Maiduguri metropolis Nigeria, lies on a relatively flat terrain of about 350 meters above sea level and is part of the undulating Borno Plain that slopes towards the Lake Chad. The rapid physical expansion of the metropolis and the annual recurrent flash flooding and inundation problems within the city continues to impact devastating socioeconomic effects on the livelihood of residents sometimes leading to loss of lives and property. It is important therefore to understand the spatial pattern of floods and terrain characteristics in Maiduguri for planning purposes. The paper examined the spatial pattern of urban flash floods and inundations, and the terrain characteristics in Maiduguri metropolis. Digital Terrain Model (DTM) generated from the Shuttle Raddar Topography Mission was used to provide the basis for the terrain analysis to generate hydrological parameters such as elevation, flow accumulation and direction, drainage network and slope angle as well as classified elevation images and terrain wetness index to map out potential flood risk areas. The DTM identified potential areas liable to flash flood and inundation. The 3D Digital Terrain Model (DTM) of the area showed where potential floods or traps were located in the metropolis. The findings further revealed that Maiduguri was generally characterized by low lying locations with slope angles of less than 5 degrees covering an area of 144.4 km 2 out of 148 km 2 making it extremely difficult to drain. The processed flow accumulation of the study area showed a high flow accumulation pixel value of 19,972 that drained into outlet, suggesting that a large proportion of the study area was getting flooded during a rainstorm. Even though the calculated drainage density of 0.73 for the study area indicated a very good drainage system, this was also undermined by the flat terrain and urbanization. The study recommends for improved land use planning; raising awareness of the residents, provision of more drainages and continued vulnerability mapping improved the functionality of bodies responsible for flood management among others for sustainable flood management in the study area.
Flash floods are rapid rise of water along a stream or low lying sections of the urban area usually caused by heavy rainfall. Inundation on the other hand, occurs when floodwater and debris flow through an area for several days. As floods occur naturally, it has the potential for fatal causes such as displacement of people and damage to the environment [
The ability to delineate potential flash flood and inundation areas and to map the actual extent of inundation in a floodplain has always been a very difficult task more especially in the developing countries. In many regions, the lack of hydrologic and spatial data constrains the accurate delimitation of flood inundation zones [
Over the years, Maiduguri has been experiencing serious drainage problems during the rainy season. Besides, none of the earlier studies applies Geographic Information System (GIS) and Remote Sensing Techniques in the analysis of the terrain of the area and mapping of urban flash floods and inundations. This paper therefore examins the spatial pattern of urban flash floods and inundations and the terrain characteristics in Maiduguri metropolis using remote sensing and geographic information system techniques. The focus of this study therefore is to develop a Digital Terrain Model (DTM) of the area to guide future planning and to mitigate the menace of flashfloods and inundations in the rapidly growing urban areas of Nigeria.
Maiduguri Metropolis, a major city in the Northeastern corner of Nigerian, is located between latitudes 11˚04'N and 11˚44'N; and between longitudes 13˚04'E and 13˚44'E. It covers a total land area of 543 km2, which makes it the largest city in the Northeastern region of Nigeria [
Maiduguri Urban now extends to four Local Government Areas: Maiduguri Metropolitan, Jere, Konduga and to a smaller extent part of Mafa local government areas. The area is within the vast open plain which is flat or gently undulating, developed on young sedimentary rocks of the Chad formation. This relatively flat terrain is sloping towards the Lake Chad and has an average relief ranging between 300 m and 600 m above sea level [
Maiduguri is located in the Sudan Savannah vegetation region of Nigeria. It is characterized by low annual precipitation (650 mm), high evaporation and perennial water shortage [
Generally the mean monthly temperature is always above 20˚C but the daily extremes vary in a wide range reaching up to 47˚C in April. Daily temperature may occasionally exceed 40˚C, while the night temperatures are high but lowered in the early morning hours. The climate of the area is affected by the North East trade winds and the South West monsoons originating from the Sahara and the Altantic Ocean. The soil of Maiduguri and environs may be classified into sands of Aeolian origin and the beach ridge sediment, vertisol or lagoonal clay and fluvisol and clay soil of alluvial deposit. There are also the brown and reddish brown, regosols, hydromorphic and alluvial soils which are favorable for agricultural activities of many types. It has a population estimated at 1.275 million people according to the 2006 census [
The data used in this study include a Google map of the study area for 2012, Maiduguri Topographic Sheet 90 NW and Shuttle Radar Topography Mission (SRTM) 90 m Digital Elevation Model (DEM). The SRTM DEM, was processed to generate (flow accumulation and direction, drainage network and ordering as well as catchments maps, which were used for the analyses. All the spatial data were projected to common coordinate system: Universal Transverse Mercator (UTM) projection system, with Clark 1880 Ellipsoid, Minna Datum, and Zone 33. The digital elevation model (SRTM-DEM image) was acquired from the United State Geological Survey (USGS) portal. The topographic sheet 90 NW was collected from the State Ministry of Land and Survey office for validating the DEM using contour values on the map. The GIS software package used for the research was ILWIS 3.72 for processing of all the remotely sensed data. Materials used for field work and data capture include Garmin GPS map 76 CSx with ± 3m accuracy and Google Earth explorer (Quickbird image).
