprehensive assessment of the expected impacts of sea level rise within the Dansoman coastal community in Accra, Ghana. Impact of future sea level rise was modeled using SIMclim model, which is based on the modified Bruun rule. The IPCC predicted global scenarios, tidal and wave climates, historic rate of erosion and other geomorphic parameters were model input parameters.Thesimulated results were overlaid on near vertical aerial photographs obtained in 2005 and analysed. It emerged that the shoreline in Dansoman could recede by about 202 m inland by the year 2100 with baseline from 1970-1990, which compared fairly well with an earlier study by Appeaning Addo et al., (2008). The study also revealed that about 84% of the local dwellers in the Dansoman coastal community are aware of the rising sea level in the coastal area. However, a significant percentage of this number do not understand the causes of sea level rise and have poor measures of adapting to the effects of flood disasters. It came out that approximately 645,556 people, 926 buildings and a total area of about 0.78km2 of land are vulnerable to permanent inundation by the year 2100. The study has demonstrated that there will be considerable losses to both life and property by the year 2100 in the Dansoman coastal area in the likely event of sea level rise.
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Remote Sens. 2011, 3, 2029-2050; doi:10.3390/rs3092029
Remote Sensing
ISSN 2072-4292
www.mdpi.com/journal/remotesensing
Article
Impacts of Coastal Inundation Due to Climate Change in a
CLUSTER of Urban Coastal Communities in Ghana,
West Africa
Kwasi Appeaning Addo 1,*, Lloyd Larbi 1, Barnabas Amisigo 2 and Patrick Kwabena Ofori-Danson 1
1 University of Ghana, P.O. Box LG 99, Legon, Accra, Ghana; E-Mails: lloydlarbi@yahoo.com (L.L.);
ofdan@ug.edu.gh (P.K.O.-D.)
2 CSIR Water Research Institute, P.O. Box M. 32, Accra, Ghana; E-Mail: barnyy2002@yahoo.co.uk
* Author to whom correspondence should be addressed; E-Mail: kappeaning-addo@ug.edu.gh;
Tel.: +233-208-169-555.
Received: 19 July 2011; in revised form: 30 August 2011 / Accepted: 2 September 2011 /
Published: 7 September 2011
Abstract: The increasing rates of sea level rise caused by global warming within the 21st
century are expected to exacerbate inundation and episodic flooding tide in low-lying
coastal environments. This development threatens both human development and natural
habitats within such coastal communities. The impact of sea level rise will be more
pronounced in developing countries where there is limited adaptation capacity. This paper
presents a comprehensive assessment of the expected impacts of sea level rise in three
communities in the Dansoman coastal area of Accra, Ghana. Future sea level rises were
projected based on global scenarios and the Commonwealth Scientific and Industrial
Research Organization General Circulation Models—CSIRO_MK2_GS GCM. These were
used in the SimCLIM model based on the modified Bruun rule and the simulated results
overlaid on near vertical aerial photographs taken in 2005. It emerged that the Dansoman
coastline could recede by about 202 m by the year 2100 with baseline from 1970 to 1990.
The potential impacts on the socioeconomic and natural systems of the Dansoman coastal
area were characterized at the Panbros, Grefi and Gbegbeyise communities. The study
revealed that about 84% of the local dwellers is aware of the rising sea level in the coastal
area but have poor measures of adapting to the effects of flood disasters. Analysis of the
likely impacts of coastal inundation revealed that about 650,000 people, 926 buildings and
a total area of about 0.80 km2 of land are vulnerable to permanent inundation by the year
2100. The study has shown that there will be significant losses to both life and property by
the year 2100 in the Dansoman coastal community in the event of sea level rise.
OPEN ACCESS
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Keywords: sea level rise; adaptation; climate change; inundation; coastal erosion; Ghana
1. Introduction
Climate change, as a result of the shifts in the mean state of the climate or in its variability, has
persisted for some time. The earth has warmed and cooled many times since its formation over billions
of years ago [1], which may be due to both natural and human induced changes within the atmosphere
and in land use. Various factors that influence these changes include volcanic eruptions which
ultimately increase carbon dioxide in the atmosphere, changes in the intensity of energy emitted by the
sun and variations in the earth’s position relative to the sun both in its orbit and in the inclination of its
spin axis [2]. Increasing levels of Greenhouse gas has led to a rise in the earth’s average surface
temperature by about 0.7 °C over the past 100 years from about 15 °C before the late 1800s [3].
Greenhouse gas and sulfate aerosols concentrations in the atmosphere have increased as a result of
human activities such as agriculture, deforestation and the use of fossil fuels since the time of the
Industrial Revolution [4]. This phenomenon has resulted in the current crisis of global warming that is
projected to continue considerably in the 21st century, depending on the level of future greenhouse gas
emissions. Future global emissions will depend on population growth, energy sources, regional and
global economic growth [5]. This information has facilitated producing emission scenarios that are
used to project future greenhouse gas concentrations. These scenarios serve as input parameters to
computer generated models of global climate to provide estimates of future climate.
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios of
2000 presents four families of socio-economic scenarios (A1, A2, B1 and B2) that represent different
future world scenarios in two dimensions. They include a focus on economic versus environmental
concerns, and global versus regional development patterns [6]. The A1 storyline and scenario family
describes a future world of very rapid economic growth, global population that peaks in mid-century
and declines thereafter, and the rapid introduction of new and more efficient technologies. The major
underlying themes are convergence among regions, capacity building and increased cultural and social
interactions, with a substantial reduction in regional differences in per capita income [5]. The A1
scenario family develops into three groups that describe alternative directions of technological change
in the energy system. The three A1 groups are distinguished by their technological emphasis. These are
fossil intensive (A1FI), non-fossil energy sources (A1T) and a balance across all sources (A1B) [6].
