I n response to the increasing cases of flood causing monumental damage to lives and properties in different parts of the nation particularly, Southwestern Nigeria, the National Space Research and Development Agency (NASRDA) through her southwest Advanced Space Technology Applications Laboratory (ASTAL), Cooperative Information Network (COPINE) mapped out an in-road plan to assess and evaluate the spatial attributes and factors magnifying the impact of flood in Southwest Nigeria as a contribution to the fundamental data sets, frame, and baseline information required to mitigate the devastating impact of flood. More so, the knowledge output provides instruments to formulate robust and sustainable policies.
The terms of reference for this study seeks to examine flooding in relation to social, physical, and socio-economic dimensions. The adaptation/coping strategies coupled with the implementation of mitigation measures and its subsequent evaluation are additional reference points of this research. However, this report divulges spatial characteristics of the region, basin, and morphometric characteristics, thematic data generation and flood vulnerability map at the sub-basin level. Therefore, this phase of the project primarily delineates the regional basins and analyzes their respective morphometric characteristics; generates thematic dataset in relation to each of the delineated sub-basin and; generates flood index, hotspots, and vulnerability rating map of each delineated sub-basin.
The motivation for this project is premised on the need to fill the existing gap of knowledge hindering the provision of spatial information imperative to understanding the mechanism of flood in the region as it relates to climate, rainfall, slope, land use land cover, terrain, soil /geology, drainage network, and basin area. These factors were integrated into the Suitability and Vulnerability Modelling and Computation Environment (SAVMACE), an indigenous software developed in COPINE to model flood vulnerability. The resultant output and models underpin the role of channel network on the geo-hydrological behaviour of the river basin as it relates to the magnitude and frequency of flood assessments.
The result of the morphometric parameters documented in this project can be useful for national planning and development especially to river basin authorities, ministries of Agriculture, water resources, environment among others. The established degree of vulnerability of southwest Nigeria to flood disaster provides a framework for effective resource allocation to flood monitoring and control.
O ver the years, disasters arising from floods account for thousands of deaths and tremendous damage to properties across the world, displacing tens of thousands of people from their abodes and destroying their businesses. Developing countries and poor communities are especially vulnerable.
Flood occurs when heavy rainfalls continuously for a long period of time, thus, accumulating water beyond the ground infiltration capacity. This leads to a rise in the water level resulting in surface flow down the slope into nearby ground depressions. In Nigeria, flooding is not a strange phenomenon. In the last 40 years, there have been episodes of flooding in different parts of the country. These were in forms of channel floods, urban floods, flash floods, back-swamp floods, and coastal inundation among others. The most recent with a very devastating impact was that of 2012 which, according to the National Emergency Management Agency (NEMA), affected more than three-quarters of the States in the country.
Efforts to mitigate the impact of flood has witnessed the establishment of Federal agencies and parastatals. For instance, NEMA is mandated to provide relief for victims of tragic events like flooding. Similarly, NIMET is commissioned to give real-time information about rainfall, its intensity and the likely events that may follow weather extremities through their early warning system. These bodies have over time discharge their duties, however, COPINE observed that damages to lives and properties remain high in times of flood. A study on flood vulnerability would reveal the level of exposure of an area or community to a likely event of flood in that environment. Such studies are imperative for effective and efficient disaster management.
he study area was south-western Nigeria, consisting of Lagos, Ogun, Oyo, Osun, Ondo,
and Ekiti states has shown in Figure 1. It is also known as the southwest geographical zone of Nigeria. The area lies
between Latitude 6° 21’ 01’’ and 8° 37’ 1’’N and Longitude 2° 31’ 01’’ and 6° 0’ 01’’ East (Agboola, 1979), with a total
land area of 76,852 sqkm (OSGOF, 2012), and a population of 27,722,432 (NPC, 2006).
The population distribution for all the states in the south-west are: Lagos - 9,113,605, Ogun - 3,751,140, Oyo - 5,580,894, Ondo - 3,460,877, Osun - 3,416,959, and Ekiti - 2,398,957. The study area is bounded on the East by Edo and Delta states, in the North by Kwara and Kogi states, in the West by the Republic of Benin, and in the south by the Gulf of Guinea. The study area has 85 constituted forest reserves with a forest area cover of 842,499 ha.
