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Received 2 December 2015
Accepted 12 April 2016
Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
Madhuri
Department of Humanities and Social Sciences, IIT Kharagpur
Kharagpur, West Bengal 721302, India
Email: madhuriptp09@gmail.com, madhuri@iitkgp.ac.in
H. R. Tewari
Department of Humanities and Social Sciences, IIT Kharagpur
Kharagpur, West Bengal 721302, India
Email: hrt@hss.iitkgp.ernet.in
P. K. Bhowmick
Rural Development Centre, IIT Kharagpur
Kharagpur, West Bengal 721302, India
Email: pradipb@hijli.iitkgp.ernet.in
Abstract
Flood is a perennial problem in the state of Bihar, India with devastating impact on the livelihood of
people. In spite of the government’s measures of flood mitigation, households continue to live with
sufferings on account of severe damage to their material and non-material assets. In this background, the
objectives of the study are (1) to assess the mediating role of risk perception, and flood preparedness
between flood experience and livelihood resilience; and, (2) to assess the mediating role of risk
perception, and flood preparedness between flood education and livelihood resilience. The primary data
were collected from 472 households by using multi-stage random sampling technique from seven blocks
in river basins of Ganga and Kosi in the district of Bhagalpur, Bihar. To analyze the data descriptive
statistics and structural equation modelling were used. However, risk perception is not found to mediate
between flood experiences, flood education, and livelihood resilience. Households adapt the strategy of
‘wait-watch-act’. Households do not perceive flood as a threat but they have learnt to ‘live with flood’ as
a ‘way of life’. The study recommends that the active involvement of the local people can be made
mandatory with due consideration to their indigenous knowledge, flood experience, and flood education
in order to make flood measures effective and successful.
Keywords: Flood, vulnerability, resilience, livelihood, household
1. Introduction
The inundation of a vast area of land and the
resultant loss of property, human lives, and
livelihood of households by recurring river flood is
the most challenging phenomenon in the agrarian
state of Bihar, India. The livelihood structure
created after years of hard work by households is
lost in no time, and its restoration takes longer than
the expected time depending on pace and
expediency of the relief assistance received from
the government as well as non-governmental
organizations. However, it is primarily the
resilience measures of the local community
(Saavedra and Budd, 2009) that matter the most
and hence, ought be placed centrally and enhanced
further (Srivastava and Laurian, 2006) in strategic
interventions to cope with and recover from the
shocks caused by flood (Bosher et al., 2009).
Flood, all its devastating effects, severely
jeopardizes the livelihood of people who live in
active zone of flooding. The livelihood structure
created after years of hard work is suddenly washed
away in no time. Households adapt strategies to
Journal of Risk Analysis and Crisis Response, Vol. 6, No. 2 (July 2016), 48-66
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
reconstruct their livelihood structure according to
their capability, adaptability, in view of their
experience and knowledge and with the support
they receive from their own community, the
government, and other external agencies including
NGOs. The government’s approach to livelihood
includes both structural as well as non-structural
measures. Included in the structural measures are
construction of dams, floodwall, and levee, while in
non-structural measures, regulations, zoning, and
protecting floodplains and wetlands are included
(Heidari, 2009). Nevertheless, these measures
neither succeed in checking flood damages, nor
address the related issues of water logging and
drainage congestion (Vari and Ferencz, 2006).
Failure of these measures brought in focus on
reducing vulnerability, and thereafter resilience
building of the affected households was accorded
prominence in flood mitigation measures (Hyogo
Framework for Action 2005-2015: Building the
Resilience of Nations and Communities to
Disasters). Timmerman (1981) in his paper
‘Vulnerability, Resilience, and the Collapse of
Societies’ introduced the term ‘Resilience’, i.e.,
capacity to absorb, resist and recover from disaster
(Klein et al., 2003). Tierney and Bruneau (2007)
stated that ‘resilience building’ is key to livelihood
because (1) it nurtures and enhances the ability of
social and physical systems to absorb, resist and
recover from disaster; (2) the pre and post measures
to mitigate disaster help in reducing harms it might
cause (Maguire and Hagan, 2007; Tierney and
Bruneau, 2007); (3)resilience building is an
important trait for both the social and physical
systems which support sustainability (Tierney and
Bruneau, 2007); (4)it increases the capability in
dealing with uncertainties and unexpected changes
(Berkes, 2007); (5)the measures of resilience
building are proactive and emphasize on the
collective efforts of the whole community; and (6)
it focuses on the areas through which the capability
of the community can be enhanced.
