International Conference on Earth, Environment and Life sciences (EELS-2014) Dec. 23-24, 2014 Dubai (UAE)

Flood Vulnerability Classification of Lafia Township, ,

W.T. Ayuba

Abstract–The flood vulnerability classification of Lafia In Nigeria, the hydrological changes associated with Township was done using the flood risk assessment of 16 flood- urbanization have received numerous attention (Ologunorisa, prone areas. 300 copies of questionnaires were administered to 300 and Abawua, 2006). Various factors, including topographical flood plain dwellers. Three flood risk zones were obtained consisting conditions, rainfall characteristics and land use have been of high flood risk, moderate flood risk and low flood risk. Heavy adduced as the major causes of flooding in our cities rainfall of long duration and river overflow were identified as the most prominent causes of flooding in Lafia. Analysis of the (Ologunorisa, 2001). The human factors especially increase in behavioural responses of flood plain dwellers shows that majority of paved area; refuse disposal habit and occupation of the flood them have knowledge of the hazard before moving to the area, but plain were emphasized by Adefolalu, (2000) while Trevor, consider the flood hazard either of little significant or insufficient (2010) emphasized the role of rainfall amount and intensity. It enough to force them to seek alternative. The research therefore is against this background that the paper is focused on flood concludes that it will be desirable to intensify efforts on flood vulnerability classification in Lafia. prevention and control as well as entrenching abatement management strategies in zone I and II which are high and moderate flood risk areas respectively, while impacts mitigations measures could be II. THE STUDY AREA enforced in zone III. Lafia is both the Capital of Nasarawa State and Keywords---Degree of risk, Flood, Flood risk classes, headquarters of Lafia Local Government Area. The Local Vulnerability. Government Area has a land area of 2,797.5 sq. km with a population of three hundred and thirty thousand, seven I. INTRODUCTION hundred and twelve people (330,712 persons) (NPC, 2007). LOODS are the most common and widespread of all Lafia is located between latitudes 80201N and 80381N and F natural disasters (Ologunorisa, 2006). Many countries between longitudes 80201E and 80401E (see fig. 1). around the world experience some kind of flooding. Examples of such flooding include settlements around the Nile River in Egypt, Mississippi River in U.S.A., the Ganges in Bangladesh, the Rhine in Germany, Thramans River in Britain, the Kalimantan in Indonesia and in Nigeria along the major rivers like Niger, Benue and the River Basin as well as Niger Delta. Damage to property in urban areas due to floods run into huge sums of money when quantified in most cases and sometimes human and animal lives are lost. The United States, for examples, estimated an annual loss of property to flood at $12 billion in 1978 (Ologunorisa, 2006). Fig. 1 Nasarawa state in Map Showing Lafia Local Government Area Today, many countries are trying to reduce property Source: Nasarawa State Information Bulletin, 2011 damage and loss of human lives to floods through flood Lafia falls within the low land area of the Benue trough. prediction and by creating a database of flood hazard areas. It Lafia and its surrounding settlement are within the Mada River has been shown by various studies that floods can be more Basin of the Benue valley platform. The area is largely an effectively managed when flood predictions are undulating plain which is drained by the Benue River, River complemented with maps of flood risk zones (Blong, 2003; Mada of Guma and Ankwe River. The town has five months Sanyal and Lu, 2003). However, like many other natural of dry season and seven months of rainy season. The peak of hazards, floods may also bring benefits such as the recharge of the rain is in July and October each year. The rains start by ground water and deposition of silty materials quite useful for April and ends in October each year with an average of agricultural purposes (Barroca, 2006). 131.75mm to 141.5mm annually (NIMET, Lafia 2013). Lafia

town is within the Southern Guinea Savanna Vegetation belt

(Lyam, 2000). W.T. Ayuba, Department Of Geography, College Of Education , Nasarawa State, Nigeria

http://dx.doi.org/10.15242/IICBE.C1214016 134 International Conference on Earth, Environment and Life sciences (EELS-2014) Dec. 23-24, 2014 Dubai (UAE)

