International Journal of Trend in Research and Development ... · rise in sea levels. Rise in sea...

International Journal of Trend in Research and Development, Volume 4(1), ISSN: 2394-9333

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IJTRD | Jan-Feb 2017 Available [email protected] 159

Assessing the Effects of Sea Level Rise in Niger Delta

using Remote Sensing and GIS 1Sunny Chuku,

2Ifeanyi Emmanuel Njoku and

3Oge Harry Obimba,

1,2,3The Federal University of Technology, Akure (FUTA), In collaboration with African Regional Centre for Space

Science and Technology Education –English(ARCSSTE-E), OAU Post Office, Ile-Ife, Nigeria

Abstract: The changes in climate condition can be said to be one

of the major causes of floods. This paper explains the relationship

between changing climatic conditions and flooding, the effects of

global warming and how it relates to flooding, as well as high rate

of precipitation. It goes ahead to explain the effects of Sea Level

Rise (SLR) and how its impact will be felt by some parts of the

world more than others. This paper is a detailed work with a

classical approach to the effect of sea level rise in Niger Delta

Region of Nigeria. An evaluation of vulnerability to sea level rise

is undertaken for the Niger Delta based on different simulations.

Remote sensing and geographic information system (GIS)

techniques where used to evaluate effects of Sea Level Rise in the

Niger Delta region of Nigeria, considering a simulation of 1m -

4m sea level rise conditions occurring. The simulation was done

using SRTM data, administrative boundary shapefile of Nigeria

and spatial analysis were executed based on 1m -4m scenario, to

identify the towns that would be affected. The result were tables

and maps showing towns in the Niger Delta region that would be

affected based on the different simulations of sea level rise. Niger

Delta is vulnerable to the effects of SLR. Moreover, the location

of many settlements in remote areas, far away fromthe local

government headquarters, reduces the value of resilience to the

effects of SLR.

I. INTRODUCTION

Within the last few decades, the atmospheric and sea

surfacetemperatures have been rising and climates worldwide

arechanging. With such changes, floods are occurring more often

and studies need to be carried out to see how to preventfloods.

The classical approach is to look at river floods and mitigation

strategies, due to an increase in precipitation andconsequently in

the frequency of high peak floods occurringin river systems

(Bhattacharya et al., 2013; Castro-Gammaet al., 2014; Fu et al.,

2014; Leauthaud et al., 2013; MoyaQuiroga et al., 2013).

Increases in sea surface temperatures cause thermal expansion,

which increases the water level of the sea surface

(Intergovernmental Panel on Climate Change [IPCC, 2013]), and

as a result, the shoreline moves farther inland. The warming of

the atmosphere causes melting of mountain glaciers and polar ice

sheets, also an abnormal increase precipitation thus increasing the

rise in sea levels.

Rise in sea levels has various consequences for low-lyingcoastal

areas, such as inundation due to coastal floodingby incoming

rivers and/or the sea, erosion, displacement ofcoastal wetlands,

and inland intrusion of sea water (IPCC,2007b; Van et al., 2012).

Over the years, scientists have usedclimate models to generate

projections of possible sea levelrise (SLR) values by the year

2100.

The effects of sea level rise (SLR), however, will not beuniform

all over the world; some coastal areas will recordhigher sea levels

than the global average, due to land subsidence from contraction

of soil materials. Relative sea level rise is the change in sea levels

relative to the land elevation,and includes land vertical movement

in addition to globalsea level rise values. Relative sea level rise

values are higherin subsiding coasts like river deltas than the ones

in stablecoastal areas. Although subsidence occurs naturally in

deltas,in the case of the Niger Delta, it is increased even moreby

oil extraction from underground sources (Ericson et al.,2006). Oil

extraction might not affect an area if there areproper surveys and

regulations that take care of this issue,as well as if there is normal

sediment supply coming fromupstream into the delta. However,

in situations where sediment supply from upstream is reduced or

is inadequate forreplenishing the area, land subsidence will occur,

as has beenrecorded in some parts of Japan, Indonesia and

Venezuela(IPCC, 2007c).

