Assessing Vulnerability of Rural Households in Benue, Nigeria

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Assessment of Vulnerability of Rural Households to Climate
Hazards in Mountainous Area of Kwande Local Government
5th International Disaster and Risk Conference IDRC 2014
‘Integrative Risk Management - The role of science, technology & practice‘ • 24-28 August 2014 • Davos • Switzerland
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Area, Benue State, Nigeria
Bernard Tarza Tyubee1 and Iankaa Aguse2
1Department of Geography, Benue State University, Makurdi,
Nigeria.
2Trinity Secondary School, Dagba-Adagi, Adagi, Nigeria.

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Outline of Presentation
 Rational of the Study
 Study objectives
 Methods
 Results
 Conclusion
 Added value for the Post 2015 Framework for Disaster Risk
Reduction
 References

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1. Rational of the Study
 On the night of October 17th, 2010, thunderous landslide occurred, in
eight locations, in mountainous area of Kwande LGA, Benue State, Nigeria
(Figure 1).
 The accompanied sound was heard several kilometers away causing panic
and anxiety in the region.
 The thunderous sound was erroneously reported in the media, the
following day (18/10/2010), as “earthquake” or “volcanic eruption” which
further heighten panic and anxiety in the region.
 Several thousand tons of debris comprising soil, rocks and mud were
brought and deposited down slope
 Several arable farms and tree crops were destroyed and 1 person was
declared missing during the disaster.
 The event of October 17th, 2010:
 Showed how vulnerable the area is to climatic hazards
 Underscored the need to assess the level of vulnerability of households
living in the area to climate hazards for the purpose of climate change
adaptation.

Figure 1a: Landslide in Woikyor, Kwande LGA (B in
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Figure 2) – Upper slope

Figure 1b: Landslide in Woikyor, Kwande LGA (B in
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Figure 2) – Lower slope

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Figure 2: Kwande LGA, Benue State, Nigeria
Location, Facts and Figures
Kwande Local Government Area (LGA),
is one of the 23 LGAs in Benue State,
Nigeria.
Location: Latitudes 6o 30ᴵ and 7o 03ᴵ N
and Longitudes 9o and 9o 40ᴵ E (Figure 2).
Total area: 2, 300km2
Population: 180, 327 people (1991) and
248, 642 people (2006).
It shares boundaries with Katsina Ala
LGA, Benue State, in the north; Ushongo
LGA, Benue State, in the Northwest;
Taraba and Cross River States in the east
and south and Republic of Cameroon in
the Southeast.
 Relief: Highland and hilly terrain,
especially along the boundary with Cross
River State and Republic of Cameroon
where the elevation is above 1,000m
above mean sea level.
Climate: Annual rainfall varies from
1200 – 1800mm and the mean annual
temperature ranges from 23oC – 27oC.
Vegetation: Savannah and Forest

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2. Objectives of the Study
 To investigate the major climate hazards
 To analyze variation in the level of vulnerability of households
to climate hazards
 To assess adaptation strategies of households to climate
hazards

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3. Methods
3.1 Objective 1: To investigate the Major Climatic Hazards
 Climate hazards, in this study, include both climate-related and
climate-induced events that threatened life, property and ecology
which supports the livelihoods of households, and also vary among
households.
 These include landslide/mudslide, flooding, rock fall, erosion, high
temperature, drought, storms and cold spells. Extreme rainfall is
excluded because there is no marked spatial variation in the area.
 Data were collected on the frequency of occurrence and cost of
damage to property of the hazards.
 Frequency of occurrence of climate hazard events was categorized
into five classes namely:
 Yearly
 2-3 years
 4-5 years
 above 5 years (occasional)
 Never experienced

 The aggregate mean damage per event (Naira) was categorized into
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five classes namely:
 < 100, 000
 100, 000 – 200,000
 200, 000 – 400, 000
 400, 000 – 600, 000
 >600, 000
 Data on the major climate hazards were collected using focus group
discussion (FGD). The FGD comprised all household heads that are
at least 50 years of age and have lived in the area for at least 30
years (1981 – 2010).
 The number of household heads selected for the FGD were 10 each
in Bawaan,Woikyor and Womondo zones (Figure 2) respectively.
 Data were analysed using tabulation.

3.2 Objective 2: To analyze variation in the level of
vulnerability of rural households to climate hazards
Definition of Vulnerability
 In the study, vulnerability is defined, from the perspective of
climate change adaptation, as the degree to which a system is
susceptible to, and unable to cope with, the adverse effects of
climate change, including climate variability and extremes.
Vulnerability (V) is a function of exposure (E), sensitivity (S) and
adaptive capacity (AC) (Parry et al., 2007)
Vulnerability Factors
 Nine vulnerability factors were used in the study comprising:
 Slope and distance to river (E);
 Household size, household income, occupation of household heads
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and sources of household water supply (S); and
 Health care centers, roads and schools (AD).