T he southwest of Nigeria’s climate is tropical and characterized by the wet and dry seasons. The south-west rainfall has a double maxima regime separated by a dry spell popularly known as the August break (short dry season during the rainfall regime). This means the dry and wet seasons are subdivided into four seasons: a long rainy season (March-early August), a short dry season (August break or dry spell), a short rainy season (September-early November), and a long dry season (Mid November-February). The annual rainfall ranges between 1500 and 3000mm while the annual temperature ranges between 21 and 34°C. The wet season is associated with the Southwest monsoon wind from the Atlantic Ocean while the dry season is associated with the northeast trade wind from the Sahara Desert.
T he vegetation in Southwest Nigeria is made up of swamp forest (saltwater and freshwater mangrove) in the coastal area of Lagos and Ogun state; followed by tropical rainforest in the hinterland. The low land in the forest stretches inland to Ogun and parts of Ondo State, while the secondary forest is towards the northern boundary where the derived southern Savannah exists (Agboola, 1979). However, the great influence of rainfall on the vegetation of Nigeria, in general, is also reflected in the pattern of vegetation observed in southwest Nigeria. Vegetation pattern changes as rainfall reduce progressively away from the coast, towards the North. It is important to note that vegetation characteristics are also influenced by the parent materials and human factors since some areas naturally part of the forest belt have been replaced with wooded savanna due to periodic clearing of the forest for cultivation purpose.
T he importance of climate as a factor of soil formation is evident from the fact that the four major soil groups almost correspond with the climatic zone. This means soil, vegetation, and climate generally in Nigeria are inextricably bound including that of the southwest region. However, among the major soil groups including alluvial and swampy soil of the coastal area, the rainforest soil, the lateritic soil, and the sandy soil of the far north, southwest region lies majorly on the rain forest soil and partly on the lateritic soil of the savanna especially at the transition zone between the tropical rainforest and derived savanna. In addition, it is important to note that soil characteristics are influenced by the parent materials and human factors in the region.
T The entire landscape of this region is underlain by old metamorphic rocks, outcropping to form high hills in many districts. The land surface is undulating and descends from an altitude of 480 m (1,600 ft) in Ekiti district in the north to 120 m (400ft) in Ondo and Ijebu districts in the south. In the open grassland areas of Oyo, the landscape is characterized by the extensive plains broken by steep-sided inselbergs (doom-shaped hill), occurring singly or in groups. The inselbergs are particularly numerous in Ekiti, Akure, and Ondo divisions where they attain greater heights than in the Ibadan and Oyo divisions. The Idanre Hills, attaining the height of 900 m (3,000 ft), is the most prominent inselbergs in Yoruba land. Several prominent ridges, elongated in a north-south direction feature in the area east of Ilesa, a good example being the 600 m (2,000 ft) Oke Mesi-Efon Alaye Ridge. The region is drained by many north-south flowing rivers including the Ogun, Osun, and Shasa rivers. These, and other large rivers flow all year round but show a marked drop in volume during the dry season. The smaller tributaries are dry each year for periods varying from a few weeks to three months. The valley of these rivers is however generally more deeply incised than those of rivers in the coastal plains.