1.1. Flood Experience
Households carry experience of negative feelings
of flood, according to ‘inoculation hypothesis’
(Norris and Murrell, 1988; Slovic, 1987). The fear
of impending risk makes them careful in
confronting and overcoming flood (Chongfu,
2014). Attentiveness is more in the person with risk
experience than the one without it (Brilly and Polic,
2005). However, there is difference in risk
perception even in cases with similar experience of
flood (Ruin et al., 2007, Kaiser et al., 2004, Siegrist
et al., 2008). Weinstein (1989) described three
ways by which experience can affect risk
perception (1) societal attention, at the time of
flood occurrence; (2) victim-directed influence like
education and social norms; and, (3) intra-
individual response (cited from Howe, 2009). The
approach and outlook which develop after the
assessment of risk (Lazo et al., 2010) lead to
adaptation (Tompkins and Adger, 2004), of
protective actions (Weinstein, 1989) to resist future
flooding (Raaijmakers et al., 2008).
The impetus for adaptation of measures to cope
flood depends on the level of perceived risk of
households (Reid et al., 2007). If risk is not a fear,
there will be no effort for adaptation (Smit and
Wandel, 2006). It is flood experience and risk
perception, which enforce households to make
livelihood sustainable (Harvatt et al., 2011) in
perilous situation (Berkes, 2007). Thus, the
cognitive factors play significant role in livelihood
resilience (Grothmann and Reusswig, 2006). The
experience and consciousness of impending risk is
vital in adaptation of livelihood resilience
(Grothmann and Patt, 2005) by adapting different
activities to sustain and maintain livelihood (Ellis,
1998; Niehof, 2004). The diversification and
adaptation of livelihood strategies to refrain flood
is influenced by flood experience and risk
perception (Slovic et al., 2004). According to
protection motivation theory (PMT), which takes
into account the threat appraisal process and coping
appraisal process. Flood experience and response
help households residing in flood prone areas to
safeguard themselves through adaptation (Bubeck,
Botzen and Aerts, 2013). The threat appraisal
process is based on the apprehension of risk and its
repercussions, while coping appraisal process is
based on response efficacy (individual’s
expectancy that carrying out recommendation can
remove the threat), and self-efficacy (belief in
one’s ability to execute the recommend courses of
action successfully) to withstand, confront, and
resist flooding (Rogers,1983). The protection
motivation theory (PMT) has divided responses
into two categories, i.e., protective responses and
non-protective responses. Protective responses are
applied when threat appraisal and coping appraisal
are high to prevent monetary or physical damage.
On the other hand, in non-protective responses, the
threat appraisal is high and coping appraisal is low
as was found by Milne et al. (2000) in the meta-
analysis of PMT research, considering 27 studies
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
involving 7694 participants. High-risk perception
makes households to adapt coping responses,
which may be either protective or non-protective
response (Abraham et al., 1994). The model of
private proactive adaptation to climate change
(MPPACC) renamed threat appraisal to risk
appraisal and coping appraisal to adaptation
appraisal. However, adaptation appraisal, or
perceived adaptive capacity has not been included
in studies of risk perception after flood. The study
(Grothmann and Reusswig, 2006) which reveals
the relation between risk perception and adaptation
processes is based on a case study. There is a lack
of empirical study showing the relation between the
role of risk perception and adaptation of
households for livelihood resilience.