III. MATERIALS AND METHODS Both primary and secondary data were used for this study. The analytical technique employed include simple linear The primary data include information on flood perception and regression analysis for determining rainfall trend while the adjustment, and other socio-economic losses suffered during statistical packages employed include Ms Excel as well as floods. This was collected directly from the field using the SPSS version 17 statistical packages for the rainfall and the questionnaire. questionnaire data. Rainfall Trend Analysis of the study area Sixteen flood vulnerable neighbourhoods were identified is shown in fig.2 (a), 2(b), 2(c) and fig.3 below. and used as clusters for the collection of primary data and for flood risk zone classification. These neighbourhoods are: Tudun-Kauri, Sabon Pegi, GSM Village, Emir’s Palace, River Amba flood plains, Angwan-Kutare, Angwan-Jabba, Bukan Sidi, Awe street, Lubona junction, Shendam road, Shinge road, Tudun Gwandara, Rice mill area, UAC area as well as Kilima. A total of 300 samples were taken from the sixteen neighbourhoods based on their population and questionnaires were administered on flood plain dwellers within the neighbourhoods. A systematic sampling technique was employed using a sample interval of 25 for the sixteen neighbourhoods. The sample represents 10% of the study Fig. 2(a) Graph showing Total Rainfall (mm) Trend from 1980-1990 population. Secondary data on hydro-meteorological parameters was also collected from the Nigerian Meteorological Office in Lafia town. This included daily rainfall data covering a period of 30 years (1980-2010) see Table 1. TABLE I SHOWING RAINFALL DATA FROM 1980-2010 IN LAFIA

MONTH/ YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC 1980 0 31.8 0 80.5 35.9 28.9 65.7 67.7 45.9 67.9 24.1 0 Fig. 2(b) Graph showing Total Rainfall (mm) Trend from 1991-2001 1981 0 0 0 65.3 67.9 68.8 34.9 20.8 67.9 64.3 9.7 0 1982 0 0 0 20.9 34.9 42.8 36 50.6 45.9 99.5 0 0 1983 0 30.6 0 0 39.2 38.5 97.9 31.9 45.9 26 0 0 1984 0 0 0 69.8 69.4 88.9 37.9 80 56.9 37.9 0 0 1985 0 0 5.5 70.5 86 34.7 56.9 80.9 87.9 60 0 0 1986 0 0 10.5 56.1 90.1 30.6 60 38 89 80.1 0 0 1987 0 0 4.1 60.2 80.3 40.9 30 55.9 38 50.1 0 0 1988 0 0 2.2 58.1 35.9 40.7 40.8 50.9 30.7 69.4 0 0 1989 0 0 3.1 48.2 76.1 29 60.1 30.1 50.5 86.4 0 0 1990 0 0 4.1 40.1 84.3 190.1 170.1 290.2 260.1 90.1 0 0 1991 0 0 19 56.2 23.3 101.3 190.1 305.2 222.3 77.2 0 0 1992 0 0 15.1 60.1 56.1 58.2 87.2 280.3 203.5 68.3 0 0 1993 0 0 16.3 44.8 270 309.9 311.1 296.9 280.1 11.1 0 0 1994 0 0 0 0 222.8 341 266.7 300 211.2 89 0 0 1995 0 0 0 0 60.9 288.4 306 400.7 211.7 90 0 0 1996 0 0 0 0 191.9 255.6 310.7 361.2 200.7 61.1 0 0 1997 0 0 0 13.9 300 211.7 45.9 394.7 200 40 0 0 1998 0 0 0 0 82.8 112.1 200 301.2 190.1 29.1 0 0 1999 0 0 0 40.2 0 185.5 188.7 284.2 197 39 0 0 Fig. 2 (c) Graph showing Total Rainfall (mm) Trend from 2001-2010 2000 0 30.6 0 0 39.2 238.5 140.5 310.7 101.3 86.1 0 0 2001 0 0 0 182.9 230.4 114.6 251.5 229 223.6 42 0 0 2002 0 0 0 64.4 186.7 68.8 323.8 342.2 224.8 76 0 0 2003 0 4.9 0 129.1 172.6 76.9 102.6 332.9 248 105 0 0 2004 0 0 1 56.8 124.3 373.3 213.7 310.2 159.4 58 0 0 2005 0 0 57.7 43.2 161.7 106.3 242 350.2 151.4 16.9 0 0 2006 0 0 14.5 1.5 224.7 160.3 318.3 250.9 293 84.1 0 0 2007 0 0 0 83.5 104.4 258.3 244.3 222.9 223.5 250.3 0 0 2008 0 0 14.2 91.8 185.5 229.4 188.3 240.5 109 76.9 0 2 2009 0 0 20.5 100 205 240.1 260 300 250 80.1 0 0 2010 0 0 16.1 96.5 195.1 220 230 310 340.1 96.1 0 0 Source: Nigerian Meteorological (NIMET) Agency, Lafia.