Vulnerability as a concept represents potential damage,and it is

conditional upon the possibility of a hazard. Thus, asystem is said

to be vulnerable when it has a high susceptibility to the effects of

a hazard, and is unable to cope, recover oradapt (Balica et al.,

2013). System vulnerability assessmentto a certain hazard gives a

measure of the degree of damagethat might likely occur if the

hazard happens without mitigation/adaptation measures put in

place. Vulnerability levelsvary within a system; therefore,

indicators are used to determine and measure it. Such indicators

can be the ecological,political, technological and socio-economic

factors of a system. Consequently, an assessment of vulnerability

to SLR requiresa method that takes into account various

indicators that reflect the effects of the SLR on the vulnerability

itself. Dueto the complex nature of a coastal system, such

methods include assumptions that simplify coastal processes in

order toenable the assessments to be useful.

One method to determine the values of the indicators

ofvulnerability to river floods, due to SLR, is to representdata in

geographic information systems (GIS), which enablescomparison

and deduction of the relationships between thesources of the data.

Heberger et al. (2009) used GIS andhydrodynamic modelling to

estimate the potential impactsof SLR on population,

infrastructure, ecosystems and property, in case a major flooding

event would occur on the riverdischarging into the sea. Data used

for the assessment wereDEMs, base flood elevation data,

population block data, hydrological data, tidal data, data on

geology, built-up area data,etc. The results combined inundation

and erosion layers withpopulation block layers to determine the

population at risk.Similarly, a GIS-based coastal vulnerability

assessment wascarried out by Martin et al. (2012), based on

physical andhuman-induced vulnerability. The physical factors

considered were coastal systems, hydrology (sediment supply)

andlithography, while the human influence factors were road

network, population density, population growth and urban

landcover. The result was combined with an urban growth model


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to show the influence of anthropogenic factors on the

finalvulnerability of the area.

Another method for assessing vulnerability is the

coastalvulnerability index (CVI), which relates various factors

thatinfluence the degree of vulnerability of coastal areas in

aquantifiable manner. The CVI concept introduced by Gornitz et

al. (1991) uses information about the coast to quantify the relative

vulnerability of coastal segments to effectsof SLR on a regional

and national scale. In their study, Gornitz et al. (1991) assessed

the vulnerability of the US coastto erosion and inundation effects

of SLR by ranking sectionsof the coast according to their

potential for change and relative importance for coastal

management. Since 1991, theCVI methodology has been applied

globally using differentvariables, depending on the coastal area

under study and theparticular hazard being anticipated.

Pendelton et al. (2010) and Dwarakish et al. (2009) usedsix

variables to assess the coastal vulnerability to sea levelrise and

coastal change for the northern Gulf of Mexico inMexico and the

Udupi coastal zone in India, respectively.These six variables are

geomorphology, coastal slope, meanwave height, mean tidal

range, rate of shoreline change, andrelative SLR, which are

considered physical variables thatcharacterise a coastal area, and

relate to the susceptibilityof the shoreline to natural changes and

its natural ability toadapt to changes in the environment.

The CVI method is based on physical coastal variables andis

therefore not easy to use for coastal management, whichwould

need variables related to social conditions and humanimpact on

the environment in order to determine a good viewof all aspects

entailed by the vulnerability of coastal areas.Consequently, a

modified CVI approach is developed, whichincludes variables

that represent social, economic, and human influence factors of

the coast. Ozyurt and Ergin (2009)propose an improved CVI for

SLR, and apply the methodology to assess the impact of SLR for

the Goksu Delta inTurkey. The approach uses seventeen physical

and humaninfluence variables, namely rate of SLR,

geomorphology,coastal slope, significant wave height, sediment

budget, reduction of sediment supply, river flow regulation,

engineeredfrontage, groundwater consumption, land use pattern,

natural protection degradation, coastal protection structures,

tidalrange, proximity to coast, type of aquifer, hydraulic

conductivity, depth to groundwater level above sea level, river

discharge, and water depth at downstream. The result shows the

vulnerability levels of defined coastal segments to different types

of impacts, and indicates that human impact on the environment

has the highest effect for inundation. The method however does

not consider social variables.

