Flood Forecast: Case Study of Awba, Ona and Ajibode Rivers...
Transcript of Flood Forecast: Case Study of Awba, Ona and Ajibode Rivers...
Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 9(4):168-175 (ISSN: 2141-7016)
168
Flood Forecast: Case Study of Awba, Ona and Ajibode Rivers in Ibadan, Nigeria
S. O. Adesogan1 and S.E Dada
2 Oluwatobi
1Civil Engineering Department, University of Ibadan, Ibadan, Nigeria
2Consultant in Kaduna, Nigeria
Corresponding Author: S. O. Adesogan
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Abstract
Reduction of risk of flooding depends largely on the amount of information on floods that is available and
knowledge of the areas that are likely to be affected during a flooding event. Therefore, it is necessary to use
modern day techniques in developing measures that will help government and relief agencies in identification of
flood prone areas and in planning against flooding events in the future. There was delineation of flood risk maps
for the basin using remote sensing data and GIS tool. In order to achieve the aim of the study, remotely sensed
images were acquired for the study area for 1984 and 2016; the data were processed and categorized into
various land use based on supervised classification. The Digital Elevation Model (DEM) of the area was
processed in the Arc Map software showing various grids and vectors. Then 1 km squared buffer of the flow accumulation map was super imposed on each other to produce the flood risk maps. Results revealed that
surface water flows southward throughout the drainage basins and large volume of water accumulates at
downstream of the three rivers. Increase in urbanization resulted in decreased vegetation cover leading to
increase flooding. About 23.64 % of the drainage basin was within the high flood risk zone, while about 19.41
of the settlements were within the high-risk zone. It is concluded that proper wastes management should be
encouraged and there should be strict enforcement of non-settlement within the flood risk map zone.
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Keywords: flood risk; mapping; Awba, Ona and Ajibode rivers; Ibadan
INTRODUCTION
In the past four decades, economic losses due to
natural hazards such as, floods disasters have
increased in folds resulting in major loss of human
lives and livelihoods, the destruction of economic and
social infrastructure, as well as environmental damages (Munich Re, 2002). Flooding incidents have
claimed many lives, rendered many others homeless
and disrupted a wide range of environmental factors
and socio-economic activities related to agriculture,
vegetation and sustenance of human and wild life
(Hodo, 2011).
Nigeria has recorded some of the highest death toll in
the West African region. In the northern parts of the
country, entire villages and huge sparse of
agricultural land have been destroyed by flooding (ARB, 2010). In recent times, floods have destroyed
property worth millions of naira in the different areas
of Nigeria. Flooding in urban areas is seriously
becoming an ecological menace in Nigeria as several
coastal areas along the Atlantic ocean, surrounding
cities and river valleys are affected by flooding on a
yearly basis (Jeb and Aggarwal, 2008) Floods have
caused land degradation in some other parts of the
country (Abbas, 2008). The obvious reason for
flooding especially in municipalities and coastal areas
in Nigeria lies in the wide distribution of low-lying
coastal areas and river floodplains, and because these areas have fast become a long standing attractions for
human settlement (Ologunorisa and Abawua, 2005).
Effective flood hazards control is attributable to
properly designed drainage facilities, including storm
drains, highway culverts, bridges, and water quality
and quantity control structures. Design of these
facilities involves hydrologic analysis to determine
the design discharge and hydraulic analysis of the conveyance capacity of the facility (Maidment et al.,
1998). This study therefore focuses on providing
reliable information, which would assist engineers
and other stakeholders in improving flood disaster
management in the study area.
Assessment of floods will require knowledge of flood
risk areas in order to develop prevention as well as
mitigation measures. Flood risk maps are very
essential tools in the identification of flood
vulnerable areas (Jeb and Aggarwal, 2008). Some flood risk assessments have been done in some major
cities in Nigeria but the flooding menace is growing
in its impact as more than half of the states in the
country have been hit by it (Adeoye et al., 2009).
Hence, combining hydrologic and hydraulic
modelling with GIS would not only provide an easy
to understand overview of the flood hazard situation,
but also provide sustainable and viable approach
flood disaster management. This research is
appropriate for the conference in Colloquium Three:
Sustainable Development in Health, Environment
Science, Climate Change, and Project Planning (SDHECP).The contribution of the paper is in the
area of reduction of risk of flooding which depends
Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 9(4): 168-175
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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 9(4):168-175 (ISSN: 2141-7016)
169
largely on the amount of information on floods that is
available and knowledge of the areas that are likely to
be affected during a flooding event. Therefore, it is
necessary to use modern day techniques in
developing measures that will help government and
relief agencies in identification of flood prone areas and in planning against flooding events in the future.
