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Table 5. Ground elevation with reference to sea level 3.3 Flood Risk Zones The flood risk maps A and B were generated from the hydrological analysis and digitized layers from IKONOS image over the study area (Fifures 7 and 8). Each of these maps shows the spatial extent within the built-up areas at risk of being flooded whenever there was heavy downpour. Figure 7 depicts the areas around the stream channels within the study area proned to flooding event. The most vulnerable area was within 10 m radius of the stream, and this area was delineated with red polygon. The more vulnerable areas within the distance of 40 m from the red polygon were marked with yellow color; while the higher areas in blue color and beyond were considered to be less vulnerable. A geographical location with high elevation and high slope angle that fell within the vulnerable area might not necessarily get inundated during the flood event but the case of Igbokoda was quite different as the major part of the town was associated with elevation less than 20 m and slope angle between 0 and 8 degrees. ie tet ry i

Table 5 Ground elevation with reference to sea level 3.3 Flood Risk Zones The flood risk maps A and B were generated from the hydrological analysis and digitized layers from IKONOS image over the study area (Fifures 7 and 8). Each of these maps shows the spatial extent within the built-up areas at risk of being flooded whenever there was heavy downpour. Figure 7 depicts the areas around the stream channels within the study area proned to flooding event. The most vulnerable area was within 10 m radius of the stream, and this area was delineated with red polygon. The more vulnerable areas within the distance of 40 m from the red polygon were marked with yellow color; while the higher areas in blue color and beyond were considered to be less vulnerable. A geographical location with high elevation and high slope angle that fell within the vulnerable area might not necessarily get inundated during the flood event but the case of Igbokoda was quite different as the major part of the town was associated with elevation less than 20 m and slope angle between 0 and 8 degrees. ie tet ry i

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Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Table 1. Summary of landsat images acquired for the research 2.2.3. High Resolution Imagery-IKO NOS Image
Table 1. Summary of landsat images acquired for the research 2.2.3. High Resolution Imagery-IKO NOS Image
Table 2. Land covers classification categories 2.4. Hydrological Analysis
Table 2. Land covers classification categories 2.4. Hydrological Analysis
Note: A decrease carries negative sign while an increase carries positive sign elevation and along the road sides that had already been sand riled during road construction actvities. The major bare surface feature in the study area as confirmed via ground truthing was white sands. This development occurred when the water had been drained due to the increase in evaporation rate and sand filling of the area for construction purposes. The major water body in the area of study was from the wetlands which caused the flooding event in this area to be seasonal (meaning only occurred during the rainy seasons whenever there was heavy downpour).
Note: A decrease carries negative sign while an increase carries positive sign elevation and along the road sides that had already been sand riled during road construction actvities. The major bare surface feature in the study area as confirmed via ground truthing was white sands. This development occurred when the water had been drained due to the increase in evaporation rate and sand filling of the area for construction purposes. The major water body in the area of study was from the wetlands which caused the flooding event in this area to be seasonal (meaning only occurred during the rainy seasons whenever there was heavy downpour).
Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017 Figure 2. Classified landsat image over study area for the year 1986, 1999, and 2013.
Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017 Figure 2. Classified landsat image over study area for the year 1986, 1999, and 2013.
Figure 3. Percentage of the land cover area for three time periods over Igbokoda. Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Figure 3. Percentage of the land cover area for three time periods over Igbokoda. Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Figure 4. Drainage basins over the study area. Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Figure 4. Drainage basins over the study area. Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017 d d the potentials of these low lying areas for such purposes like FADAMA Project [35; 36; 37]. The stream network density in any area greatly influenced the runoff potential, and the strength of the stream network density could be determined by the number of channels or tributaries within a rainage basin in an area [32]. The natural stream network of the study area is illustrated in Figure 6. It revealed that few channels existed over the study and this could be accounted for the low draining rate of water which in turn caused accumulation of rain water over the area whenever there was heavy ownpour. In this study, the extreme rainfall data available to simulate the flooding area was over the past 27 years. The mean magnitude of rainfall that can create flooding in the study area was 440.9 mm which was in the month of August as shown in Table 4.
Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017 d d the potentials of these low lying areas for such purposes like FADAMA Project [35; 36; 37]. The stream network density in any area greatly influenced the runoff potential, and the strength of the stream network density could be determined by the number of channels or tributaries within a rainage basin in an area [32]. The natural stream network of the study area is illustrated in Figure 6. It revealed that few channels existed over the study and this could be accounted for the low draining rate of water which in turn caused accumulation of rain water over the area whenever there was heavy ownpour. In this study, the extreme rainfall data available to simulate the flooding area was over the past 27 years. The mean magnitude of rainfall that can create flooding in the study area was 440.9 mm which was in the month of August as shown in Table 4.
Figure 6. Stream network with the drainage basins over the study area. Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Figure 6. Stream network with the drainage basins over the study area. Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017
Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017 Figure 7. Flood risk Map A.
Journal of Applied Science & Process Engineering Vol. 4, No. 2, 2017 Figure 7. Flood risk Map A.
Table 6. The spatial extent of the flood prone area within the residential area
Table 6. The spatial extent of the flood prone area within the residential area
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