The acceptance and avoidance of risk is
voluntary to households (Raaijmakers et al., 2008).
The fear of being vulnerable and consciousness of
risk boost households’ resilience and actions to
cope with flood (Grothmann and Reusswig, 2006;
Ludy and Kondolf, 2012). However, studies differ
about the nature of relationship between flood
experience, risk perception, and mitigation method.
In the study of hurricane and storm risk by Peacock
et al. (2005), the experience and damage of flood
led to enhancement of risk perception resulting in
improved precautionary actions (Lindell and Perry,
2000) to mitigate flood risk (Mileti, 1999). The
threat of flood enhances adaptation of livelihood
strategies of households (Botha et al., 2011). Flood
experiences amplify risk perception and
consequently the behavior of recovery and
adaptation. These are important components of
livelihood resilience building and risk reduction
(Bubeck, Botzen and Aerts, 2012) after flood. The
households’ flood experience and perception of risk
influence their responses to control (Harvatt et al.,
2011) and initiate precautionary measures to
overcome flood (Harvatt et al., 2011) and make
themselves resilient (Fatti and Patel, 2013).
The way households perceive flood risk and
resulting damages determine households’ responses
to and management of flood risk (Harvatt et al.,
2011). Studies reveal that the personal experience
of destruction of livelihood increases the fear of
flood risk perception (Plapp and Werner, 2006;
Siegrist and Gutscher, 2006) and motivate
households to accelerate efforts for livelihood
resilience. On the other hand, there are studies
which do not find any influence of risk perception
on private mitigation strategies (Bubeck, Botzen
and Aerts, 2012; Nyakundi, Mogere, Mwanzo and
Yitambe, 2010) or decreases risk perception after
flood experience (Brilly and Polic, 2005; Botzen,
Aerts and van den Bergh, 2009). Therefore, the
differences in approaches of households with
regard to acceptance or ignorance of risk are
reflected in their livelihood resilience. Therefore,
the present study looks into risk perception as a
mediator between flood experience and livelihood
resilience.
The experience of flood is a key component in
flood risk management. It determines households’
responses to flood warnings and their efforts to
improve preparedness (Botzen, Aerts and van den
Bergh, 2009b; Aboagye, Dari and Koomson, 2013).
It always alerts households to remain prepared to
meet flood challenges (Few et al., 2005), and
enables them to adjust with and respond to the
flooding situation to minimize flood damages
(McCarthy et al., 2001). The self-protective
measures based on personal experience keep
households
ready for future ones (Weinstein, 1989).
Jackson (1981) found that experience of earthquake
influence households’ preventive measures.
Households use their experience in adapting
and coordinating flood mitigation measures like
laying sand bags in flood prone areas (Anderson,
1965), and how to participate in rescue activities
(Perry and Lindell, 1978). They themselves attempt
to save their lives and property (Keogh et al.,
2011). Knowledge and experience provide strategic
input to the affected households in their efforts to
mitigate flood effects (the theory of bounded
rationality), (Smith, 2001). It comes in handy to
households in designing suitable measures to
mitigate flood impacts (Tapsell, 2001) and also
broadens their perception and responses to an event
(Cutter,1993). Households develop ways to
minimize damages and devise livelihood strategies
in view of the nature and extent of damages, on the
one hand, and make optimal use of available
resources, on the other. They remain prepared to
handle the dreadful effects of flooding (Cash and
Moser, 2000). In course of time, it becomes their
strength to withstand the unstable situation (Robyn,
2012), according to the social constructionist
theory (Loseke, 1999). Households’ knowledge and
experience of flood find to be better equipped in
dealing with flooding (Brilly and Polic, 2005;
Wilson, 2012) and always keep them alert and
motivated with emergency preparedness to meet
flood challenges (Mileti,1999). The social
constructionists explain how households through
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
personal experience and interaction respond to
flood (Stabllings, 1995).