Sampling of Households
 Households used in the study are those living in the areas of Kwande LGA
with a minimum elevation of 630m above sea level. These comprised
Bawaan (A), Woikyor (B) and Womondo (C) areas referred to as zones
(Figure 2). “Wo” means mountain in the local dialect.
 During a reconnaissance survey, a total of 101 households were identified
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in the three zones comprising:
 25 households in Bawaan (A),
 38 households in Woikyor (B)
 35 households in Womondo (C)
 A table of random numbers was used to select 50 households for the
study using the surnames of household heads . These comprised:
 14 households in Bawaan,
 19 households in Woikyor
 17 households in Womondo
Procedure of Vulnerability Assessment:
 The following procedure was adopted in the vulnerability assessment

 The nine vulnerability factors were first mapped on a 1- 7 vulnerability scale ranging
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from:
1 - very resilient
2 - resilient
3 - at risk
4 - vulnerable
5 - significantly vulnerable
6 - very vulnerable, and
7 - extremely vulnerable
 In order to obtain approximate linearity of response for each factor, different response
classes were then defined corresponding to different scoring of the factors raw values
into the 1 – 7 scale (Villa and McLeod, 2002).
 For the E and S factors, 7 and 1 reflect the maximum and minimum incidence or effects
while for AD factors, 7 and 1 reflect the minimum and maximum incidence or effects.
This is because V is directly related to E and S and inversely related to AD.
 The design of the response classes was based on studies by Kaly et al (1999) and Tyubee
et al (2010) and were checked for quality control during reconnaissance survey.
 All the nine factors were not weighted because they were presumed to have equal
contribution to household’s vulnerability in the study.
 Data were collected using field measurement and questionnaire
 Data were analyzed using descriptive statistics and aggregation method.

3.3 Objective 3: To assess Adaptation Strategies of
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Households to the Climate Hazards
 The major adaptation strategies identified in the study area
were:
 Change in agriculture system
 Relocation down slope
 Change in major livelihood source
 Relocation up slope
 Data on adaptation strategies to the climate hazards among
the 50 households were collected using questionnaire.
 Data were analyzed using tabulation

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4. Results
4.1 Major Climate Hazards
Major Climatic hazards based on frequency of occurrence
 In Bawaan, Erosion is the most frequent event, occurring
yearly, whereas landslide/mudslide, flooding and rock fall
occurred every 2-3 years. Drought had never been
experienced in the zone for the past 30 years (1981 – 2010).
 Erosion and flooding are most frequent events in Woikyor
occurring every year while landslide/mudslide and rock fall
occurred every 4-5 years. Drought had never been
experienced in the zone.
 In Womondo, flooding and erosion occurred yearly.
Landslide/mudslide and storms occurred every 2-3 years
while drought had not been experienced in the zone.

Major Climatic hazards based on the cost of
damage
 Landslide/mudslide is the major hazards in the three zones
with mean cost of damage exceeding 600, 000.00, followed
by flooding (Bawaan and Womondo) with 400, 000.00 –
600,000.00 and flooding, rock fall and erosion (Woikyor) with
cost of damage of 200, 000.00 – 400, 000. 00 per event.
 However, erosion has no cost of damage to households
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property in the three zones.

4.2 Variation in the level of vulnerability of
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households to climate hazards
 The result showed that Adaptive Capacity factors are the most
vulnerable factors, with mean vulnerability score (VS) of 6.2 (very
vulnerable), followed by Sensitivity factors with VS of
5.6(Significantly vulnerable) and least by Exposure factors with VS
of 4.9 (Vulnerable) respectively (Table 1).
 Health care centers, schools and roads have the highest
vulnerability score of 6.2 (very vulnerable) while household size has
the least vulnerability score of 4.2 (vulnerable)
 4 households (8%) have VS of above 6, 45 households (90%) have
VS of 5.0-5.9 and only 1 households (2%) have VS less than 5.0. The
mean VS of the 50 households is 5.3 (significantly vulnerable)
(Figure 3).
 Households vulnerability levels vary among the zones from
Woikyor (VS = 5.6), Womondo (VS = 5.4) and Bawaan (VS = 4.8)
respectively with regional mean VS of households of 5.3 (Table 2).