This study is structured in five parts. After the introduction and

review of vulnerability methods, the study area is presented,

followed by a short description of the applied methodology.

Results are presented in Sect. 4, followed by conclusions in Sect.

5.

II. STUDY AREA DESCRIPTION

The Niger Delta region sometimes called the Oil Riveris a low-

lying area consistingof several tributaries of the Niger River and

ending at theedge of the Atlantic Ocean. It consists of several

creeks, estuaries and mangrove swamp. The regionhas an area of

approximately 70,000 km2 makes up 7.5% of Nigeria‟s land

mass. It consist of the following states in Nigeria; Abia, Akwa

Ibom, Bayelsa, Cross River, Delta, Edo, Imo, Ondo, and Rivers

State andis home to about 31 million people of more than 40

ethnic groups including the Annang, Bini, Efik, Esan, Ibibio,

Ijaw, Ikwerre (Ihwuroha), Isoko, Itsekiri, Kalabari, Ogoni, Okrika

(Wakrike) ,Oron, Ukwuani, Urhobo.


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Nigeria‟s economy depends on oil and gas extraction from the

Niger Delta as the main source of foreign exchange; therefore,

many multinational oil and gas companies operate in the region,

and over 500 oil wells are located onshore. The extraction of oil

and gas has increased land subsidence in the delta, with values

estimated to range from 25 to125 mm yr−1 (Syvitski, 2008).

Land subsidence lowers the topography of delta areas with

respect to the sea and makes the relative sea level rise high. For

coastal areas, the relative sea level rise value is much more

important than the eustaticsea level rise.

Other environmental problems in the Niger Delta that canbe

further exacerbated by SLR include construction of dams in the

upstream and erosion of the coast. The Niger River hasa number

of dams constructed upstream of the Niger Delta,with a total

combined capacity of 30 billion m3. The construction of dams

reduced the estimated percentage sedimentto the Niger Delta by

70 % (NDRMP, 2004). Since deltasare replenished by upstream

sediment supply, this conditionmakes the Niger Delta vulnerable

to coastal erosion and landloss (IPCC, 2007c).

Erosion is already ravaging the Niger Delta, due mainly tonatural

causes (like river flow and ocean surge) and construction of

bridges, canals and other coastal structures, which altered the

natural course of the rivers (NDRMP, 2004). Based on population

figures of 1995, Awosika et al. (1992)estimated that 600 000

villagers in the Niger Delta wouldneed to be displaced in case of

a 1 m sea level rise. However, this estimate may be surpassed, as

the population of theNiger Delta increased with a growth rate of

over 3.1 % between 1991 and 2006 (NPC, 2010).

III. METHODOLOGY

A. Impact of Sea Level Rise on the Niger States in Nigeria

To view more closely the effect of SLR on the Niger Delta

coastline and highlight those towns with high potential risk of

SLR, a simulation for SLR was been conducted using the

Geographical Information System (GIS) and the Shuttle Radar

Topography Mission (SRTM) data. These data, which are widely

used in many scientific investigations, are considered to comprise

the best Digital Elevation Model (DEM) on a global scale with

consistency and overall accuracy (Suna et al., 2003; Ghoneim and

El-Baz, 2007, Ghoneim et al., 2007). Below are the results of this

simulation. The past century has witnessed a 17 cm rise in the sea

level (IPCC, 2001) at a mean rate of 1.75mm per year (Miller and

Douglas, 2004).

B. Sea Level Rise 1m

C. Sea Level Rise 2m

Taking into account the full “likely” range of predictedincreases

in temperature, SLR could even be amplified to up to 1.4 m by

the year 2100 (Rahmstorf, 2007). Other researchers have

predicted between 5-6 meters SLR in the event of the West

Antarctic Ice Sheet collapse (Tol et al., 2006). Without any doubt,

SLR is a global threat. With varying predictions on the extent of

SLR, based on different variables which cannot all be foreseen,

there is a near consensus on the need to apply precautionary

principles to global warming. This explains why studies of

impact, mainly those carried out by the World Bank, consider

SLR scenarios between 1-5 meters. The threat emerges from the

fact that a large percentage of the earth‟s population inhabits

vulnerable coastal zones. About 400 million people live within 20

km of a coast, worldwide (Gornitz, V., 2000).