H1: Risk Perception would mediate between Flood
Experience and Livelihood Resilience.
Households’ experience of flood and worries to
it are reflected in their preparedness level
(Raaijmakers et al., 2008). Raaijmakers et al.,
(2008) observed that experience generates
awareness, understanding along with worry, which
decreased after long time. The community disaster
resilience framework emphasized that more the
households have resilience building capacity, less
would be their worries about repercussions of flood
(Raaijmakers et al., 2008) (Fig.1).
Fig. 1: Relationship between Flood characteristics (cited
from Raaijmakers, 2008)
Households’ repeated experience to flood
enriches their understanding of the nature of flood,
which is ultimately helping them in their livelihood
resilience (Grothmannw and Reusswig, 2006).
Furthermore, flood experience helps household in
overcoming flood impact (Pagneux et al., 2011) by
responding through preparedness measures which
facilitate their efforts in livelihood resilience (Paton
et al., 2006). Livelihood resilience measures do not
only mean to protect from flood but also taking
proactive measures to control flood (Longstaff,
2005). It enhances households’ efforts and abilities
(Folke et al., 2003) which assist them to adapt in
hazardous and uncertain conditions (Lengnick-Hall
and Beck, 2005). The anticipation of flood risk and
the destruction it causes, trouble the households,
who accordingly may remain prepared for future
event, so that the impacts can be reduced, and their
property and life can be saved (Howe, 2011).
There are a number of studies of impact of
disaster preparedness (Lindell and Perry, 2000) on
socio-demographic characteristic of the
households. On the contradiction, there are studies,
which show that there is no correlation between
flood experiences and flood preparedness measures
(Lin et al., 2008) despite being frequently affected
by flood. In a nationwide survey of earthquake risk
in Taiwan, Lin et al. (2008) did not find any
relation between experience, risk perception, and
households’ preparation. In survey of flood
preparedness in the Maribyrnong (Victoria)
(Victoria State Emergency Service (VICSES),
2008), and in 2005 survey of flood prone properties
in Maitland, NSW (New South Wales) (Hunter-
Central River Catchment Management Authority,
2005);shows that there is minimum or no
preparedness plan to combat flood (Gissing, Keys
and Opper, 2012). In another survey of landslide
victims in Taiwan, support shows that disaster
experience does not have any bearing on
preparedness (Ho et al., 2008). While on the other
hand, in the study by Slovic (2000) of hurricane
reveals that flood experience stimulates flood
preparedness. However, there is paucity of study, to
establish that flood preparedness stimulates
households’ livelihood resilience after flood.
H2: Flood experience would influence livelihood
resilience through flood preparedness.
Therefore, the first objective of the study is to
assess the mediating role of risk perception, flood
preparedness on flood experience, and livelihood
resilience.
1.2. Flood Education
Education, in general, broadens households’
understanding of the social and physical world
around them; flood education creates awareness
with regard to pros and cons of flooding in
particular. Flood education is defined as ‘any
learning process or activity that builds households
resilience to flooding’ (Dufty, 2008). In a critical
situation of flood and in recovery of livelihood, it
comes in handy to households’ rescue, improves
their capabilities, and knowledge to marshalling
political and economic advantages (Srinivas, 1996).
In flood management, awareness creation and
issuance of warning before hand play crucial role
(Elliott et al., 2003). Webber and Dufty (2008)
identified ‘preparedness conversion’, ‘mitigation
behavior’; ‘adaptive capability’, ‘community
competencies’ and, ‘post-flood learning’ as an
important function of disaster education. Though in
the guidelines for disaster management (Maria-
Sabo and Gavrila, 2011; UNISDR, 2009) it is
suggested that disaster education plays a vital role
in minimizing flood impact, but it is not included in
the government’s mitigation measures. Moreover,
the government’s awareness programs do not
properly emphasize on provisioning, protection,
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
and promotion of livelihood resilience. In
livelihood provisioning, food and health relief are
provided to households who are chronically
vulnerable, whereas livelihood protection
intervention includes income transfer,
infrastructure repair, rehabilitation, and
improvements, besides food or cash for work or
other means and compensation for assets such as
tools, boats and seeds. Livelihood promotion is a
set of development initiatives of households to
diversify their livelihood strategies; create
alternative income-generating activities; provide
financial services, such as loans and insurance and
strengthen markets (cited from The Household
Livelihood Security Concept, Retrieved from
ftp://ftp.fao.org/docrep/fao/X0051t /X0051t05.pdf).