Relevant flood data in Lafia such as flood depths, flood duration and level of damage were obtained using direct field observation and measurements. Flood depths were measured using ranging poles while flood duration and level of damage were obtained using questionnaire administered on flood plain

dwellers. Fig. 3 Graph showing the Rainfall Trend Analysis from 1980-2010

http://dx.doi.org/10.15242/IICBE.C1214016 135 International Conference on Earth, Environment and Life sciences (EELS-2014) Dec. 23-24, 2014 Dubai (UAE)

The above figures shows that Lafia has a positive The parameters were selected because of the fact that they correlation which indicates upward annual rainfall trends and are capable of truly measuring flood risk. They are believed to consequently, the possibility of flooding. The result of the be capable of doing this because previous scholars upward trends of Lafia is statistically significant since p<0.5 (Ologunorisa, and Abawua, 2006) have shown that they have (alpha level) an indication that the upward trend could be strong positive bearing on flood generating and vulnerability random. components of flood hazard. Also, the parameters selected are The flood vulnerability classification map of the study area easy to measure and quantify. Finally, it is also believed that was done based on the flood vulnerability assessment of they will clearly bring out internal variations within the study environmental parameters of 16 flood-prone areas used in the area. study. The flood vulnerability was done in two stages. The The second state involves the quantitative rating and first step involves the identification of the most important assessment of the environmental parameters (hazard and environmental parameters (that is hazard and vulnerability vulnerability factors) in the selected settlements for flood risk indices) influencing flood vulnerability. These indices are: mapping based on the rating scales devised in this study. depth of flooding (meters) duration of flood (hours/weeks), In devising the scale for measuring, the nine environmental perceived frequency of flood occurrence, perceived extent of parameters, emphasis was placed on the range of values damage arising from flood, percentage deviation of seasonal obtained during field work. The rating procedure adopted was rainfall (mm) from the mean, area or location/relief, proximity base on Clark’s principle (Clark, 1951). This entails to hazard source (e.g. to source of river), land use or dominant multiplying the scores of the nine parameters selected in this economic activity and adequacy of flood alleviation measure. study in each settlement to give the settlements flood risk The scale used for the scoring of the parameters are shown index for land use planning. By multiplying the scores, the in Table 2 while Table 3 shows flood risk classes and Table 4 flood risk in each settlement will be limited to least favourable shows flood risk indices for land use damage. parameters influencing flood (that is the laws of minimum). This is preferred to additive method of computing indices TABLE II which assumed the different parameters add together without GRADUATED SCALES FOR SCORING THE PARAMETERS USED IN DEFINING FLOOD RISK interference (Gbadegesin, and Nwagwu, 1990). In this S/N PARAMETERS RANGE OF VALUES SCORE method, the higher the value of the risk index, the higher the 1. Depth of flooding (m) <1.0 metres 1 degree of risk. 1 – 2.0m 2 Based on the rating scales in Table 2 three flood risk classes > 2m 3 were obtained and shown in Table 3 while Table 4 shows the 2. Duration of floods < 12 hours 1 (hours/weeks) 12 – 24 hours 2 computation of the flood risk indices for the data collection in > 24 hours 3 the selected flood-prone areas used in the study. The flood risk 3. Perceived frequency of Once in 5 years or more 1 classes obtained in Table 3 were used to divide the study area occurrence Once in 3 years 2 into flood risk zones for land use planning and property Once in a year 3 values. 4. Extent of damage in < 25 percent 1 The resulting flood risk map consisting of three zones is percentage 26 – 50 percent 2 > 50 percent 3 shown in fig. 4. The first zone consists of area of high flood 5. Percentage deviation of < 25 percent 1 risk, and these include Emir’s Palace, Kilima, Rice Mill Area, seasonal rainfall (mm) 26 – 50 percent 2 Tudun Kauri, Angwan Jabba, Angwan Kutare and River from the normal > 50 percent 3 Amba Area. The second zones are moderate flood risk area average and include UAC Area, GSM village, Sabon Pegi, Bukan Sidi, 6. Location/relief in > 15 percent 1 Awe Street, and Lubona Junction. While the third zone meters above sea level 1 – 15 percent 2 < 5 meters 3 consists of low flood risk and these include Tudun Gwandara, 7. Proximity to hazard > 200 meters 1 Shinge Road and Shendam Road respectively (see fig. 4). source in meters 100 – 200 meters 2 < 100 meters 3 8. Perceived adequacy of > 50 percent 1 flood control measures 25 – 50 percent 2 in percentage < 25 percent 3 9. Dominant land use or Agricultural/residential 1 economic activity planned and unplanned 2 industrial/commercial 3 Source: Adapted from Ologunorisa, 2006.