D. Sea Level Rise 3m


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E. Sea Level Rise 4m

Worryingly, if the sea level rises by only 1 m, it would affect

more than 100 million individuals (Douglas and Peltier, 2002).

The coastal zone of the Niger Delta States in Nigeria is no

exception to the threat of SLR. Similar to many parts of the

world, capital cities and major towns that lie along the coast or on

estuaries.

IV. RESULT

Under the 1m SLR scenario, the simulation reveals that 21 towns

and 3 states of the Niger DeltaStates would be directly impacted

by the rise of the sea level.

Towns that would be affected for 1m simulation

S/N TOWNS X Y

1 Offorsuokiri 6.6808 4.4197

2 Ochokorocho 7.0166 4.6166

3 Ndoro Market 5.6 5.15

4 Kpongbokiri 6.2833 4.4

5 Kala Tuma 6.9305 4.5872

6 Kalafiogbene 5.6 5.15

7 Kalafigbene 5.6 5.15

8 Gbotebo Creek 5.45 5.1333

9 Fenipainga 6.9666 4.5519

10 Egbo-Ide (2) 5.75 5.3333

11 Egbo Ide 5.75 5.3333

12 Dempster Creek 5.4166 5.45


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13 Boler Creek 7.1333 4.55

14 Anu 6.7166 4.7955

15 Amukpe 5.7166 5.8666

16 Aghoro 5.45 5.1333

17 Adekagbene 5.6 5.15

18 Orotoh 6.9016 4.8716

19 Ngbetchurukiri 6.7541 4.803

20 Fenipanga 6.9666 4.5519

21 Kala Dabara 6.9416 4.5975

In the case of 2m scenario, the simulation reveals that 43 towns and 4 states would be affected.


S/N TOWNS X Y

1 Umuoparali 7.0166 4.6666

2 Segpe 5.8333 4.55

3 Samkiri 6.9902 4.673

4 Orukalama 6.8333 4.7

5 Ojiama 6.7833 4.7333


7 Ochokorocho 7.0166 4.6166

8 Nosworthy Point 7.1166 4.55

9 North Point 7.0666 4.5666


11 Namapogu 6.4666 4.5666

12 Mbiakpaba 6.2666 4.5666

13 Kpongbokiri 6.2833 4.4

14 Kala Tuma 6.9305 4.5872



17 Isampou 5.85 5.0666


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18 Isampo 5.85 5.0666

19 Harrys Town 6.7802 4.7994


21 Fenipainga 6.9666 4.5519

22 Fairweather Island 7.0666 4.5666

23 Egbo-Ide (2) 5.75 5.3333

24 Egbo Ide 5.75 5.3333

25 East Point 7.0666 4.5666


27 Boler Creek 7.1333 4.55

28 Ayama 7.3333 4.5666

29 Arugbana 7.0166 4.65

30 Anu 6.7166 4.7955

31 Amukpe 5.7166 5.8666

32 Amanku 7.3333 4.5666

33 Amabilou 5.7 4.9

34 Amabilo 5.7 4.9

35 Ajamangoro 5.5333 5.9333

36 Aghoro 5.45 5.1333


38 Orotoh 6.9016 4.8716


40 Fenipanga 6.9666 4.5519

41 Kala Dabara 6.9416 4.5975

42 Ngbetokurukiri 6.7541 4.803

43 Anu Settlement 6.7166 4.7955

In the case of 3mthe simulation reveals that 135towns and 7 states would be affected.