In most of the studies, flood education had not been
looked as an important factor in constructing
livelihood resilience (Paton et al., 2006).
Paton et al. (2006) stated that resilience is a
measure of how well households and societies can
adapt to a changed reality and capitalize on new
possibilities offered. Flood education by making
forecasts, issuing early warnings, outlines recovery
procedures (Heinz, 2000) which help households to
resist and overcome flood impact. It further
generates awareness among them with regard to
adaptive measures (Botzen et al., 2009) for
livelihood restoration (Berkes, 2007). However, the
attitude and sensitivity of households towards risk
is important in adaption of strategies to diversify
income sources, and self-organize before, during
and after flood. The efforts and responses of
households to resist flood depend on their
consciousness (Fielding et al., 2005). However,
Palm (1981) found that disaster education does not
guarantee ‘risk avoidance behavior’, but is about
‘preventive measures’ to protect households
(Howe, 2009). Therefore, there is a need to create
consciousness, and competencies among
households for their livelihood resilience (Dufty,
2008). Studies show how consciousness is
significant in flood mitigation measures of
households (Pagneux et al., 2011; Burningham et
al., 2008; Miceli et al., 2008; Weinstein, 1989)
which may be enhanced through training to
improve their adjustment and adaption of
opportunities of income and potential precautionary
measures to enable them in restoring their
livelihood bases. Therefore, risk perception plays a
prominent role in creating awareness and
enhancing understanding about future occurrences
of flood (Raaijmakers et al., 2008). Thus, the study
tries to explore the mediation of risk perception
between flood education and livelihood resilience.
H3: Risk perception would mediate between
livelihood resilience and flood education.
Not only risk perceptions of households
motivate them towards resilience measures, but
flood preparedness also facilitates them in their
livelihood restoration. Furthermore, Dufty (2008)
emphasized that ‘Flood education can facilitate the
community to build its capability (networks,
leadership, and competencies) for preparedness,
response, and recovery and involve the community
in the planning, implementation and evaluation
phases’. Households with knowledge and being
aware of potential impact of hazards remain
prepared with contingency plans to meet challenges
arising out of flooding conditions (Bauman, 1983).
The protective measures give proper direction and
stimulate the process of resilience so that livelihood
can be regenerated without any heavy loss (Dufty,
2008). The attentiveness of potential hazard keep
household prepared with emergency plans to meet
the challenges arising from flood (Bauman, 1983).
Study show how disaster education increases
preparedness for hurricane (Faupel et al., 1992). On
the contrary, studies also show that in spite of
learning through flood education, it does not
stimulate households for livelihood resilience
(Boura, 1998; Paton et al., 2003).
Along with flood control and mitigation, the
pre-flood preparedness practices help in
restructuring livelihood activities is an important
concern, which needs attention. The improvement
in capabilities and diversification of livelihood help
households to bounce back to normal life (Walker
et al., 2004) without experiencing much destruction
in their day-to-day life. The awareness programs
mainly focuses on mitigation and coping measures
but there is dearth of study which aid in adaptation
and restoration of livelihood. The needs and
involvement of households in flood prone area may
be given proper consideration instead of fixing the
flood education process only to disseminate
knowledge so that it cannot be one-way approach
(O’Neill, 2004). Flood education is a most essential
factor in mitigation and management (Berkes and
Folke, 1998) of flood control (Berke, 1998; Burby
et al., 2000) but flood preparedness enhance
livelihood resilience is not elucidated (Burby,
1998; Burby et al., 2000). Hence, the study
articulates flood preparedness as an intervening
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
aspect between flood education and livelihood
resilience.