TABLE III FLOOD RISK CLASSES FOR LAND USE PLANNING

S/N FLOOD RISK INDICES FLOOD RISK CLASS REMARKS 1. < 100 I Low flood risk 2. 100 – 600 II Moderate flood Fig.4 Flood Risk Map of Lafia risk Source: Field Survey, 2011. 3. > 600 III High flood risk

Source: Adapted from Ologunorisa, 2006.

http://dx.doi.org/10.15242/IICBE.C1214016 136 International Conference on Earth, Environment and Life sciences (EELS-2014) Dec. 23-24, 2014 Dubai (UAE)

TABLE IV neither do they have an idea of flood insurance scheme as a COMPUTATION OF FLOOD RISK INDICES FOR LAND USE PLANNING means of flood adjustment or reducing the impact of flooding. Moreover, results of the seasonal flood risk assessment

indicate that there is no flood at all during the dry season months of November to April. Also, the month of May marks

the beginning of floods season. During the month of May

viation Measures there is “low flood risk” in the entire study area. Also that during the month of June, “moderate flood risk” is

experienced in the whole study area, while the months of July to October are periods when the entire study area experience “high flood risk”. In terms of spatial variations in the level of S/N Settlement ofDepth Flooding Meters in DurationHours/Weeks PerceivedFrequency of Flood Occurrence Extentof Damage Percentage in PercentageSeasonalDeviation of Rainfallfrom theMean Locationor Relief ProximityHazardSource to Adequacyof Alle DominantEconomicActivity FloodIndex Risk FloodClass Risk high floods emir’s palace, kilima, rice mill area, Tudun Kauri, 1. Tudun Kauri 2 3 3 3 3 3 2 3 1 2916 III 2. Sabon Pegi 1 2 2 2 2 1 1 3 3 144 II Angwan-Jabba, Angwan-Kutare, as well as River Amba areas 3. GSM Village 2 2 3 3 2 1 1 3 2 432 II are very critical zones of high flood risk, where settlements are 4. Emir’s Palace 2 3 3 3 3 2 3 3 2 5832 III 5. River Amba Area 3 3 3 3 3 3 3 3 2 39366 III displaced by floods.

6. Angwan Kutare 2 3 3 3 3 2 3 3 1 2916 III V. CONCLUSION 7. Angwan Jabba 2 3 3 3 3 2 3 3 1 2916 III 8. Bukan Sidi 2 1 3 3 2 1 1 3 2 216 II Lafia town has been classified into three flood vulnerability 9. Awe Street 2 1 3 2 2 1 1 3 2 144 II 10. Lubona Junction 2 2 2 3 2 1 1 3 2 288 II zones base on flood generating mechanism. Base on the above 11. Shendam Road 1 1 1 1 2 1 1 1 1 02 I findings, it will be desirable to intensify efforts on flood 12. Shinge Road 1 1 1 1 3 1 1 1 1 03 I control and abatement management strategies in zone I and II 13. Tudun Gwandara 1 1 1 1 2 1 1 1 2 04 I 14. Rice Mill Area 2 3 3 2 2 2 3 2 1 864 III which are high and moderate flood risk areas. Also, in zone I 15. UAC Road 2 2 3 3 2 1 1 3 2 432 II it might be necessary to discourage large scale investment and 16. Kilima 3 3 3 3 2 2 3 1 1 972 III human occupation through the regulation of land use and the