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S/N TOWNS X Y

1 Yaye 4.75 6.1333

2 Umuoparali 7.0166 4.6666

3 Ugbokodo 5.6833 5.5833

4 Udama 6.7833 4.7666

5 Tsekelewu 4.9833 5.9833

6 Tobacco Head 8.25 4.8833

7 River Talita 4.8166 6.3166

8 Seven Fathoms Point 8.2666 4.9

9 Seven Farthum Point 8.2666 4.9

10 Sereobia 6.7063 4.8483

11 Seregbia 6.7063 4.8483

12 Sarah 7.0833 4.6666

13 Sara 7.0833 4.6666

14 Samkiri 6.9902 4.673

15 Sacrifice Island 6.4 4.5333

16 Palmas Point 5.3 5.9166

17 Owupokuobu 6.9836 4.5144

18 Owupokuobo 6.9836 4.5144

19 Oweribobo 4.9166 6.25

20 Osokoma 6.0833 4.8

21 Osiama Creek 6.0666 4.75

22 Orusangama 6.5816 4.6763

23 Oroto 4.8 6.0833

24 Oroki Creek 5.3666 5.9666

25 Opu Ekweboko 6.9616 4.6913

26 Opolo 4.8166 6.3

27 Omifun Oke 4.6333 6.25

28 Olotu 4.7666 6.1166

29 Olokokiri 6.3161 4.5741

30 Ologi Creek 5.3666 5.9666

31 Olodiama 5.9666 5.15

32 Okusikiri 6.9819 4.523

33 Okuburi Creek 6.15 4.8666

34 Okomu Creek 5.0833 6.2333

35 River Okomu 5.0833 6.2333

36 Okokokiri 6.3161 4.5741

37 Okipirri 6.4 4.5333

38 Okipiri 6.4 4.5333

39 Ojiama 6.7833 4.7333

40 Oguburi River 6.15 4.8666

41 Ogubiri River 6.15 4.8666

42 Ogu 6.2722 4.9025

43 Ogoubiri 6.1166 5


45 River Ofara 4.8 6.35

46 Obote 4.75 6.1333

47 Obo 4.9166 5.9833



50 Namasibi 6.9825 4.6197

51 Namapogu 6.4666 4.5666

52 Moor Island 8.25 4.8833

53 Miller Island 5.5833 5.4

54 Mbiakpaba 6.2666 4.5666

55 Maran 4.6666 6.2

56 Manran 4.6666 6.2


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57 Mahin Lake 4.8166 6.1833

58 Mahin Lagoon 4.8166 6.1833

59 Mahin Creek 4.7666 6.1166

60 Mahin Canal 4.7666 6.1166

61 Lower Enyong Forest

Reserve 7.95 5.2666

62 Lodu Imenyi 5.5333 5.6333

63 Kotokoro Creek 5.05 6.25

64 Kotoko Creek 5.05 6.25

65 Kokotoro Creek 5.05 6.25

66 Kofewa 4.8 6.3833

67 Kala Tuma 6.9305 4.5872



70 James Flats 8.2666 4.8666

71 Ilowo 4.85 6.05

72 Ilepete 4.8666 6.0333

73 Ilegboro 4.8052 6.2569

74 Ijo Odo 4.7 6.1833

75 River Igbokoda 4.8166 6.3166

76 Igbokoda 4.8 6.35

77 Idogun 4.7333 6.15

78 Idiogba 4.7833 6.1

79 Ground Point 8.2833 4.8666


81 Galpin Creek 5.55 5.4

82 Gadege 4.8166 6.3166

83 Flag Point 8.2666 4.9166

84 Fenipainga 6.9666 4.5519

85 Eruna Odo 4.7833 6.1166

86 Eruna Eru 4.7666 6.1166

87 Eruna 4.7666 6.1166

88 Eliott Point 8.2833 4.8666

89 Elem Kalabari 6.9758 4.5741

90 Ekeresa 5.5833 5.7833

91 Egbo-Ide (2) 5.75 5.3333

92 Egbo Ide 5.75 5.3333

93 Duke Town 8.3166 4.9666

94 Diema 6.3319 4.3052


96 Dawes Island 7.0833 4.6666

97 Cross River Creek 8.2666 4.9166

98 Cross Bank 8.2666 4.9166

99 Caution Bank 8.2666 4.9166

100 Calabar River 8.2666 4.9

101 Calabar 6.9758 4.5741

102 Brass Town 6.2427 4.3169

103 Brass 6.2427 4.3169

104 Bokodo 5.6833 5.5833

105 Beletiama 6.2105 4.3183

106 Bassambri 6.4166 4.5333

107 Bassambiri 6.4166 4.5333

108 Basambiri 6.4166 4.5333

109 Awoye 4.9166 5.9833

110 Asisa 4.7166 6.1666

111 Ashisha 4.7166 6.1666

112 Arugbana 7.0166 4.65

113 Apostle Canal 4.7833 6.1

114 Apata 4.9 6.0333


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115 Anu 6.7166 4.7955

116 Amabilou 5.7 4.9

117 Amabilo 5.7 4.9

118 Allan Point 7.1666 4.5166

119 Alagbon 4.8 6.0833

120 Ajatitor 5.6833 5.5833

121 Ajapa 4.8333 6.0833

122 Ajamangoro 5.5333 5.9333

123 Aiyetoro 4.7833 6.1

124 Ago Forojo 5.05 6.25

125 Aghoro 5.45 5.1333


127 Aboto Creek 4.8166 6.3166

128 Abalala 4.6666 6.2166

129 Orotoh 6.9016 4.8716


131 Fenipanga 6.9666 4.5519

132 Kala Dabara 6.9416 4.5975



135 Okarki 6.4325 4.9827

In the case of 4mthe simulation reveals that 228towns and 7 states would be affected.


S/N TOWNS X Y

1 Yokri Sobo 5.2666 5.45

2 Yoki Village 5.2666 5.45

3 Yaye 4.75 6.1333

4 Winstanley Point 7.2333 4.5333


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5 Winstanley Head 7.2333 4.5333

