Flood Forecast: Case Study of Awba, Ona and Ajibode Rivers ...jeteas.scholarlinkresearch.com/articles/Flood Forecast CONF.pdf · and is situated in Akinyele Local Government Area

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

_________________________________________________________________________________________

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.

__________________________________________________________________________________________

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

© Scholarlink Research Institute Journals, 2018 (ISSN: 2141-7016)

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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:

http://glcfapp.umiacs.umd.edu:8080/esdi/index.jsp


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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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Adeoye, N O, Ayanlade, A and Babatimehin, O.

2009, “Climate change and menace of

floods in Nigerian cities: socio-

economic implications”, Advances in

Natural and Applied Sciences, 3 (3):

369-377.


175

African Research Bulletin (ARB) 2010, “Policy and

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Research Bulletin: Economic, Financial

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Hodo InyangOrok 2011. A Gis-Based Flood Risk

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Flood Forecast: Case Study of Awba, Ona and Ajibode Rivers ...jeteas.scholarlinkresearch.com/articles/Flood Forecast CONF.pdf · and is situated in Akinyele Local Government Area