H4: Flood experience would influence livelihood
resilience through flood preparedness.
Hence, the second objective of the study is to
find out the mediating role of risk perception, and
flood preparedness between flood education and
livelihood resilience.
2. Study Area and Sampling Strategy
The study was conducted in the district of
Bhagalpur, Bihar. It has an area of 2570 sq km and
the rivers Ganga and Kosi traverse throughout the
district. The southern part of the district falls in the
Badua-Koa sub-basin of the river Ganga, and the
area in north of Ganga falls under the Baghmati-
Kosi sub-basin. These two sub-basins constitute the
Mid-Ganga basin that causes severe damage to life
and property. The district is principally drained by
the river Ganga, which enters the district at
Sultanganj. The northern boundary of the district is
marked by the river Kosi (Ghugri) heavily laden
with silt and sand. Geomorphologically, the district
forms a part of the Mid-Ganga foreland basin
(Ministry of Water Resources, 2009). Fig.2 shows
the flood inundated area of Bhagalpur district.
The study is based on the primary and
secondary data, and focus group discussion. The
primary data were collected by using multi-stage
random sampling technique. In the first stage, the
purposive sampling method was used to identify
the blocks, which have remained inundated in the
last 6 years during successive floods with the help
of data provided by the Bihar Disaster Management
Department, and in consultation with block
development officers (BDOs). Based on the data
obtained, out of 13 blocks, which are often affected
by flood, 7 blocks (Bihpur, Ismailpur, Gopalpur,
Rangra Chowk, Kharik, Narayanpur, and
Naugachhia) are selected for study. Table 1 shows
the number of village and size of population of the
blocks. The secondary data were collected from the
records of the district planning board, various
Depts. of the Governments of Bihar dealing and
several other documents and reports published from
time to time with regards to the issue of flood in the
state.
2.1. Focus Group Discussion
Focus group discussions were arranged in each
block of the area under investigation to ascertain
the views of the village people with regard to the
issue of livelihood resilience of the flood affected
households and other flood related issues. In the
Fig. 2: Administrative Map of Bhagalpur District, Bihar (Central ground water board, Ministry of Water resources, 2009).
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
Table 1: Number of Village and Size of Population of
the Blocks
Sl.
No
Blocks
Villages
Population
in the Block
1.
Ismailpur
6
6,277
2.
Gopalpur
11
76,420
3.
Rangra Chowk
9
72,780
4.
Kharik
19
102,825
5.
Bihpur
22
97,033
6.
Narayanpur
15
81,971
7.
Naugachia
12
122,809
Source: http://www.allaboutbihar.com
focus groups discussions, the issues of livelihood
resilience measures, households apply to cope with
flood were discussed. Groups were constituted in
all the blocks consisting of randomly selected ten
members in each group. In groups only those
members were included whose names did not
figure in the list of respondents for quantitative data
collection. Before the focus group discussions were
held in actual, the researcher met the village
persons and explained about the purpose of
discussion. They were requested to express their
opinion frankly without any fear or prejudice.
Initially, the village people were very reluctant and
were not agreeing for discussion due to their bitter
experience of the government’s approach to their
plight during flooding. It was a tough time for the
researcher to convince. It was then that village
people very hesitatingly agreed to take part in
discussion. After that, the place, time, and dates
were decided as suggested by village people.
Before, the actual discussions, the members were
requested to follow an order and express their
opinion without hesitation one by one. Tea with
biscuits was arranged for adult members and toffee
for young children. All the members were then
requested to ensure everyone’s participation.
Members were than frankly requested to share their
experience and opinion on the issue raised. The
questions raised for discussion were the following:
What do you do to cope with flood within the
household and in the farm?
How do you manage to reconstruct your
livelihood after flood, or how do you survive
in the flood prone area?
