FLOOD SIMULATION AND TERRAIN ANALYSIS BETWEEN 2018 AND 2019 IN THE NIGER DELTA: A CASE STUDY OF YENA

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FLOOD SIMULATION AND TERRAIN ANALYSIS BETWEEN 2018 AND 2019 IN THE NIGER DELTA: A CASE STUDY OF YENAGOA AND ITS ENVIRONS Eteh, Desmond Rowland*1, Akana Tombra Susan*2 *1 PhD

Student, Faculty of Science, Department of Geology, Niger Delta University, Wilberforce Island, Bayelsa State. *2 Lecturer,

Faculty of Science, Department of Geology, Niger Delta University, Wilberforce Island, Bayelsa State.

ABSTRACT In recent times, due to climate change and other environmental factors, flooding has been a recurrent problem in most parts of the world, the Niger Delta inclusive. Governments are constantly in search of ways to combat this environmental crisis to save life and property. This research, therefore, uses flood simulation to determine flood prone regions in the study area and when these flood zones are safe for people to occupy. It also uses terrain analyses to determine the drainage pattern within the study area.

This research explores the use of Shuttle Radar Topographic Mission (SRTM) data and Borehole data to monitor flood prone areas and digital elevation models (DEM) to determine the drainage patterns with the aid of Arc Scene 10.6 and Arc Map 10.6 software. Results show that the study area has 147 catchment areas, a dendritic drainage pattern, and elevation ranging from -14m to 38m. Borehole water level monitoring revealed that the flooding episode of 2018 was outsized by that of 2019. The flood simulation models indicate that flooding within the study area is cyclic in nature with floodwaters beginning to rise slowly in the middle of the year, peaks in November and drops sharply by December. From simulations.

Based on this work, the south-western areas in the study area would require a lot more flood mitigation processes to prevent loss of lives and properties during the flood season and would be safe for habitation in the early months of the year.

KEYWORDS: Flood simulation, GIS, Remote Sensing, drainage channel, 3D Modelling, SRTM

I.

INTRODUCTION

Floods are one of the most common of all environmental hazards regularly claiming over 20,000 lives per year and adversely affecting around 75 million people worldwide [13]. It is estimated that of the total economic loss caused by all kinds of disasters, 40% are due to flooding [6]. Flood is a major disaster and for the past decades, it has plagued not only the Niger Delta but the world at large [1]. The United Nations Commission on Sustainable Development [14] earmarked some probable causes of flooding to include heavy tropical storm, high intensity of rainfall, climate changes, deforestation, and the dam burst. [4] and [5] both suggest that the major causes of flooding within the Niger Delta are caused by an increase in rainfall, blockage of natural drainages and disregard of Town Planning and Urban Laws especially during constructions. The need for development and growth within the Niger Delta has also led to the increase of human settlements on river flood plains and low-lying regions effectively blocking drainage pathways.

Thus, the incidence of recurrent flooding in the Niger Delta region is still a problem yet to be fully addressed. However, the simulation of floods and drainage patterns in the environment provides information and visual representation that can assist decision making of the government and individuals when flood zone areas may be safe for people to occupy [9]. Geographic Information System (GIS) has also been applied extensively to flood studies [5] as it reflects all kinds of spatial data in the real world. It can input, output, store, search, display, analyze, and be applied under certain support of software and hardware. The integration of GIS techniques on flood simulation and terrain analysis calls for a consign by applying GIS tools to monitor flood and the effect of drainage systems on flooding. This is to detect the drainage channel, its elevation and response to water flow direction, and determine the flood simulation model during and after the flood with the response to water increase. [15] and [8], both carried out a community-based flood risk assessment of San Sebastian using GIS and were able to develop detailed www.irjmets.com

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information on the flood hazard, vulnerability, flood prone areas, and expected losses which in turn was used to manage risk within the area. Also, the integration of a hydraulic simulation model and GIS can contribute to the quantitative assessment of the effects of the upstream land-use changes on downstream flood pattern which can be used by municipal authorities as a valuable tool in municipal planning, including a wider range of applications in addition to risk management.