6 Umuoparali 7.0166 4.6666

7 Ugbokodo 5.6833 5.5833

8 Udama 6.7833 4.7666

9 Ubat Mbat 8.1333 5.0833

10 Uba Mbat 8.1333 5.0833

11 Tsekelewu 4.9833 5.9833

12 Tobacco Head 8.25 4.8833

13 River Talita 4.8166 6.3166

14 Seven Fathoms Point 8.2666 4.9

15 Seven Farthum Point 8.2666 4.9

16 Sereobia 6.7063 4.8483

17 Seregbia 6.7063 4.8483

18 Segpe 5.8333 4.55

19 Sarah 7.0833 4.6666

20 Sara 7.0833 4.6666

21 Sangapiri 6.495 4.5583

22 Samkiri 6.9902 4.673

23 Sacrifice Island 6.4 4.5333

24 Palmas Point 5.3 5.9166

25 Owupokuobu 6.9836 4.5144

26 Owupokuobo 6.9836 4.5144

27 Owupoku 6.6952 4.3777

28 Oweribobo 4.9166 6.25

29 River Owena 5.1666 6.5666

30 Otu Creek 4.8666 6.4333

31 River Out 4.8666 6.4333

32 Otoka 6.1833 5.3333

33 Otaba 6.6866 4.833

34 Osokoma 6.0833 4.8

35 Osiama Creek 6.0666 4.75

36 Orusangama 6.5816 4.6763

37 Oroyo Zion 4.65 6.2333

38 Oroto 4.8 6.0833

39 Oroki Creek 5.3666 5.9666

40 Opu Ekweboko 6.9616 4.6913

41 Opuba Zion 4.9166 6.0666

42 Opomatobo 6.3475 4.66

43 Opolo 4.8166 6.3

44 Opobo Creek 7.2333 4.5333

45 Opobo Channel 7.2333 4.5333

46 Omifun Oke 4.6333 6.25

47 Olotu 4.7666 6.1166

48 Olokokiri 6.3161 4.5741

49 Ologi Creek 5.3666 5.9666

50 Olodiama 5.9666 5.15

51 Old Sangama 6.5925 4.6377

52 Okusikiri 6.9819 4.523

53 Okuburi Creek 6.15 4.8666

54 Okrika Creek 7.0833 4.7333

55 Okrika 7.0833 4.7333

56 Okpoma 6.2961 4.3033

57 Okoroboko 6.7288 4.5541

58 Okomu Creek 5.0833 6.2333

59 River Okomu 5.0833 6.2333

60 Okokokiri 6.3161 4.5741

61 Okipirri 6.4 4.5333

62 Okipiri 6.4 4.5333

63 Okikiri 6.8186 4.5363


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64 Okaiki Creek 6.5333 4.6

65 Ojiama 6.7833 4.7333

66 Ogulama 7.0833 4.7333

67 Oguburi River 6.15 4.8666

68 Ogubiri River 6.15 4.8666

69 Ogu 6.2722 4.9025

70 Ogoubiri 6.1166 5

71 Ogoloma 7.0833 4.7333

72 Ofoni 6.05 5.1


74 River Ofara 4.8 6.35

75 Odot Creek 8.1333 5.0833

76 Obote 4.75 6.1333

77 Obo 4.9166 5.9833

78 Obio Usiere 7.9666 5.2833

79 Obioku 6.5375 4.3375

80 Obagboro 5.5666 5.8166



83 Ndoro 5.6166 5.0833

84 Namasibi 6.9825 4.6197

85 Namapogu 6.4666 4.5666

86 Moor Island 8.25 4.8833

87 Miller Island 5.5833 5.4

88 Mbiakpaba 6.2666 4.5666

89 Mbasikiri 6.2561 4.4677

90 Maran 4.6666 6.2

91 Manran 4.6666 6.2

92 Mahin Lake 4.8166 6.1833

93 Mahin Lagoon 4.8166 6.1833

94 Mahin Creek 4.7666 6.1166