The research limitation is the prediction and does not
include mitigation measures of flood in the study
area.
METHODOLOGY
A flow chart is presented to summarize the research
activities. Data such as rainfall, Satellites imagery and digital maps were collected and analysed
thoroughly.
Figure 1: General Procedure for carrying out the research
The Landsat data used for this study were acquired from the global land-cover website at the University
of Maryland, USA (URL;
http://glcfapp.umiacs.umd.edu:8080/esdi/index.jsp).
The images are thematic mapper (TM) image
acquired on 18th
December 1984, Enhance Thematic
Mapper plus (ETM + ) image acquired on 6th February
2000 and the Operational land Imager (OLI) acquired
on 5th of February 2016 as shown in Table 1. The
satellite data have 30m spatial resolutions and the TM
and ETM Plus images have spectral range of 0.45-
2.35 micro meter with bands 1,2,3,4,5,6,7 and 8 while the Operational Land Imager (OLI) extends to
band 12.
Table 1: Landsat data acquired from the GLC website
of university of Maryland USA S/N Data Type Date Spatial
Resolution
1 Landsat Thematic
mapper (TM)
18thDecember
1984
30 meters
4 Landsat
Operational Land
Imager (OLI)
5thFebruary
2016
30 meters
Data Pre Processing
Due to the fact that both the Landsat ETM+ and Landsat TM images were captured under clear
conditions (0% cloud coverage for both images),
uniform atmospheric conditions within the images
were assumed and no atmospheric corrections were
applied.
All the images were pre-processed by the USGS in
order to rectify any geometric or radiometric
distortions of the image to a level of 1G product. This
correction process employs both digital elevation
models and ground control points to achieve a product that is free from distortions related to the
Earth (e.g. curvature, rotation), satellite (e.g. attitude
deviations from nominal), and sensor (e.g. view angel
effects). The USGS also geometrically corrected and
geo referenced both images to the WGS1984 datum
and Universal Transverse Mercator (UTM) zone 31N
coordinate system (USGS, 2010). The satellite
imageries were pre-processed in order to correct the
error during scanning, transmission and recording of
the data. The pre-processing steps used were:
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a) Radiometric correction to compensate the effects
of atmosphere ;
b) Geometric correction i.e. registration of the image
to make it usable with other maps or images of
the applied reference system ; and
c) Noise removal to remove any type of unwanted noise due to the limitation of transmission and
recording processes.
Data Post Processing
1. Image Composite
A false Color Composite operation were performed
using the Idrisi software and the landsat bands were
combined in the order of band 4,band 3 and band 2
for landsat TM and ETM+ while landsat OLI was
composited in the order of band 4,band4 and band 3
due to change in sensor.
2. Image Classification The False Color Composite was further Classified
using the maximum likelihood classification
technique. A supervised classification was performed
by creating a training sample and based on spectral
signature curve, various land use classes were created
namely; Settlement Vegetation; Cultivation and water
body. The classified map was generated for years
1984; 1990 and 2013 respectively. Ground truthing
was done to verify the result of the classified maps.
3. Hydraulic Map
The data required for the generating the hydraulic map are the drainage pattern, flow dimensions and
flow velocity. The methods involved in generating
the hydraulic map included recognizance survey,
acquisition of drainage map and acquisition of flow
parameters then processed using ArcGIS 10.
DATA ANALYSIS
Series of analysis were performed on the processed
Landsat images, SRTM 90m DEM and the Oyo State
data to generate flood risk maps, population at risk
within the different flood risk zones as well as
detection of changes in vegetation and land cover in the study area. The statistical tools that were used to
analyse the data collected, include descriptive
statistical tools, involving the simple percentages.
The analysis of data was aided with the use of the
computer software, Micro Soft Excel sheet.