The A2 storyline and scenario family describes a heterogeneous world. The underlying theme is self
reliance and preservation of local identities. Fertility patterns across regions converge very slowly,
which results in continuously increasing population. Economic development is primarily regionally
oriented and per capita economic growth and technological change more fragmented and slower than
other storylines [5]. The B1 storyline and scenario family describes a convergent world with the same
global population, that peaks in mid-century and declines thereafter, as in the A1 storyline, but with
rapid change in economic structures toward a service and information economy, with reductions in
material intensity and the introduction of clean and resource efficient technologies. The emphasis is on
global solutions to economic, social and environmental sustainability, including improved equity, but
Remote Sens. 2011, 3
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without additional climate initiatives [5]. The B2 storyline and scenario family describes a world in
which the emphasis is on local solutions to economic, social and environmental sustainability. It is a
world with continuously increasing global population, at a rate lower than A2, intermediate levels of
economic development, and less rapid and more diverse technological change than in the B1 and A1
storylines. While the scenario is also oriented towards environmental protection and social equity, it
focuses on local and regional levels [5].
An illustrative scenario was chosen for each of the six scenario groups A1B, A1FI, A1T, A2, B1
and B2 and it is regarded that all should be considered equally sound. The Special Report on Emission
Scenarios (SRES) do not include additional climate initiatives, which implies that no scenarios are
included that explicitly assume implementation of the United Nations Framework Convention on
Climate Change or the emissions targets of the Kyoto Protocol [5]. From these model estimates using
the SRES scenarios, it is projected that a globally averaged warming of 2.4 to 6.4 °C for a scenario
assuming higher emissions of greenhouse gases in the century. It also projects further warming of 1.1
to 2.9 °C by the year 2100 for a scenario assuming lower emissions in which emissions grow slowly,
peak around the year 2050 and then fall [2]. As global warming occurs resulting in thermal expansion
of the upper ocean layer due to the increase in the world's ocean temperature, the sea level is expected
to increase in the near future [7]. It is anticipated that sea level will continue to rise for several
centuries, even if greenhouse gas emissions are stabilized [8], due to long lag times for the deep oceans
to respond. Global warming has also resulted in the continuous melting of ice sheets or increase in
iceberg calving from land-based ice sheets that has contributed significantly to sea-level rise [9].
Studies by [7] identified the impact of sea level rise on future shoreline evolution trend and concluded
that remote sensing methods coupled with archival shoreline data will enable future rates of change to
be predicted. Monitoring the shoreline to detect change and predict its future impact is significant since
they are recognized by the International GeographicData Committee (IGDC) as one of the 27 most
important features [10].
Remote sensing technology has been used to identify, monitor and assess coastal changes in various
places using mapping techniques [11-13]. The mapping methods adopt techniques that extract the
shoreline positions from data sources. The conventional data sources consist of historical maps, aerial
photographs and repeated field measurement, while the current sources are obtained from remote
sensing technologies using airborne, spaceborne and land based techniques. Remote sensing
advancement has thus enabled the provision of a continuous monitoring of the shoreline globally. This
enables shorelines mapped in situ and extracted from aerial photographs to be compared to detect,
measure and analyze change. Historic rate of change information and estimated sea level rise enable
the future shoreline positions over time to be estimated and its impact on the coastal environment
identified. Satellite images have shown that the extent of Arctic sea ice has declined by about 8.5% per
decade from its size in 1979 [2]. According to [14], if the observed increases in ice discharge rates
from the Greenland and Antarctic ice sheets were to increase linearly with global mean temperature
change, this would add a 0.05 to 0.11 m rise for the A1FI scenario over the 21st century. The global
average rate of sea level rise for the past century has been estimated to be about 10 to15 cm, which
could rise to about 1 m over the next century [15]. The effect would vary locally due to prevailing
factors such as isostatic adjustment of the mantle and variations in oceanic level change [3]. Some
coastal areas in the world will thus experience rise above the normal, whilst in other places sea level
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rise will be low. Furthermore, coasts subsidence due to natural or human induced causes will
experience larger relative rises in sea level [16]. In some locations, such as deltas and coastal cities,
this effect can be significant [17]. Increases of extreme sea levels due to rises in mean sea level and
changes in storm characteristics are of global concern to coastal nations and local coastal
environmental managers since they drive significant impact within coastal environments. Future
coastal environment modeling results reveal that both tropical and extra-tropical storm intensity will
increase [14], which implies additional coastal impacts than attributable to sea-level rise alone,
especially for tropical and mid-latitude coastal systems [18].
Changes in other storm characteristics are less certain and the number of tropical and extra-tropical
storms might reduce according to [14]. Similarly, future wave climate is uncertain, although extreme
wave heights will likely increase with more intense storms [19]. Changes in runoff driven by changes
to the hydrological cycle appear likely, but the uncertainties are large [3]. Human modification of the
hydrologic cycle could also affect sea level rise. Sequestration of water on land in reservoirs and
through irrigation losses could exceed amounts transferred seaward by groundwater mining and
increased runoff due to urbanization and deforestation. The net effect of these processes could slow sea
level rise by about 0.9 ± 0.5 mm/yr [20]. The future of the Antarctic ice sheet introduces a major
uncertainty into sea level projections. Global climate models anticipate higher rates of Antarctic
snow/ice accumulation than melting, which would remove water from the ocean and reduce sea
level [21]. According to [22], a large part of the West Antarctic ice sheet is potentially unstable
because it rests on land now below sea level or forms floating ice shelves, which are locally “pinned”
or stabilized by submarine ridges. These prevent rapid discharge of ice from fast-moving ice streams.