95 Mahin Canal 4.7666 6.1166

96 Mahin 4.8 6.1666

97 Lower Enyong Forest

Reserve 7.95 5.2666

98 Lodu Imenyi 5.5333 5.6333

99 Lelekiri 6.7744 4.6663

100 Kugbo Creek 6.5333 4.6

101 Kpokpo 5.2333 5.5833

102 Kotokoro Creek 5.05 6.25

103 Kotoko Creek 5.05 6.25

104 Kokotoro Creek 5.05 6.25

105 Kofewa 4.8 6.3833

106 Kekere 5.1666 6.5666

107 Keboko 6.8277 4.5166

108 Kala Tuma 6.9305 4.5872



111 James Flats 8.2666 4.8666

112 Ilowo 4.85 6.05

113 Ilepete 4.8666 6.0333

114 Ilegboro 4.8052 6.2569

115 Ikirikokiri 6.5333 4.4327

116 Ikei 6.3683 4.3147

117 Ijo Odo 4.7 6.1833

118 Ijokiri 6.6063 4.4486

119 Igbotu 4.9 6.4333

120 River Igbokoda 4.8166 6.3166

121 Igbokoda 4.8 6.35


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122 Idogun 4.7333 6.15

123 Idiogba 4.7833 6.1

124 Ibaka 7.0833 4.7333

125 Hole in the Wall Creek 5.4166 5.5833

126 Harrys Town 6.7802 4.7994

127 Ground Point 8.2833 4.8666


129 Galpin Creek 5.55 5.4

130 Gadege 4.8166 6.3166

131 Frankkiri 6.6063 4.4486

132 Flag Point 8.2666 4.9166

133 Fenipainga 6.9666 4.5519

134 Fatumakiri 6.3 4.5833

135 Eruna Odo 4.7833 6.1166

136 Eruna Eru 4.7666 6.1166

137 Eruna 4.7666 6.1166

138 Enyong Creek 7.95 5.2833

139 Enikorogha 4.8666 6.4333

140 Emelesua 6.6975 4.8433

141 Eliott Point 8.2833 4.8666

142 Elem Kalabari 6.9758 4.5741

143 Elem Abissa 6.7838 4.4288

144 Elder Creek 5.4166 5.5333

145 Ekernakiri 6.3197 4.4344

146 Ekeresa 5.5833 5.7833

147 Ekemakiri 6.3197 4.4344

148 Egbo-Ide (2) 5.75 5.3333

149 Egbo Ide 5.75 5.3333

150 Ebukama 7.4333 4.5

151 Duke Town Point 8.3166 4.9833

152 Duke Town Crossing 8.3 4.9833

153 Duke Town 8.3166 4.9666

154 Diema 6.3319 4.3052


156 Dawes Island 7.0833 4.6666

157 Dariama 6.9422 4.4822

158 Dannykiri 6.5333 4.4327

159 Cross River Creek 8.2666 4.9166

160 Cross Bank 8.2666 4.9166

161 Clarendon Island 6.11 4.3952

162 Caution Bank 8.2666 4.9166

163 Calabar River 8.2666 4.9

164 Calabar Crossing 8.3 4.9833

165 Calabar 6.9758 4.5741

166 Bumodi Creek 5.5 5.1

167 Brass Town 6.2427 4.3169

168 Brass 6.2427 4.3169

169 Bomadi Creek 5.5 5.1

170 Bokodo 5.6833 5.5833

171 Blind Creek 7.5166 4.5666

172 Bille 6.8886 4.5769

173 Bile 6.8886 4.5769

174 Benin Creek 5.4166 5.5833

175 Beletiama 6.2105 4.3183

176 Basuokiri 6.3 4.5833

177 Bassambri 6.4166 4.5333

178 Bassambiri 6.4166 4.5333