T There are six states in the southwestern region of Nigeria. Prominent among these states in terms of urbanization, economy, and population are Lagos State and Ibadan, the capital of Oyo State. Lagos State is the most populous state in Nigeria after Kano State. It is also the major port and by far, the largest industrial centre in the country. Its growth in recent years has been phenomenal. The island city of Lagos (or Eko) was founded more than 300 years ago by a Yoruba Sub-group, the Awori. By 1800, the small fishing and farming settlement had grown to become one of the leading slave ports in West Africa. The oldest residential area was located on Lagos Island where the Oba’s palace is also located. Housing conditions are very poor in this part of the city, which is one of the worst slums in Nigeria. Newer and equally low-grades residential areas characterized by narrow streets with open gutters include Shomolu, Mushin, and Ajegunle. The middle-grade residential areas of Ebute Metta, Yaba, and Surulere house most of the wage-earning population while top civil servants and company executives live in the high-grade residential areas of Ikoyi, Victoria Island, Magodo, and Ikeja. The most impressive part of Lagos State is the Central Business District (CBD), covering the southern part of Lagos Island. This district is characterized by many skyscrapers rising to over twenty-five floors and great intensity of land use. Important functions of the CBD include wholesaling, financing, administration, and retailing. The main industrial estate, including Ikeja, Apapa, and Ilupeju, like the University campus and the teaching hospital are all located in the mainland district. Lagos Island is linked to the rest of the country by only two bridges, and since the bulk of the workers live in the mainland districts, the rush-hour traffic is one of the major distress occasioned by the recklessness of Lagos drivers. Attempts to ease the traffic congestion on Lagos roads include the construction of flyovers from Lagos Island and the main port of Apapa to mainland districts. The old-walled city of Ibadan started as a military camp and was built on a hilly and defensible site. Most of the early settlers came from old Oyo, destroyed early in the nineteenth century during the Fulani jihad. Later, the town attracted a large number of people from all over Yoruba land. The town was then surrounded by a wall about 16 km (10 miles) in circumference and the people who were predominantly farmers lived in large traditional compounds, only a few remaining today. The old city is notorious for its lack of planning, narrow, and winding lanes and is essentially one continuous slum. The new residential districts of Ekotedo, Sabo, Mokola, and Molete are located outside the old city walls and have a predominantly migrant population. The night clubs and other places of entertainment are concentrated in these migrant suburbs. The range of hills, running through the heart of the city is the most prominent feature of the physical landscape. These hills have provided sites for such landmarks as Mapo Hall, Bower Tower, and Premier Hotel. Other prominent buildings include the twenty-seven story Cocoa House and the ten-story co-operative building. As the capital of Oyo State, Ibadan is essentially an administrative centre although it is best known as the seat of Nigeria’s Premier University. Other important education and important research institutions include the International Institute of Tropical Agriculture (IITA), the University College Hospital (UCH), The Polytechnic, Ibadan, the Federal School of Forestry, the Federal Agricultural Research Centre, and the National Institute of Social and Economic Research. There are also several large modern manufacturing establishments in the city, the most important include the British Tobacco Company’s cigarette factory, a plastics factory, Coca Cola company, Procter and Gamble, and Pepsi Cola factory among others. It should be understood that the South West Region is noted for its rich cultural and traditional values, preserved and transmitted from generation to generation through a system of traditional and cultural education. These traditions and cultures have some level of uniformities and differences in terms of language, dressing, belief, religion, norms, and values. Among this uniformity are masquerade festivals and native attires donned in Yoruba land.
A lthough crude oil is now by far the most important source of government revenue in Nigeria, 70 percent of the labour force in southwest Nigeria is employed in agriculture. Indeed, the low per capita income reflects both the continuing reliance of most Nigerians on traditional agriculture and the low productivity of agriculture in the country. An increasing number of people are now employed in manufacturing while a much larger proportion obtain meager income from petty trading. Most south westerners are still peasant farmers producing their food crops and deriving income from one or more cash crops, as well as from the sale of surplus food crops. The main food crops grown in the southwest are yam, cassava, rice, and maize. Mixed cropping on fields, rarely exceed 0.4 hectares (1 acre) in the southwest and extreme dispersal of holdings, are characteristic features of farming in this region. Small-scale traditional irrigation is practiced along the floodplains of the major rivers in the region. Market gardening is important around the major towns where the increasing number of educated citizens have created a great demand for crops like cassava, maize, yam, palm oil, garri, rice, etc. The establishment of large modern poultry farms in the outskirts of the major towns is a relatively recent development in the region. The most developed parts of rural southwest Nigeria have been those districts cultivating crops such as the oil palm, cocoa, rubber, and cotton, commonly called export crops; although, an increasing proportion of these crops are now used for local manufacturing. The geographical conditions suitable for the production of these crops are present in the region.