Ocean warming could eventually thin and “unpin” these shelves, which would accelerate the calving
of icebergs into the ocean and thus increase the sea level. This process, although considered very
unlikely, would have devastating consequences on low-lying coastal areas globally should it
occur [23].
As sea level rises, material on sandy shorelines is eroded from the upper beach and deposited on the
near-shore ocean bottom [24]. Consequently the ocean moves landwards or the shoreline recedes. It is
generally accepted that the coastline will retreat horizontally 50 to 100 times the vertical sea level
rise [25]. Hence, the predicted global sea-level rise would cause a coastal recession of sandy beaches
of 4.5 to 88 m by 2100 in many places around the world [25]. The most obvious outcome of sea level
rise is the permanent inundation of coastal areas. Over time inundation changes the position of the
coastline and drowns natural habitats and human structures. Inundation can also exacerbate coastal
erosion by transporting submerged sediment offshore and extend the effects of coastal flooding by
allowing storm waves to act further inland. Apart from relative sea level rise, other coastal
environmental factors also influence inundation. They include sediment availability, beach profile
gradient and the geomorphology of the shoreline. Although both coastal inundation and beach erosion
hasten shoreline retreat, they are however two distinct processes [26]. Unlike inundation, which
drowns land areas, erosion redistributes sediment from the onshore to offshore areas. Sea level rise
does not directly erode beaches and coastal areas. Rather, rising sea levels act as a swelling tide that
allows waves to act further up the beach profile and permits larger waves to reach the coast [26].
Beach erosion is intensified in areas affected by inlets or where the construction of groins and
breakwaters disrupts longshore drift [3].
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The threat of sea level rise calls for concerted efforts in the coastal communities, especially in the
developing nations where geospatial data for effective coastal environmental monitoring are scarce [7],
to improve their resilience to the impacts of coastal hazards. Developing pragmatic policies to
sustainably manage the local coastal environment in developing nations has been influenced by the
lack of reliable information on the expected impact of sea level rise on the coastal environment. This
development has also affected the adaptation technique to be adopted for the coastal environment.
Also, potential constraints to adaptation techniques are poorly understood [27]. This raises long-term
questions about the implications of ‘hold the line’ versus ‘retreat the line’ adaptation policies and,
more generally, how best to approach coastal spatial planning. While shoreline management is starting
to address such issues for the 21st century [28], the long timescales of sea-level rise suggest that
coastal management, including spatial planning, needs to take a long-term view on adaptation to
sea-level rise and climate change. This paper presents results of a comprehensive assessment of the
expected impacts of sea level rise within the Dansoman coastal area in Accra, Ghana.
1.1. Study Area
The study area (Figure 1), which could be described as an industrial, ecological and a residential
area is experiencing coastal erosion and inundation. The area spans about 3.06 km and is located at
latitude 5.3180°N and longitude 0.10010°W along the Gulf of Guinea. It is characterized by a gently
sloping shoreline and sandy beach. Dansoman, similar to most parts of the Accra coast, has relatively
an open coast that enables considerably strong unimpeded swell waves to reach the coast [19] and
break obliquely generating longshore currents [29]. The significant wave height for 50% of the time is
about 1.4 m, the period is between 10 to 15 s and spring high tide is about 1.26 m [30]. The study area
comprises Panbros, Grefi and Gbegbeyise communities and experiences recurrent inundation as a
result of episodic spring tides. A major salt industry that supplies salt to the entire West Africa region
is located in the area as well as other small scale businesses like shops, fish landing sites, resort centers
and farms. The area is an important habitat for marine and migratory birds and its destruction will
affect approximately 35,000 waterfowl [31]. Flooding of the saltpans will also swell the unemployment
problems in the area. It is reported that the shoreline in Accra could recede between approximately
320 m to 610 m inland by the year 2250 [7]. This is expected to affect significant proportion of coastal
infrastructure and the inhabitants. However, knowledge about the effect of sea level rise on the local
communities is scanty. This is because few studies have unambiguously quantified the relationships
between observed coastal land loss and the rate of sea-level rise at the local scale.
Dansoman is experiencing gradual coastal submersion and periodic inundation caused by spring
tides. It is unclear as to what extent these losses are associated with relative sea-level rise due to
subsidence, and other human drivers of land loss, and to what extent they result from global warming.
Historic sea level rise in the study area is about 2 mm/yr that is expected to rise to about 6 mm/yr in
the next century [7]. Evidence of sea level rise has been reported by various authors [32-35]. The
historic rate of erosion in Accra is about 1.13 m/yr ± 0.17 m/yr and future predictions for the next 250
years indicate that the extent of destruction of coastal infrastructure could be disastrous [7]. The long
term erosion trend is due to relative sea level rise, deficit in sediment budget for littoral transport,
orientation of the shoreline and anthropogenic influences [7]. Coastal erosion has resulted in exposed
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rock substratum [36], collapsed about 17 coastal buildings within a period of 26 years [37] and
destroyed natural fish landing sites [38].
Figure 1. The study area (source [39]).