179 Basambiri 6.4166 4.5333

180 Barapakama 6.6111 4.4619


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181 Ayama 7.3333 4.5666

182 Awoye 4.9166 5.9833

183 Awiakalakala 6.3452 4.6491

184 Asisa 4.7166 6.1666

185 Ashisha 4.7166 6.1666

186 Arugbana 7.0166 4.65

187 Apostle Canal 4.7833 6.1

188 Apata 4.9 6.0333

189 Anu 6.7166 4.7955

190 Amanku 7.3333 4.5666

191 Amakalakala 6.3452 4.6491

192 Amabilou 5.7 4.9

193 Amabilo 5.7 4.9

194 Allan Point 7.1666 4.5166

195 Alagbon 4.8 6.0833

196 Alagbaefe 6.34 4.5158

197 Aladje 6.1833 5.3333

198 Aladja 6.1833 5.3333

199 Akwamobugo Creek 6.3833 4.3666

200 Akugbene 5.85 5.2666

201 Ajatitor 5.6833 5.5833

202 Ajapa 4.8333 6.0833

203 Ajamangoro 5.5333 5.9333

204 Aiyetoro 4.7833 6.1

205 Ago Forojo 5.05 6.25

206 Aghoro 5.45 5.1333

207 Agada 6.4863 4.5972

208 Afoni 6.05 5.1

209 Adumama 6.5333 4.3666


211 Aboto Creek 4.8166 6.3166

212 Abalala 4.6666 6.2166

213 Orotoh 6.9016 4.8716


215 Okpo 6.7955 4.7966

216 Degema Hulk 6.75 4.7625

217 Ekanakiri 6.3197 4.4344

218 Allagbafeu 6.34 4.5158

219 Owupubo 6.6952 4.3777

220 Elem Abisse 6.7838 4.4288

221 Fenipanga 6.9666 4.5519

222 Temakiri 6.8627 4.5236

223 Kala Dabara 6.9416 4.5975

224 Oruama 6.4016 4.5325

225 Abelkiri 6.7775 4.7175



228 Okarki 6.4325 4.9827

CONCLUSION

Highly vulnerable coastlines expose the inland areas to effects of

SLR, serving as a gateway for inundation, stormsurge and coastal

erosion. The results of the spatial analysis for the Niger Delta

highlighted towns of the coast is that highly vulnerable to effects

of SLR like flooding, erosion, and salt water intrusion into

underground aquifers. These areas of the coast need to be

protected against the negative effects of SLR.

Human influence on coastal environments can affect sediment

supply and accelerate erosion, and should therefore becaptured in

vulnerability assessments. Analysis of social andhuman influence

variables shows that in terms of type ofaquifer, aquifer hydraulic

conductivity, population growth, sediment supply, and

groundwater consumption, the NigerDelta is vulnerable to the

effects of SLR. Moreover, the location of many settlements in

remote areas, far away fromthe local government headquarters,

reduces the value of resilience to the effects of SLR.

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