Source: Derived from computation of Rainfall Data. maintenance of adequate flood ways. Some devices may be introduced such as channel encroachment statutes, (such as IV. RESULTS AND DISCUSSION permanent evacuation) and setting of setback lines of at least 100 meters from hazard source, critical to successful adoption The following findings have become obvious from the of such measure are environmental education and the precise study. First, the analysis of annual rainfall trend shows that analysis of the physical geography of Lafia and the appraisal Lafia has a positive correlation which indicates upward annual of development potential in terms of such analysis. In case of rainfall trends and consequently the possibility of flooding. permanent evacuation, we may begin to think of resettlement The result of the upward trends of Lafia is statistically of flood displaced people to areas of low flood risk. While significant since P<0.5(alpha level), an indication that the impacts mitigation measures could be enforced in zone III for upward trend could be random. Secondary, there is consistent sustainable development. increase in rainfall amount towards the later part of the 1990s. Thirdly, results also show that the frequency of heavy ACKNOWLEDGMENT rainfall equal or greater than 25.00mm from July to October constitutes the flood season in the study area. This research acknowledges the support from the Tertiary Fourthly, analysis of behavioural responses of the flood Education Trust Fund (TETFUND), - Nigeria. plain dwellers to the hazard of flood revealed that the population has fair idea of some of the causes of flood hazards REFERENCES in Lafia of which heavy rainfall of long durations and river [1] G.R. Clarke, (1951). The Evaluation of Soils and the Definition of Soil overflow are the most prominent causes. Majority of them Classes from Studies of the Physical Properties of the Soil Profile in the have stayed in the area for a considerable period of 12 years Field. J. Soil Science 34,639-647. and above. Also, the populations were aware that the area they [2] A. Gbadegesin, and U. Nwagwu, (1990). On the Suitability of the Forest and Savanna Ecological Zones of Southwestern Nigeria for live or farm on was subject to flooding. It rather seem that for Maize Production. Agriculture, Ecosystem and Environment, 31, pp.99- the majority of the respondents, the flood hazard is either of 113. little significant or insufficient enough to force them to http://dx.doi.org/10.1016/0167-8809(90)90213-W consider alternative. Also, the respondents in the study area [3] A.A. Lyam, (2000). Nigeria: A People United A Future Assured Survey of States Vol. II. Gabumo Publishing Co. Ltd, . are so attached to their native land and therefore, unwilling to [4] NIMET (Nigeria Meteorological Agency Lafia), Daily/ Monthly consider option. This mentality has made them to suffer Climatic Data 1980-2010. several losses from flood. [5] NIMET (Nigeria Meteorological Agency Lafia), Daily/Monthly In addition, the duration of floods in the study area last for a Climatic Data 2013. [6] National Population Commission (NPC) 2007. Federal Republic of period less than 4 hours, and the level of flood water is as high Nigeria Official Gazette No.24 Vol. 94. as 1 meter and above during flood season. Also flood victims [7] E.T. Ologunorisa, (2001). An Assessment of Flood Risk in the Niger spend 3-4 days outside their homes during flood. Furthermore, Delta, Nigeria. Unpublished Ph.D Thesis, Department of Geography majority of the flood victims do not get compensated or relief and Environmental Management, University of , Port Harcourt, 303pp.

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[8] J. Sanyal, and X.X. Lu, (2003). ‘Application of GIS in Flood Hazard Mapping: A Case Study of Gangetic West Bengal, India’. Proceedings of Map Asia 2003, Malaysia. [9] E.T. Ologunorisa, and Abawua, (2006). Flood Risk Assessment. A Review of Journal of Applied Science and Environmental Management Vol.9, N0. 1, pp57-63. [10] E.T. Ologunorisa, (2006). Flood Risk Assessment and Management in Nigeria. Perspective from the Niger Delta. Selfers Educational Books , Nigeria. [11] L. Barroca, (2006). Indicators for Identification of Urban Flooding Vulnerability. National Hazards Earth System, Science 6:553-561 http://dx.doi.org/10.5194/nhess-6-553-2006. [12] R. Blong, (2003). A Review of Drainage Intensity Scale. National Hazards Earth systems, Science, 29:57-76. [13] D.O. Adefolalu, (2000). Effects of Climate Change and Freshwater Resources. Federal University of Technology, Mina, Nigeria. [14] J. Trevor, (2010). “Northern Nigeria Hit by Flood”. www.wsws.org/articles/2010/oct.2010/nig-005. Assessed on the 30th June, 2011.

Wakayi, Thomas Ayuba obtained his first degree (Bsc.Hons.) Geography from the University of , Nigeria in 1996,Post Graduate Diploma in Education (PGDE) from the National Teachers’ Institute ,Nigeria in 2007 and a Master of Science (Msc.) degree in Environmental Resource Management from the Nasarawa State University ,Nigeria in 2014.He is presently a Senior lecturer with the Department of Geography, College of Education Akwanga, Nasarawa State, Nigeria.His area of research includes Environmental Resource Management and Sustainable Development. He has published several books and book chapters as well as numerous articles in academic journals including Assessment of the Effects of Urban Flood in Lafia Township, Nasarawa State, Nigeria, “Readings in Geography”, Stochastic Modeling of Thunderstorm Frequency Over Nigeria, Climatic Change Scenario, Drought Analysis Versus Perception in Borno State, Nigeria, etc.

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