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2. Methodology
Data for this study include digital map and 2005 near vertical aerial photographs obtained from the
centre for remote sensing and GIS (CERGIS) in Ghana, 1904 bathymetric map produced for the Ghana
Ports and Harbours Authority from planetable surveys (onshore) and echo sounding (offshore, last
revision in 1992), 2000 population and housing census from the Ghana Statistical Services Authority,
wind climate from the Svašek Hydraulics in the Netherlands, and IPCC sea level rise scenarios
from [5]. The mapping methods adopt techniques that extract the shoreline on historical maps, aerial
photographs and in situ. Selecting a particular method for mapping is influenced by factors such as the
level of accuracy required, type of output desired, method of ground control point collection,
availability of funding and/or equipment, and the method to be adopted to analyze the shoreline
change. Studies by [7] determined the positional accuracies of the shoreline on the maps and
concluded that the maps are reliable for shoreline change analysis.
2.1. Shoreline Mapping
In situ mapping of the shoreline position using physical survey methods involved determining the
HWL proxy with reference to an established control point. Using the Real Time Kinematics Global
Position System (RTK-GPS) method enabled the 3D coordinates of the shoreline proxy to be obtained.
Two GPS receivers SOKKIA GSR2700 ISX in conjunction with an AllegroCX_36506 data logger
were used for the survey. One stationary receiver served as a reference base station, while the other
receiver was used as a rover. The data was collected by moving a monocycle equipped with a GPS unit
directly along the shoreline at a constant speed and continuously tracking a roving antenna relative to
the static base station. The coordinates were collected at specified time intervals, allowing real-time
digitization of the proxy, and each epoch of data collected is processed to create a string of point
coordinates representing the shoreline. The beach profile was also mapped using the RTK method to
determine the dune height. This enabled topographic information obtained from [7] to be validated.
Shoreline position on the 2005 digital map was digitized onscreen in Geographic Information System
(GIS) environment. The identified HWL mapped facilitated the identification of the erosion trend in
the study area. The revised 1992 bathymetric map was converted into digital format to facilitate
analysis in GIS. The marked positions of the seabed with their spot heights on the 1992 revised
bathymetric map were manually digitized. The historic map was placed on a digitizing board and the
points mapped using the sensitive digitizing puck. The point mode method was adopted over the
stream mode since it reduces coordinate resolution uncertainty [19] and according to [40] it is the
preferred method when precise digitizing is required. The Ghana meter grid coordinate system was
adopted for the maps.
2.2. Modeling Techniques
Numerical and geometric models have been developed that incorporate the laws of physics, climate
data and sea level rise information. The modeled results enable various analyses that have increased
scientific understanding into coastal processes. Analysis of sea level change at specific coastal
locations and over short timeframes for modeling involves two components. First, there is the global
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component arising from thermal expansion of ocean water and the transfer of continental water
reservoirs to the ocean. The second is the local component reflecting vertical land movement or
subsidence due to tectonics, isostatic adjustments and sediment compactions [9].
2.3. The Bruun Rule
The Bruun Rule states that the equilibrium profile of a beach-and-dune system is re-adjusted for
a change in sea level [24]. According to this rule, a rise in sea level will cause erosion and
reestablishment of the equilibrium position of the shoreline further inland and described by the
following equation [41]:
Ceq = z l/(h + d) (1)
where Ceq is the equilibrium change in shoreline position, z is the rise in sea level, l is the closure
distance, h is the height of the dune at the site and d is the water depth at closure distance (l/(d + h)
thus gives slope).
Two important drawbacks have been identified with the use of the Bruun rule to model shoreline
change under a trend of rising sea level [41]. First, it gives only the “equilibrium” (or steady-state)
change. However, coastal systems do not adjust instantaneously since there is apt to be some time lag
in the response. Secondly, shoreline retreat, as evidenced by historical data on beach profiles, is apt to
occur in “fits and starts” over time, not as a steady, year-by-year incremental change. This uneven
response of the shoreline is partly a function of the chance occurrence of severe stormy seasons, which
often cause erosion (in contrast, a season of very few, or mild, storms may allow the natural system to
replenish the sediment supply and the shoreline to advance). Cooper et al. [42] also identified
deficiencies in the Bruun model as a “one model fits all” approach that makes it unsuitable for a highly
complex sedimentary environment with significant alongshore sediment transport. The limitations
identified have resulted in the improvement of the Bruun model.
2.4. Modification of Bruun Rule
The Bruun Rule has been modified [41] to add a response time and a stochastic “storminess” factor
as follows:
dC/dt = (Ceq C)/T + S (2)
where t is time, C is the shoreline position relative to that of t = 0, Ceq is the equilibrium value of C, T
is the shoreline response time and S is a stochastically-generated storm erosion factor.
This study adopted the modified Bruun Rule to simulate future shoreline response to the sea level
rise under plausible sea level rise scenarios. Sea level rise was projected using the CoastCLIM
component of the SimCLIM model system [41] and the CSIRO_MK2_GS Global Circulation Model
(GCM) pattern which is already incorporated in SimCLIM. The CoastCLIM model operates on the
principle of the modified Bruun Rule and was validated and a trial experiment performed using
available data.