Description of Study Area
The study area lies between longitude 3051ꞌ11ꞌꞌE to
3058ꞌ16ꞌꞌE and latitude 7025ꞌ50ꞌꞌN and to 7032ꞌ28ꞌꞌE
and is situated in Akinyele Local Government Area
in Ibadan. It has a total perimeter of 41.35km and an area of 111.67sqkm. It comprises of River Awba,
River Ona and River Ajibode. River Awba drains
westward within and through the University of
Ibadan and has a total length of 3.53km. The inlet and
outlet coordinates of River Awba are 3054ꞌ20ꞌꞌE,
7026ꞌ13ꞌꞌN and 3052ꞌ40ꞌꞌE, 7026ꞌ16ꞌꞌN respectively.
Awba Reservoir has been highly utilized and treated
for the University of Ibadan residents’ consumption.
River Ona within the study area takes it source from
Elebu and drains southwards through International
Institute of Tropical Agriculture (IITA) into Eleyele
reservoir. It has a total length of 14.56km. River Ona
is the primary first order river that drains the whole of
Ibadan city. All other rivers in the city are tributaries of River Ona. The inlet and outlet coordinates of
River Ona within the study area are 3053ꞌ12ꞌꞌE,
7032ꞌ25ꞌꞌN and 3052ꞌ30ꞌꞌE, 7026ꞌ36ꞌꞌN respectively. In
1942, the quest to create a modern water system to
meet the challenge of water scarcity for the emerging
Ibadan metropolis led to the construction of Eleyele
Dam on the main River Ona with a reservoir storage
capacity of 29.5 million litres (Tijaniet al, 2011).
Ajibode river is a major tributary of River Ona with a
total length of 3.76km. The inlet and outlet
coordinate of River Ajibode are 3054ꞌ20ꞌꞌE,
7029ꞌ14ꞌꞌN and 3052ꞌ40ꞌꞌE, 7026ꞌ16ꞌꞌN respectively. Important researches are on River Ajibode as it could
serve as an alternative source of raw water for the
University of Ibadan residents.
Figure 2: Map of the Study Area Showing Awba,
Ona and Ajibode Rivers.
RESULTS AND ANALYSIS
Clipping and Classification of Image
The landsat image was classified into four major land use that includes developed area, wetland, vegetation
and reservoir. The clipped map of the study area is
presented in Figure 3. A total of six LGAs have full
or part of their boundaries within the study area.
These include Akinyele, Lagelu, Ido, Egbeda, Ibadan
Northwest, Ibadan North and Ibadan Northeast
LGAs. A total of about 575 communities are present
within the study area.
Delineation of Drainage Basin
The result of the Terrain processing used to delineate
the drainage basin is presented in figure 4. A total of 44 sub basins were generated from the processing of
the DEM. The largest sub basin had an area of 16.78
km2 while the smallest sub basin had an area of 0.2
km2 at the upstream of river Ona. For proper analysis
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of flood risk mapping in the study area, all the sub
basin area were merged into a single basin area, with
major rivers, being Ona and Ajibode and Awba
stream (figure 5).
Figure 3: Clipped Map of the Study Area
Figure 4: Delineation of Drainage Basin
Figure 5: Map showing merged Drainage Basin
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Flow Direction and Accumulation on DEM
Figure 6 shows the result of the flow direction
analysis performed on the DEM. The figure reveals
that a downward path for all water flowing on the
surface of the area is present in the study area.
Creation of the direction of flow on a surface elevation is the first step in process of producing
stream networks in a study area. The flow direction
would enable the determination of flow accumulation
in different cells within the area. Generally surface
water flows southward, in the study area (Fig 6). As
depicted in fig 7, majority of the study is contributing
to river Ona, having low value of flow accumulation,
while it could be observed in fig 7 that large amount
of water is accumulated in rivers. The white lines
display the stream path for cells with threshold values
of 98,241 to 501,028. The stream network indicates
the path of formation of large body of flowing
surface water in the event of rainfall or the sudden release of huge quantity of water in the study area.
Water discharged through this network will leave at
the lowest part of each of these drainage basins.
Built-up or urban settlements around this stream
network are likely to be inundated when there is a
release of water.
Fig 6: Map showing Flow Direction
Figure 7: Map Showing Flow Accumulation
Stream Buffer Zones and Slope Angle
In order to show those areas that are most vulnerable
to flooding incidence, a buffer was created within
1000 m of the stream network where flow
accumulation is high (Fig 8). The green symbolizes
areas within the 1000m stream buffer zone.
Settlements within the green area are most likely to
be inundated. Another important factor to be
considered in determining vulnerable areas is the
slope steepness of the elevation. Calculation of the
slope angles of the DEM reveals that areas within and
without the stream buffer have varying slope angles.