Hydro processing operations in ILWIS environment was used to determine the natural flow pattern of surface water after rainfall. Hydro processing is an ILWIS term describing the collection of operations used in either analyzing or modeling ground water phenomena. The procedure described in this section is meant to determine the natural flow pattern of surface water after a rainfall. This requires series of operations working in sequence with the output of one operation becoming the input of the next operation [
1) Digital Elevation Model SRTM DEM (90 m)
2) Landsat MSS, TM and ETM+
To prepare for hydrological parameter extraction using image processing software, the study used a Digital Elevation Model (DEM) which is a digital representation of relief over space. The DEM was prepared and pro- cessed by fill operation, so as to have smooth flow of water. By relating any map with the corresponding terrain surface in a 3-dimentional model, one can discover and understand relations between spatial data sets. For example, by draping on Maiduguri urban area map over the height values of a 3D model, it is possible to see where potential floods or traps are located: on slopes, on flat areas and in the lower areas of Maiduguri. The DEM was used to extract flow accumulation and direction, drainage network extraction and ordering, and catchment/basin extraction. The Drainage pattern map was determined from the flow accumulation. The output raster map shows the basic drainage as pixels with value True, while other pixels have value False (Boolean). Boolean map performs a Boolean exclusive or operation on the cell values of two input images. If one input value is true (non-zero) and the other false (zero), the output is 1. But if both input values are true and both are false, the output is 0. The Boolean math tools interpret the input cell values as Boolean values, where non-zero values are considered true and the value 0 is considered false. The two input raster were tested on a cell-by-cell basis (ArcGIS 10, 2010). The interpolated DEM was processed using the DEM Hydro-processing module in ILWIS. The sequential steps in the processing were followed to delineate the sub watershed. The filled DEM operation was first performed before calculating flow direction and flow accumulation to define new streams using a drainage area (
The first operation is the “fill sink” process meant to remove local depressions from the DTM. The depressionless DEM (after fill operation) was used to generate a flow direction raster map. The flow direction shows the possible direction of water run-off on the elevation model. This analysis was performed using the flow direction tool in DEM hydro-processing module in ILWIS. Determination of flow accumulation is the next step after flow direction and it shows the cells within the study area where water accumulates as it flows downwards. Thus, wards around these cells will receive much water during an event of rainfall or any sudden release of water. The stream network was created from the flow accumulation raster map to show the path of streams on the elevation. A reclassification of the flow accumulation results was performed using the reclassification slicing tool. Slicing classifies the values of raster map into appropriate class range using the upper bound limit. The Flow accumulation operation performs a cumulative count of the number of pixels that naturally drain water into outlets. The operation can be used to find the drainage pattern of a terrain (
・ As input the operation uses the output map of the flow direction operation to compute flow accumulation.
・ The output map contains cumulative hydrologic flow values that represent the number of input pixels which contribute any water to the outlets (or sinks if these have not been removed).
・ The higher the Flow accumulation value, the higher the chance of any area near the outlet to be flooded.
The water sink operation is calculated from the Digital Elevation Model (DEM) of the study area:
・ Depressions that consist of a single pixel, i.e., any pixel with a smaller height value than all of its 8 neig- hbouring pixels;
・ Depressions that consist of multiple pixels, i.e., any group of adjacent pixels where the pixels that have smaller height values than all pixels that surround such a depression.