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2.5. Examining the Shoreline Response to Sea Level Rise
The state of the shore was analyzed from the surveyed results by comparing the 2005 digitized
and the 2009 in situ surveyed shoreline positions, which revealed that the shoreline has migrated
significantly inland. The CoastCLIM model was used to analyze the shoreline responses to various sea
level rise scenarios. By applying selected IPCC scenarios and incorporating data such as site related
parameters and storm characteristics, sea level rise projections were generated for the study area from
1940 to 2100. The study accounted for uncertainties by simulating for the extreme situation, the best
estimate and the low sensitivity scenario. The site related parameters include the shoreline response
time, which governs the responsiveness of the system to sea level rise in a given year; the depth of
material exchange that was computed for using equations by [43] and [44] to represent the best and the
worse case scenarios; the height of the dune that was obtained from [19] and validated from the RTK
GPS survey; and the shoreline residual movement also from [19]. The future shoreline positions in the
Dansoman coastal area were simulated for the years 2025, 2050, 2075 and 2100 with a baseline from
1970–1990 average. The 25 years intervals simulation was done to spread the predictions evenly.
2.6. Assessment of Impacts of Coastal Inundation on the Communities
Two factors were used to assess impacts of coastal inundation on the communities. These were
impacts on socioeconomic systems and impacts on natural systems. These two factors were adopted
due to the prevailing local economic activities and ecology as discussed in Section 1. The simulated
future shoreline positions for the selected periods of 2025, 2050, 2075 and 2100 were overlaid on the
aerial photographs.
2.6.1. Impacts on Socioeconomic Systems
The socioeconomic systems were grouped into two. They are the landuse pattern and the population
at risk. The landuse pattern was further classified into three categories that include the built up area
(defined as areas having buildings), the vegetation zone (defined as areas with vegetation) and the
beach zone (defined as area from the shoreline to the built up zone). The population at risk in the study
area, within a period, was estimated by visually identifying the number of buildings likely to be
affected by the simulated shoreline positions overlaid on the aerial photographs. The results were used
to statistically estimate the number of people at risk to coastal inundation based on the 2000 population
census data using the equation [45]:
Pr = Nb × Ph × Hb (3)
where Pr is the current population at risk, Nb is the estimated number of buildings, Ph is the average
number of persons per household and Hb is the average number of households per building.
The results obtained was used to calculate an average geometric population growth rate by means of
the equation below [45]
r = [(Pi/Po1/t l] × l00 (4)
where r is the geometric population growth rate (%); Po is the initial population (from the 2000 census
data), Pi is the final population and t is the number of years for which the projection is performed.
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The population was projected through the years 2025, 2050, 2075 and 2100, assuming a constant
growth rate of 4.53 [46] and using the equation below [45]:
Pi = Po × (1+r) t (5)
It was also assumed that it is appropriate to use the entire Accra recent growth rate and apply it to a
small subset within the metropolitan area.
2.6.2. Impacts on Natural Ecosystem
The projected mangrove ecosystems under threat from sea level rise in the communities were
estimated for the years 2025, 2050, 2075 and 2100 using the simulated shoreline positions overlaid on
the aerial photographs. Bird species diversity was used to characterize the impacts of coastal
inundation on the natural ecosystem. The key bird species at the coastal area were classified according
to the [47] Red List Classifications.
2.7. Assessment of Flood Risk Awareness
The coastal community’s awareness of flooding in the study area was determined from a structured
questionnaire. The questionnaires were administered to 120 households in the study area projected to
be likely inundated in the next 100 year scenario. Descriptive statistics method was used to analyze the
results from the questionnaires that were administered.
3. Results
The input parameters for the CoastCLIM model used to simulate future shoreline positions are
shown in Table 1. These were obtained from [7] and field measurements. Table 2 provides the
estimated sea level rise and the shoreline positions under the SRES A1FI and B2 scenario.
Table 1. CoastCLIM model input parameter for the Dansoman coastal area.
Input Value
Site location coordinates Lat: 5.52, Long: 0.17
The closure distance, l, (m) 670
The depth of material exchange, d, (m) 4.19
The dune height, h, (m) 2.14
The residual movement (m/y) 1.3
Storm surge cut mean (m) 4.5
Storm surge cut Standard deviation (m) 1.57
GCM pattern CSIRO_MK2_GS
The shoreline response time 5
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Table 2. Estimated long term sea level rise, equilibrium shoreline and the current
shoreline position.
Year
Sea level rise
from SimCLIM
(cm)
Equilibrium
shoreline from
Bruun rule (m)
Current shoreline
with baseline from
1940 (m)
Shoreline position
with baseline from
1970–1990 average (m)
SRES A1FI 2025 6.77 118.96 115.47 63.88
2050 15.73 160.95 157.08 105.49
2075 30.05 208.61 203.34 151.75
2100 46.41 258.42 253.65 202.06
SRES B2 2025 7.17 119.39 115.83 64.24
2050 14.86 160.03 156.55 104.96
2075 23.85 202.04 197.75 146.16
2100 33.74 245.01 241.22 189.63
Table 3. Projected sea level rise (cm) for the 21st century under SRES A1F1 and B2 in study area.
Year Low (cm) Mid (cm) High (cm)
SRES A1F1 2025 2.97 6.77 11.39
2050 7.25 15.73 26.45
2075 14 30.05 50.9
2100 21.22 46.41 79.71
SRES B2 2025 3.18 7.17 12.05
2050 6.46 14.86 25.6
2075 10.14 23.85 41.99
2100 14.04 33.74 60.27
Figure 2. Sea Level Rise Projections based on CSIRO_MK2_GS A1F1.
0
10
20
30
40
50
60
70
80
90
1990
1996
2002
2008
2014
2020
2026
2032
2038
2044
2050
2056
2062
2068
2074
2080
2086
2092
2098
Sea level r ise (cm)
Sea-Level Projections for Dansoman coastal area Based on
the CSIRO_MK2_GS and the A1F1 Emission Scenario
Low
Mid
High
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The shoreline response to sea level rise based on the various scenarios is provided in Table 3
below. Figures 2 and 3 are the sea level projections based on CSIRO_MK2_GS A1F1 and the B2
emission scenarios.