Thus, it is possible that some areas within the stream
buffer zone are well above water level than other
areas and such areas will be less vulnerable to
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flooding than the later. Fig 9 shows the slope
steepness of the area reclassifies into three categories.
The lower the slope angles of a particular area, the
closer to water level. Thus, areas with slope angles
between 0 – 1.32658 and within the stream buffer are
likely the most vulnerable to water inundation in the event of sudden release of water or rainfall. As shown
in table 2, lowest percentage of the study area are
within the high slope, which implies only few areas
are not vulnerable to floods, which accumulate in low
laying areas with small slope angle.
Table 2: Summary of Slope in the Study Area
Slope Area (km2) Percentage
Low 109.79 34.54
Medium 177.05 55.70
High 31.02 9.76
Total 317.86 100
Figure 8: Map Showing Stream Buffer Zone
Figure 9: Map showing Slope
Extent of Urbanization
Table 3 shows the Changes in land use types in the
study area between 1984 and 2016. The table shows
that the area covered by water body which was 8.20
Square kilometres in 1984 had decreased to 2.26
Square kilometres in 2016 with a percentage decrease of 1.87%. The table also shows that developed area
which was 105.29 Square kilometres in 1984 had
increased to 151.75 Square kilometres in 2016 with a
percentage increase of 14.62%. Furthermore, the
table shows that wetland which was 4.54 Square
kilometres in 1984 had increased to 3.47 Square
kilometres in 2016 with a percentage increase of
2.04%. In addition, vegetation which was 199.77
Square kilometres in 1984 had decreased to 152.77
Square kilometres in 2016 with a percentage decrease
of 14.79%, it could be observed that there was
increase in developed area from urbanization as vegetation cover decreased. This implies that
urbanization is on the rise in the drainage basin,
which would have adverse effect on flooding.
Table 43: Summary of Land Use Change between
1984 and 2016
1984 2016
Area Percentage Area Percentage
%
change
Water
Body 8.20 2.58 2.26 0.71 -1.87
Developed
Area 105.29 33.13 151.75 47.75 14.62
Wetland 4.54 1.43 11.03 3.47 2.04
Vegetation 199.77 62.86 152.77 48.07 -14.79
Total 317.8 100 317.8 100
Fig 10: Land Use Map of the Study Area in 1984
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Fig 11: Land Use Map of the Study Area in 2016
Delineation of Flood Risk Zones
The intersection of the stream buffer zone, the
reclassified slope steepness and the land use
classification for the year 2016 was used to produce
the different flood risk zones (fig 4.10). The overlay
of the settlements and LGA layers distinguishes the
different places in study areas within the risk zones. The summary of the result of the analysis is presented
in table 4, where it is shown that about 23.64 % of the
drainage basin is within the high flood risk zone.
Table 5 also shows that about 19.41 of the
settlements were within the high risk zone, some of
these areas include, Polytechnic Ibadan, Oja Oba,
Apete, OdoOna and Ijokodo.
Figure 12 shows the flood risk maps of the study
areas with settlements and LGAs.
Table 4 Summary of Area within Flood Zones
Flood Risk Zone Area Percentage
Low 155.2 48.84
Medium 87.46 27.52
High 75.14 23.64
Total 317.8 100
Table 5 Summary of Settlement within Flood Risk
zone
Settlements Percentage
Low 133 56.12
Medium 58 24.47
High 46 19.41
Total 237 100
Fig 12: Flood Risk Map of the Study Area
CONCLUSION AND RECOMMENDATIONS
The study revealed that surface water flows
southward throughout the drainage basins and large
volume water accumulates at downstream the three rivers. Furthermore, it was observed there was
increase in developed area from urbanization as
vegetation cover decreased between 1984 and 2016.
This implies that urbanization was on the rise in the
drainage basin and would have adverse effect on
flooding.
The intersection of the generated stream buffer zone,
the reclassified slope steepness and the land use
classification for the year 2016 was used to produce
the different flood risk zones. This distinguished the
different places in study areas within the risk zones. The summary of the result of the analysis revealed
that about 23.64 % of the drainage basin was within
the high flood risk zone, while about 19.41 of the
settlements were within the high risk zone, some of
the areas include, Polytechnic Ibadan, Oja Oba,
Apete, OdoOna and Ijokodo.
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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 9(4):168-175 (ISSN: 2141-7016)
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