A nalytical Hierarchy Process (AHP) is a multi-criteria decision method, using hierarchical structures to represent a problem and then develop priorities for alternatives based on the judgement of the user (Papaioannou, et al., 2015). AHP has been successfully used in solving various flooding problems (Kishor and Gopal, 2017; Kazakis et al., 2015; Papaioannou, et al., 2015). In this study, AHP was used in structuring and assigning weights to the flood causative factors. The top level of the AHP hierarchy structure exhibits the overall goal of the decision to be made, which in our study is flood vulnerability. After the hierarchy was constructed, AHP was used to establish priorities for all its nodes. This enabled information elicited from experts to be processed mathematically. A multiple pairwise comparisons based on a standardized comparison scale of nine levels was then used to obtain the pairwise comparison matrix. The table below illustrates the nine-point scale.
|Saaty’s Scale of Relative Importance
|Moderate importance of one over another
|Essential or strong importance
Pairwise judgements were made based on the best information available and the knowledge and experience of experts. The local priority (weight) for a criterion was computed from a pairwise comparison matrix by normalizing the points in the columns (divide a cell value by the sum of a column) and averaging the normalized points in the row of the criterion. The consistency of the comparisons was evaluated by calculating a Consistency Ratio (CR). If the CR is equal to or less than 0.1, the comparison is considered consistent, otherwise, it would be reviewed. The CR is defined by the following equation:
The Random Index (RI) refers to a randomly generated reciprocal matrix from the 9-point scale and can be obtained by referring to the RI table. Saaty (1990) provides a function of n in the relationship as shown in the table below.
The consistency index (CI) is defined as:
λ_max is the largest Eigenvalue derived from the comparison matrix;
n is the number of criteria.
The process of AHP used in this study can be summarized in four steps: construct the decision hierarchy; determine the relative importance of attributes and sub-attributes; evaluate each alternative, and calculate its overall weight regarding each attribute, and; check the consistency of the subjective evaluations. A similar procedure was used in the following studies; Hoque et al., 2019; Luu et al., 2018; Kishor and Gopal 2017; Kazakis et al., 2015; Papaioannou, et al., 2015 Ouma, and Tateishi, 2014, and Schoenherr et al., 2008. The above AHP computations and subsequent flood vulnerability mapping were carried out using SAVMACE (Suitability and Vulnerability Modelling and Computation Environment).
O ne of the software used for flood vulnerability mapping is SAVMACE. It is an environment for modelling suitability or vulnerability. The modelling is done using the multi-criteria decision analysis (MCDA) techniques. The software is subsequently used to calculate the suitability or vulnerability using the model already built and prepared spatial data imported into the software. The results of the computation can now be visualized and symbolized in the GIS software.
T he flood model was built in SAVMACE using MCDA techniques. At the factors level, AHP was used to specify the relative strength/contribution of each selected factor to flood vulnerability. The AHP module in the software was used to generate the relative weights of each factor by comparing each of the factors to one another on the scale of importance ranging from 1 to 9. These nominal comparisons, of one factor to another, were subsequently used to compute the relative weight of each factor using the Geometric Mean method incorporated into SAVMACE. At the class level, within each of the factors, the relative weights were modelled and specified using Weighted Linear Combination (WLC). The relative weights at the classes levels were arrived at by using Sequential Numerical Ranking and Ratioing. The factors selected for this flood vulnerability in their decreasing order of importance are Elevation, Distance to Stream, Slope, Rainfall, Land use/land cover, and Soil. After subjecting them to the AHP procedures, specifying their relative importance to one another, the following weights were obtained, respectively: 0.3931, 0.2637, 0.1530, 0.0964, 0.0574, and 0.0365, with a consistency ratio of less than 0.1. This ratio with respect to the number of factors used in this modelling shows that the AHP relative importance specifications are consistent. The classes within each factor are specified and weighted according to their levels of severity/types (as the case maybe). The results of the computation of vulnerability percentage were also classified to indicate four (4) degrees of vulnerability. classification is as follows: 0-25% is Less vulnerable, 26-50% is Marginally vulnerable, 51-75% is Moderately vulnerable, and 76-100% is Highly vulnerable.
S AVMACE works with the shapefile GIS data format, and the data preparation was carried out in the vector data format for shapefiles. All the data layers representing each of the factors were assembled, processed, and integrated into one data layer in a GIS environment.
T o obtain the flood vulnerability results, the prepared spatial data was imported into SAVMACE, headings in its attribute table are connected to the appropriate branches/parameters in the built model, and the computation engine calculated and classified the levels of flood vulnerability for all the geographical area represented by the data. The spatial data, now containing the results, was symbolized and composed into the flood vulnerability maps in GIS software.