Figure 3. Sea Level Rise Projections based on the B2 emission scenarios.
0
10
20
30
40
50
60
70
1990
1996
2002
2008
2014
2020
2026
2032
2038
2044
2050
2056
2062
2068
2074
2080
2086
2092
2098
Sea leve l rise (cm)
Sea-Level Projections for Dansoman coastal area Based
on the CSIRO_MK2_GS and the B2 Emission Scenario
Low
Mid
High
Figure 4 shows the simulated shoreline positions overlaid on aerial photographs to reveal the
potential impact of flooding on the Dansoman coastal communities that are susceptible to permanent
inundation in future using the various sea level rise projections. Figure 5 shows estimated settlement
and vegetated areas susceptible to permanent inundation in the study area.
Figure 4. Areas susceptible to permanent inundation in the Grefi and Gbegbeyise communities.
Remote Sens. 2011, 3
2041
Figure 5. Settlement (red) and vegetated area (green) susceptible to permanent inundation.
Table 4 presents results on the estimated built up area and vegetation that are likely to be lost within
the study area, while Table 5 shows the estimated coastal population, area and buildings that falls
below various years simulated shoreline positions.
Table 4. Estimated built up area and vegetation to be lost.
Period Landuse pattern Number of spots on map Sum (ha)
1990–2025 Beach 1 4.885
Built up 14 3.732
Vegetation 6 1.342
2025–2050 Built up 18 24.554
Vegetation 9 5.991
2050–2075 Built up 18 25.944
Vegetation 9 6.336
2075–2100 Built up 21 40.047
Vegetation 11 7.815
Table 5. Estimated Population, area and buildings to be lost in the projected years.
Year Estimated population
vulnerable
Estimated number of
buildings vulnerable
Total area
vulnerable (Km2)
SRES A1F1 2025 2,135 85 0.35
2050 28,951 381 0.48
2075 137,114 596 0.62
2100 645,558 926 0.78
SRES B2 2025 2,210 88 0.35
2050 28,724 378 0.48
2075 127,912 556 0.61
2100 589,110 846 0.74
%Study Area Communities
Legend
CSIRO Line s
Along the Coast
Built up
Vegetation
N
1:8000
0.2 0 0.2 0.4 Kilometers
Loc at i on
Loc at i on
%
%
Gbegbeyise
Grefi
1161900 1162800 1163700 1164600 1165500 1166400 1167300 1168200 1169100 1170000 1170900
308700 308700
309600 309600
1161900 1162800 1163700 1164600 1165500 1166400 1167300 1168200 1169100 1170000 1170900
307800 307800
G u l f o f G u i n e a
Type Count Sum _ Ac re s Sum_Hectares
Along the Coast 112.2080 4.9400
Built up 21 98.9550 40.0470
Vegetation 11 19.3100 7.8150
Remote Sens. 2011, 3
2042
Tables 6 and 7 give results on the flood risk awareness of the inhabitants of the coastal communities
obtained from the administered questionnaires. Table 6 presents the percentage of people who have
suffered from the impact of coastal inundation, while Table 7 shows the responses to early warning
signals prior to inundation.
Table 6. Residents who have suffered from the implications of coastal inundation.
Number of respondents Percentage
Suffered from coastal
inundation implication 68 56.7
Not suffered from coastal
inundation implication. 52 43.3
TOTAL 120 100.0
Table 7. Response to early warnings prior to coastal inundation.
Frequency Percentage
Do not receive any early warning prior to inundation 98 81.7
Receive early alarm prior to inundation 22 18.3
Total 120 100.0
Figure 6 presents a pie chart on the perceived causes of inundation sampled from the respondents to
the questionnaires in the study area and Figure 7 shows the residents’ estimation on the measures in
place to mitigate the threat of inundation. Table 8 presents results on the implications of coastal
inundation in the study area as reported by the respondents to the administered questionnaires.
Figure 6. Causes of inundation in the study area.
rainfall
28%
sea leve l rise
70%
storm surge
2%
Cause of Coastal Inundation in the
Dansoman Coastal Communities
R
4
4
a
g
m
s
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a
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o
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. Discussi
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.1. Shoreli
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. 2011, 3
T
a
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on displac
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Figure 7.
A
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able 8. I
m
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d
ings
s
ehold
od
e
to Sea Le
v
e
nds show
n
evel. How
e
r
ease in t
h
k
ably in the
s
in the at
m
rise at the
n
ario. For t
h
e
se values c
a
l area.
A
daptation
m
m
plications
o
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M
For Far
m
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o
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n
in Figure
2
e
ver, the ris
h
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a
coastal ar
e
h
e best sce
n
ould be us
e
m
easures t
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f coastal i
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Examp
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l
lapse of B
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, the next
t
e is expect
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ere. The
B
f of the ce
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a
t is antici
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a of Dans
o
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d when co
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o
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e
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undation i
n
l
es
d Foot Ras
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h
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a
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estock rea
r
S
helters
u
re, Electri
c
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es.
s
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i
u
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t
wo to thre
e
e
d to accel
e
B
2 scenari
o
n
tury (refer
p
ated to wa
r
o
man are 1
c
ted values
n
sidering s
e
e
a level ris
e
n
Dansoma
n
h
es,
r
ing
c
al
i
ty,
e
decades
a
e
rate sharpl
o
also de
p
to Figure
3
r
m the eart
5.73 cm b
y
of 14.86 c
m
ea
-level ris
e
e
.
n
.