Inundated areas were extracted using the wetness index. The purpose is to isolate dips and hollows that maintain water for longer periods, exclusive of permanent water bodies like lakes and swamps. The aim is to find low lying areas of poor drainage. Through this index, an idea of the spatial distribution and zones of saturation or variable sources for runoff generation is obtained. The TWI was calculated by running an elevation variance algorithm on the DEM. This is a neighbor function that looks at the average elevation of all surrounding cells. Then calculates variance based on itself and the average. Once the potential areas were determined, the resulting maps in raster format were statistically evaluated in relation to geomorphologic units characterized as susceptible areas to flood inundation. The selected flood areas were those with poor and very poor drainage conditions. Flood inundation areas were assigned a value of 1 and others to 0. Although, the ability of a DEM-based surface to correctly identify flooded areas depends on the quality of the elevation data used for generating the DEM. The wetness index can also be derived from Landsat ETM + image to identify differences between wet and non-wet areas [
The processed hydrologic parameters include flow accumulation and direction, drainage network extraction and ordering, and catchment. These images were extracted from SRTM Digital Elevation Model (SRTM DEM), 90m spatial resolution and clearly displayed the potential inundation areas with poor drainage conditions. These areas last for the whole rainy season and are considered to have very poor drainage condition. These images have revealed a very clear characteristic of the Maiduguri terrain. The results indicated that the elevation of each ward differs from one another. This was found attributable to the different inundated areas within same wards and equally responsible for the spatial distribution of flash floods and inundated areas within the metropolis. The images presented as Figures 4-6 show the terrain and watershed of the Maiduguri metropolis over the height
values of a 3D model. The images depicted the elevation of the area showing different height levels of the terrain of the metropolis in meters above sea level (asl). These images indicate clearly where the potential floods or traps are located both on slopes, flat areas and in the lower areas of the metropolis. The white area indicates the higher elevations which are at low risk to flash floods while the black portion signifies the lower elevations which are highly vulnerable or prone to flash floods and inundations. The finding shows that Maiduguri is generally flat in nature and extremely difficult to drain (Figures 4-6). The flatness of the terrain partly explains why these stagnant pools persist in an arid zone with sandy soils that should absorb the water almost immediately. Also, drifts of sand lie on the surface which is underlaid by clay, silt and sandy clay that may retard the underground seepage of the water.
The processed flow accumulation of the study area indicated a high flow accumulation pixel value of 19,972 that drains into outlets (
The natural stream network of the study area is illustrated in (
(BBR), the old shoreline of Mega Chad. Yet, this river system still finds an outlet across the Ridge to change to
North East direction.
The images (Figures 8-10) were extracted from SRTM Digital Elevation Model (SRTM DEM), 90 m spatial resolution and clearly displayed the potential inundation areas with poor drainage conditions. These areas last for the whole rainy season and are considered to have very poor drainage condition. Water sink gives further explanation on the nature of terrain (Figures 8-10). They show depressions in elevation below the surrounding or neighboring terrain, which results in water trap. The high risk zones are areas that are most likely to be inundated in a flooding event while the low risk areas are the least likely to be flooded. The analysis also shows that the high risk areas are more than other risk zones. Obviously, this could be explained by the flatness of the terrain of the study area. Much of the study area is made up of small depressions. As shown from computation of the entire Maiduguri area, there are more water traps/depressions than higher elevations. This means that even though Maiduguri is flat, there are many depressions. The total water sink is 104.20 km2 and free water sink is 48.5 km2. The city therefore needs to be well planned to have flood risk reduction. It is a known fact that water flows from an area of higher elevation to that of a lower elevation. The stream network of the area revealed that some parts of the urban area are built on the natural stream channels or drainages. The effect on the terrain is that buildings and diversions lead to an obstruction of the natural course of water during rainfall and especially as there are no effective drainages in the area and may make flooding and inundation inevitable.
The Water Sinks and Wetness index (
from 0.4 meters to 1.2 meters. Majority of the constructed drainages are not interlinked with one another. Rainwater therefore does not have access to move; rather it stagnates and generates more floods.
The paper has demonstrated the application and usefulness of Remote Sensing (RS) and Geographic Information System (GIS) tools in flood risk management. The Digital Terrain Model (DTM) has identified the flood risk areas within the metropolis and has provided adequate knowledge of the flood situation for government intervention towards curtailing the disaster. The area is very flat in nature as indicated by the 3D Digital Terrain Model (DTM) and is characterized by a very good and well fashioned natural drainage system but is taken over by poorly planned urban development rendering them less effective. The occurrence of flash flood and inundation is on the increase with devastating socioeconomic effects and the effects are more devastating where natural drainages networks exist, but are replaced by residential buildings due to urban sprawl. Therefore, poor residential planning and inadequate management strategies can be responsible for escalating flash floods and inundation in the city. It will therefore continue to pose a threat to residents and the risk of exposure is expected to be on the rise as the metropolis witnesses’ rapid urbanization, coupled with poor urban planning and management activities. This calls for serious urban re-engineering to overcome existing challenges and to put future of the urban area to proper planning and plan implementation for sustainable city.
Mohammed Abba Jimme,Abbas Bashir,Abel Aderemi Adebayo, (2016) Spatial Distribution Pattern and Terrain Analysis of Urban Flash Floods and Inundated Areas in Maiduguri Metropolis, Borno State, Northeast, Nigeria. Journal of Geographic Information System,08,108-120. doi: 10.4236/jgis.2016.81011