II.

METHODOLOGY

a) Study Area and Geology The area under investigation is situated in the central Niger Delta sedimentary basin of Southern Nigeria (Figure 1) in Bayelsa State, Nigeria. The area lies within Latitude 4o53'30''N – 5o4'30''N and Longitude 6o13'30''E – 6o21'30''E. The area is within Yenagoa metropolis having good road network links to different towns including oil and gas facilities of major companies such as Nigerian Liquified Natural Gas (NLNG), Shell Petroleum Development Company (SPDC) and AGIP. The topography of the area is low with a maximum of 38m altitude. The major social-economic activities of the locals are fishing, farming, and local sand dredging from and rivers. The study area which is in the southwestern flank of the Niger Delta and its geology has been described extensively by Short and [11] amongst many others. The Niger Delta Basin is formed by a failed rift triple unction during the separation of the South American Plate and the African plate, which opens into Atlantic. Rifting in the basin started late Jurassic and ended in the midCretaceous. Several faults occur although there are mainly thrust faults within the basin. The delta covers a land area over 105,000 km2 [10].

Figure 1: Map of the study area (Eteh Desmond)

b) Data Collection The data collected are Shuttle Radar Topographical Mission (SRTM) downloaded from [17], An administrative map from where political boundaries and roads were obtained and digitized from a highresolution image of about 3m from Google Earth., other data were acquired with the use of Garmin72 GPS for the acquisition of coordinates of the communities respectively. (Table 1). Also, in the study area, 2 boreholes were drilled and cased in January of 2018 two meters (2 m) away from the shoreline, from which data was collected using Deep meter. The deep meter was used to collected the water level data from the boreholes in January which served as the baseline and then monthly intervals from June to December 2018 and 2019 were further collected. (See Figure 2). www.irjmets.com

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Table-1: List of Data collected for the study area Satellite Data

Date

Spatial Resolution

Source

SRTM

22/11/2000, 1-ARC second

30 m

[17]

Google Earth Imagery

06/02/2012

3m

[18]

Table-2: Summary Table of the data collected from Borehole monthly January

June

July

August

Sept

Oct

November

Dec

2018 (m)

0

0.58

4.3

4.8

8.3

9.2

11.45

6

2019 (m)

0

1.1

2.85

3.38

6.91

8.6

9.33

8.6

c) Data processing and analysis Arc GIS 10.6 software in spatial analyst extension was used to generate the height information from SRTM DEM (Digital Elevation Model), Drainage channel, and drainage basin in hydrology tools. The Global Positioning System (GPS) data was in degree decimal format and was computed on Microsoft excel and import into the Arc GIS environment in DataBase Format before location map was generated alongside Digital elevation including digitizing of road river and other properties. Microsoft Excel software was used to perform the results for water level getting from the borehole and a plot on a line chat to study the simulation and also imported into the Arc scene 10.6 environment alongside with the result of the baseline and Digital elevation model to perform simulation model.

III.

RESULTS AND DISCUSSION

a) Digital Elevation Model The DEM of the study area ranges from -14.00 m to 38.00 m (Figure 2). The southern part of the study area (Yellow areas- Yenegoa, Swali, Ekeki, Yenaka, and surroundings) is observed to display the lowest elevation indicating that such areas are most likely the first to be overcome by floodwaters [5] and [4].

The north-western and the eastern part (Figure 2- green areas) of the study area are observed to have higher elevation indicating that floodwaters would require greater height to overcome these areas which corresponds to findings by [5]. He suggested that the low lying, flood prone areas within the study area are easily detected using DEM and suggested that these areas can be used for agricultural practices.