Table 1: Vulnerability Scores of the factors
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Figure 3: Variation in the level of households
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vulnerability

Table 2: Variation in the level of households
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vulnerability among the three zones

Causes and triggers of vulnerability in the study area
 Remoteness: Limit provision of infrastructure and services
 Inaccessibility: Limit movement of people, goods and services
 Population increase – Increase in population density from 78
persons/km2 in 1991 to 108 persons/km2 in 2006: This reduces area
for cultivation, increased pressure on available resources and the
fragile ecosystem
 Major sources of livelihoods - Farming, hunting, lumbering, fuel
wood harvesting: Livelihood sources that are highly vulnerable to
climate change impacts
 Unsustainable methods of resource exploitation - Slope wise
cultivation, no reserve forest: These aggravate the occurrence of
climate hazards events
 Territorial issues – The surrounding fertile plains and undulating
lands belong to other States and Cameroon Republic: These reduce
area for cultivation and increase the pressure of cultivated land.
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4.3 Adaptation Strategies
The result of adaptation strategies by households against climate
hazards events has shown that:
 A total of 22 households (44%) have identified change in
agricultural system as major adaptation strategy
 14 households (28%) accepted relocation down slope
 10 households (20%) indicated change in the major livelihood
source
 4 households (8%) opted for relocation upslope.

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5. Conclusion
The major conclusions of the study
 Flooding and erosion are the major climate hazard events
occurring every year
 Landslide/mudslide is the major climate event with mean cost
of damage exceeding 600, 000.00 naira
 Households in the study area are significantly vulnerable to
climatic hazards (mean VS = 5.3)
 Lack of basic infrastructure and services are the major drivers
of household’s vulnerability (mean VS = 6.2). This is attributed
to the remoteness and limited accessibility of the region.
 Majority of households prefer change in agricultural system
and relocation down slope as adaptation strategies to the
impacts of the climate hazards.

6. Added value for the Post 2015 Framework for
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Disaster Risk Reduction
 How did your work support the implementation of the Hyogo Framework for
Action:
 The work has focused on vulnerability of rural households to climate hazards
in remote mountainous region. The work has identified:
 Major drivers of vulnerability
 Major climate hazards events threatening livelihoods
 Adaptation strategies
 From your perspective what are the main gaps, needs and further steps to be
addressed in the Post 2015 Framework for Disaster Risk Reduction in:
 Research: 1.Improving understanding of the underlying causes and triggers of vulnerability to hazards
events 2. Linking livelihoods sources and indigenous sustainable practices.
 Education & Training: Capacity building on disaster preparedness, response and recovery practices for all
stakeholders in DRR and DRM: government, NGOs, corporate organisations and individuals.
 Implementation & Practice: Agencies charged with disaster risk management should be empowered,
and there should be an effective mechanism of coordinating disaster management among stakeholders.
 Policy: Policy dialogue should be geared towards effective designing, implementation and evaluation of
policies that would reduce exposure to hazard risks, increase resilience and quality of life, and also to bridge
the knowledge gap on DRR /DRM among stakeholders.

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References
Kaly, Ursula; Brigugio, Lino; McLeod, Helena; Schmall, Susana; Pratt, Craig; Pal,
Reginald (1999). Environmental Vulnerability Index (EVI) to summarize Natural
Environmental Vulnerability Profiles. SOPAC Technical Report number 275.
South Pacific Applied Geosciences Commission, Fiji.
Parry, M. L.; Canziani, O. F.; Palutikof, J. P. and Co-outhors (2007). Technical
Summary, Climate Change 2007. Impacts, Adaptation and Vulnerability.
Contribution of Working Group II to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change, Parry, M. L.; Canziani, O. F.;
Palutikof, J. P; van der Linden, P. J.; hanson, C. E., Eds., Cambridge University
Press, Cambridge, UK, 23 – 78.
Tyubee, Bernard Tarza; Gyuse, Timothy Terver; Basalirwa, Charles Peter Kagawa;
Majaliwa, Jackson Gilbert Majalolo (2010). An Assessment of the Level of
Vulnerability to Climate Risks in a Developing and Unplanned Tropical City
using the Environmental Vulnerability Index Model. Proceedings of the
International Disaster and Risk Conference on Risks, Disasters, Crisis and
Global Change: From Threats to Sustainable Opportunities, Davos, Switzerland,
759 – 762.
Villa, Fernando; McLead, Helena (2002). Environmental Vulnerability Indicators for
Environmental Planning and Decision-Making: Guidelines and Applications.
Environmental Management, 29 (3), 335 – 348.

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Assessing Vulnerability of Rural Households in Benue, Nigeria

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