Percent
a
responde
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1.7
25.
0
54.
2
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40.
0
55.
0
45.
0
a
re not exp
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y after the
p
icts simil
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). This is
a
h. The like
l
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2050 and
m
by 2050
a
e
in project
s
20
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e of
n
ts (%)
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year 2050
a
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nd 33.74
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or planni
n
4
3
w
a
s
h
e
t
o
g
e
b
y
b
y
n
g
Remote Sens. 2011, 3
2044
4.2. Shoreline Changes and Coastal Inundation
Coastal inundation caused by high waves and gradual inundation by sea level rise within the
Dansoman coastal communities are expected to increase. This will move the shoreline inland and
thereby submerge the coastal lands and properties. From Table 2, shoreline retreat under sea level rise
scenarios with baseline from 1970 to 1990 average is likely to occur at the Panbros, Grefi and
Gbegbeyise communities in the Dansoman coastal area of Accra. The shoreline for the best-case
scenario could recede from 64.24 m in 2025, to 104.96 m in the 2050s, and up to 189.63 m by the year
2100 (refer to Table 2). In the worst-case scenario, there could be a shoreline recession of 151.75 m by
the year 2075 and a major recession of 202.06 m by the year 2100. This corroborate the study by [7],
which reported that between 200 m and 600 m of shoreline will be eroded by next 250 years under sea
level rise scenarios in Accra in the worst case scenario. This implies that over 200 m of coastal land
could be lost in the Accra by 2100. The trend of the shoreline recession scenarios displayed by the
SimCLIM system depict greater recessional rate beyond the year 2050 both for the best case and the
worst case. The projections do not include the additional extent of the periodic spring tides that occur
in the area. This indicates that some areas beyond the 2100 simulated shoreline position are vulnerable
to inundation. The flood period could affect wide areas of land which would also adversely affect a
number of small scale industries, businesses, residents and the mangrove vegetation within the area.
4.3. Impacts on the Coastal Communities and Landuse
The coastal area can be described as an important ecological, industrial site and densely populated
area that extends from Panbros to Gbegbeyise. On the whole, a relatively narrow coastal strip would be
permanently inundated below the 2100 simulated shoreline position. However, flooding due to storms
and high spring tides could periodically engulf a much greater area.
Due to the highly populated nature of the coastal area of Dansoman as reported by [46], a large
population and considerable private property and infrastructure will be potentially at risk to gradual
inundation and high tidal waves. Figure 4 reveals the position of the shoreline for the years 2025,
2050, 2075 and 2100 overlaid on an aerial photograph. The shoreline indicates the baseline from 2005.
Figure 5 further shows the built up areas, mangrove vegetation spots and the beach areas at risk to
gradual inundation of the coast. Under the A1F1 scenario (refer to Table 4) nearly 6.0 ha of vegetated
land and approximately 25.0 ha of built up area are expected to be submerged due to inundation by the
year 2050. This is however expected to increase considerably by the year 2100, where about 8.0 ha of
vegetation land and 40.0 ha of the built up area would be submerged.
4.4. Population
High population densities are presently concentrated near the coastline at Grefi and Gbegbeyise.
The housing structure of the local population in the area is made up of sandcrete buildings which are
indiscriminately built along the coast. These are likely to be destroyed in the event of coastal
inundation. If population density coupled with housing habit should keep on growing at the current
trend in the area, the flood periods will pose a major disaster in the future and evacuation of vulnerable
people would be difficult since the few routes separating the buildings would be choked up with flood
Remote Sens. 2011, 3
2045
waters. From the study, under the A1F1 scenario, it can be observed that an estimated number of about
29,000 people could be displaced by the year 2050 and by the year 2100, nearly 646,000 people could
be affected by inundation in the Grefi and Gbegbeyise communities (refer to Table 5).
The Densu Ramsar site is located close to the Panbros salt industry in the west. The gradual
permanent inundation could destroy the wetland zone which would affect the ecological site in the
coastal area. The site serves as a habitat for migratory bird species of which some are endangered.
Fishing is also likely to be affected since the remaining natural fish landing sites will be destroyed
together with the breeding ground of the fishes by the inundating waters. According to the fishers, they
have experienced decline in fish catch and earnings (refer to Table 8). They attribute one of the reasons
to the inundation problem of the area. This is because the sea is gradually submerging the fish landing
sites in the communities.
4.5. Flood Risk Awareness
From the survey, it emerged that coastal inundation is the major coastal hazard in the communities.
The respondents confirmed that they really have problems of inundation in their area. According to
them, inundation in the coastal community is caused by sea level rise and rainfall. However, majority
of them responded that high tide as a result of sea level rise is the significant cause of inundation. The
situation becomes devastating during the period when they experience spring tide in the area. During
the survey, majority of the respondents emphasized that the severity of the high tides keeps on
increasing every year and the coastal land is rapidly being submerged by gradual inundation.
As indicated in Table 6, about 57% of the population in the study area has suffered flood damage.
The damage caused involved mainly property damage and the displacement of people from their
homes. The properties include houses which are made of sandcrete materials, household chattels like
furniture, television etc., small scale business like bars and shops, domestic farm animals and gardens.
From the respondents interviewed, no deaths were recorded in their families as a result of flooding.
However, most of them reported that there have been incidences of death due to the collapse of
building on some people in the area. There were some few injuries reported.