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Figure-2: Digital Elevation map of the study area.

b) Drainage System The drainage system within the study area is observed to be dendritic in nature [7],[2] with flow direction moving from the north to the south (Figure 3). A total of 147 catchments areas/subbasins were identified in a single watershed (Figure 4) indicating that the study area has an adequate drainage system. Although this highly connected drainage system is present within the study area, the absence and inability to obey and enforce environmental laws and practices have led to the blockage of these natural drainage systems leading to flooding [5]. Also, the study area is drained by a single watershed hence, flash floods are common when there is a constant downpour and the watershed is incapable of channeling the discharge water to the ocean. The drainage pattern within the study also reveals that water enters into the Epie creek from the River Niger (Figure 3). This creek, which dominantly drains the study area requires constant dredging to accommodate the influx of sediment laden waters. The inability to monitor and dredge this channel causes the flooding of the study area .

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Figure-3: Drainage channel of water flow direction (Eteh Desmond)

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Figure-4: Drainage Basin of the study area

c) Flood Simulation

Flood Simulation Rise in water level (m)

14 12 10 8 6 4 2 0

January

June

July

August

Sept

Oct

November

Dec

2018 (m)

0

0.58

4.3

4.8

8.3

9.2

11.45

6

2019 (m)

0

1.1

2.85

3.38

6.91

8.6

9.33

8.6

Figure-5: Flood simulation result of 2018 and 2019 The outcomes from Table 2. uncovers that in January 2018 and 2019 baseline was taking as zero to contemplate the rise and fall in sea level, so there is ascend in sea level from June to July at slow speed then from July to August the speed diminish which can be attributed to low rain fall (see Figure 5) at that point water ascend at rapid from August to November at that point lessening from November down and furthermore comparing 2018 and 2019 outcomes in June it was see that water level in 2019 is higher than in 2018 which can be as a result of sediment deposit from previous years, couple with government not be able to dredge the River Niger including River Nur,Le Niger, Orashi River Epie Creek , kolo Creek and on other hand due to the nature of altitude, drainage channel and a lot of subbasin

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present in the terrain causing flash flood during rainy season and in December 2018 and 2019 (Table 2) shows that the speed at which water drop is high in 2018 than 2019 causing farmer to plant late, individual and institution were display for longtime and from Figure 5 Shows that 2018 flood generally is higher than 2019 flood in the district.

Figure-6a: Baseline water level in 2018 January (Eteh Desmond)

Figure 6b: Baseline water level in 2019 January (Eteh Desmond)

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Figure 6c: Flood Simulation in 2018 (Eteh Desmond)

Figure 6d: Flood Simulation in 2019 (Eteh Desmond)

Figure 6a and 6b shows the baseline of the terrain before the flood and Figure 6c and 6d shows flood simulation results which are the disaster period in November 2018 and 2019 displacing various Towns most along with the riverine communities and household in the city including the closing of business due to the rise in sea level affecting their shop and office. comparing 2018 and 2019 flood reveals that the 2018 flood is bigger than 2019 flood (see Figure 6c,6b, and Table 2) and most communities were affected seriously in 2018. The simulation was able to delineate flood relief area were in Figure 6c, the area www.irjmets.com

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suitable for flood relief zones are denoted from an orange colour to red have elevation 18m and above and 14 m below could be flood plain areas and therefore this process can be used for Flood analysis mapping by mapping flood-prone areas using the noble approach of remote sensing and Geospatial techniques to determine area that area flood free zone and area that flood risk zone by [5]

IV.

CONCLUSION

Through the use of flood simulation and terrain analysis within the GIS and remote sensing platform, the cause, risk and effect of floods within the study area has been determined. The lack of enforcement of environmental laws and the inhabitation of drainage pathways is the major reason of flooding within the study area. The simulation revealed that the south eastern part of the study area would experience greater levels of flooding if ways to mitigate this problem is not developed and implemented. This mitigation processes should involve the constant dredging of channel pathways to help the discharge waters to reach the ocean without breaking the channel banks and causing flooding.

V.

REFERENCES

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