On the evacuation as a result of inundation, 70% of the respondents have evacuated before. This is
mainly because the flood water inundates their houses and passage routes leaving them with no place
of refuge and shelter. The respondents stressed that this usually happens during the periods when they
experience spring tides. About 27.5% of them reported that they have not evacuated from the place
before. However, they gave reason as living far inland not less than 50 m from the coastline. The
remaining 2.5% did not respond to this question.
With regards to the possible health effects that coastal inundation could have on the residents of the
coastal communities, majority of the respondents, representing 58.3% said they do not think it has
some health effects at all. Their reason is that the sea water kills germs and parasites. Among the
remaining 41.7% who said coastal inundation has a negative health effects, 70.5% said the health
effects are parasitic. This is because the stagnant water breeds mosquitoes which cause malaria. They
also reported of other skin diseases and rashes which affect children rampantly during these seasons of
floods. They suspect the inundated water breeds some parasites that when children walk in them, they
get infections. 22.7% said the health effects are water borne and they mentioned diseases like diarrhea
Remote Sens. 2011, 3
2046
and stomach aches. They gave reason that the sea water transports lots of dirt and sediments from the
sea onto land. They also have refuse dumps along the coastal areas which get flooded and spread the
refuse in the environment thereby affecting their drinking water and food. They stressed that during the
spring tide seasons the residents especially children suffer from diarrhea, cholera and other dirt borne
diseases. The remaining complained of foul air in the environment. The reason given was that the flood
water is unclean, also carries along dead materials and scatters the refuse collected in the vicinity.
From the questionnaire responses, 41.7% said they build sand barriers to adapt to the gradual sea
level rise. Thus, they dig sand from the coastal area and form mould barriers with stones to protect
their structures. However, majority of them said they are ineffective and could not resist the impacts of
the sea as it moves onshore. The barriers collapse. With regards to whether the government supports
the residents of the coastal communities during flood season, most of the respondents said government
does not offer any support, as 80% responded ‘no’ to the question. However a few people said when
there are massive damages in the communities during spring tides, they only receive items like rice,
canned fish and bowls as compensation to the damages caused by the flood water.
The greater proportion of the respondents said that they are expecting a massive disaster caused by
coastal inundation in the near future. This is confirmed by 74.2% of the respondents with only 1.2%
expecting a less disastrous future flood. When asked about the future mitigation measures they are
planning to take individually, 50.8% of them said they will evacuate from the area, 32.5% said they
will move to safer grounds in the same area and the rest mentioned other measures such as sea defense,
mould concrete building and some not even having any plans of future mitigation measures.
5. Conclusions
It has emerged that by the year 2100, the most likely range of sea level rise in the Dansoman
coastal area from model projections is between 21.2 cm–79.7 cm, considering the worst case (SRES
A1F1). The best case (SRES B2) is also projected to be 14.0 cm–60.3 cm. The study concludes that
under the CSIRO_MK2_GS scenario and with reference to the 1970–1990 baseline, by the year 2100,
the most likely recession could be 202.06 m inland, considering the worst case (SRES A1F1). The best
case (SRES B2) is also projected to be 189.63 m inland. The results corroborate the study by [7].
Coastal inundation hazard of Dansoman coastal areas are expected to increase as a result of higher sea
level rise due to climate change. It is projected that about 0.48 km2 of coastal land will be lost by the
year 2050 to permanent inundation with reference the 2005 baseline. Considering the year 2100, it is
likely that a maximum of about 0.78km2 of the coastal land will be lost to permanent inundation in the
coastal area of Dansoman in Accra. This would lead to the displacement of a greater percentage of the
local population due to the relatively high rate of population growth in the community. The number of
buildings likely to be affected by the year 2050 is about 381, while by the year 2100 a total of about
926 houses could be destroyed at the coast. Significant buildings will be destroyed as a result of the
unplanned pattern of physical development. For the coastal vegetation within the study area, it is
projected that a maximum of about 6.0 ha of vegetation would be lost to permanent inundation by the
year 2050 and by the year 2100 the coast area might have lost about 8.0 ha of vegetation. For the built
up areas, a total of about 25.0 ha of land could be permanently inundated by the year 2050. This will
lead to about 378 houses being submerged and destroyed by the sea water within the coastal area. By
Remote Sens. 2011, 3
2047
the year 2100, approximately 99.0 ha of land in the built up areas could be inundated permanently
leading to the destruction of about 926 buildings in the coastal area. Fish landing sites could also
be destroyed.
The large-scale salt industry at Panbros, the Densu delta and the whole communities spanning the
barrier ridge could be severely impacted. Also at risk are thousands of species of animals particularly
birds whose habitats are the wetland vegetation and the Sakumo lagoon in the communities. Human
health of the coastal population suffers from inundation and pollution in terms of food, water quality
and sanitation. Coastal inundation may foster the spread of parasitic and enteric diseases in the
communities through the stagnant flood waters. From the study, it could be realized that, people living
in the Panbros, Grefi and Gbegbeyise communities are aware that the sea is rising and the beaches are
eroding. This has caused some people to leave the coastal communities and many more are ready to
leave. However, most of the people do not know that climate change is one of the factors leading to sea
level rise. From the survey, 92.5% of the respondents confirmed that coastal inundation is the major
problem at the Dansoman coastal communities and they have suffered great losses as a result of
inundation in the area. The study also revealed the fact that inhabitants have no systems in place to
help them adapt to the problem of inundation in the communities.
This study has revealed the significant impact of coastal inundation in the Dansoman coastal
community and how it will influence economic activities. It has also exposed the level of awareness of
the community on coastal flooding and the mitigation measures currently in place.
Acknowledgements
This study was funded by Edward Larbi.
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