With regard to the first question, members
stated, “Since flood a recurring phenomenon in the
area, they have become habituated to live with it.”
They closely watch over flood progress and remain
ready to evacuate any time. They also identify
places where they can keep their belongings safely
when floodwater will cover the danger level. They
move to safer places with their belongings, which
they could carry with them. The heavy items of the
household are kept on the rooftop of the dwellings,
or tied with the roof. Temporary shelters are made
of plastic on the roadside, railway track, national
highway, and other high land areas. Food is rarely
cooked and water and other essentials of life are
arranged with great difficulty. The government
though provides food packets and other items but it
is not being made available to everyone. It is often
too short of households’ requirements. In order to
meet food requirement in emergency conditions,
they keep which are traditional fast food, items -
ready to eat during flood. Vegetables are grown in
house premises. As floodwater stays for three to
four months, households go for traditional farming.
One of the members mentioned that it is because of
her (Ganga river) displeasure that she brought silt
and sand to our land. Ganga river is worshipped as
holy mother. One of the respondents said, “We are
poor people and have no savings but we work as
daily wage laborer (roj kamne and khane wale log).
The damage and destruction caused by flood has
made our life hell. Flooding is a curse to them in
their opinion. It destroys all their resources support
base - resultantly many households migrate to other
places in search of livelihood. The government
officials in connivance with the political leaders
takes away for themselves all the relief assistance
government sends for distribution among flood
victims. It is an open loot of the government
resources, and no action is taken against erring
officials and persons in spite of several complaints.
2.2. Measures
The following section details the measurement
scales and the items (Table 2) used in measuring
the constructs. In-depth interviews were conducted
with key informants at three study sites.
Information from the qualitative research was used
for designing the structured interview schedule for
household survey. The final measurement scales
and design of the interview schedule on a five point
Likert scale. AMOS and SPSS software was used
to analyze the data.
3. Results and Analysis
3.1. Preliminary Data Analysis
The preliminary data analysis, reliability
estimation, confirmatory factor analysis through
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
structural equation modeling was used to
analyze and interpret the data. The normality
of the variables was tested by skewness and
kurtosis.
3.2. Reliability of the Measurement Scales
In accordance with the Chronbach alpha test, all the
constructs except flood preparedness obtained an
acceptable of a coefficient alpha above .70 (Table
3) indicating that the measurement scales were
reliable and appropriate for further data analysis.
3.3. Correlations between Variables
During the preliminary analysis of data, the mean
and standard deviation were obtained for each
variable. The correlation gave preliminary support
for the hypotheses of the study (Table 4). Flood
experience was negatively correlated and
insignificant to livelihood resilience (r = -.075,
p > .01). Flood education was also negatively
correlated to livelihood resilience but significant
(r = - .272, p < .01). However, risk perception was
positively correlated to livelihood resilience and
significant (r = .172, p < .01). The correlation
between flood preparedness and livelihood
resilience was significant but negative (r = -.413,
p < .01). The study also explored the relation
between flood experience and risk perception
(r = .585, p > .01) but the correlation between flood
Table 2: Measurement and Scales of Items.
Measured
Variable
No. of
Items
Measurement Scale
Source
Flood
Experience
11
1=not exposed to flood
5= very severely exposed
to flood
Tyler and Hoyt (2000); Norris and Murrell (1998); Susan
et al. (1996)
Flood
Education
6
1= strongly disagree
5= strongly agree
Dufty (2008); Mishra and Suar (2005)
Livelihood
Resilience
15
1=not at all
5=much more than usual
Household Questionnaire: Survey of Living Conditions,
Uttar Pradesh and Bihar ad
apted from World Bank (1997);
Hahn et al. (2009); DHS (2006); WHO/RBM (2003);
Fernando (2003); Patnaik and Narayanan (2010); Scoones
(1998); Little et al. (2001)
Risk
Perception
6 1=not at all
5=much more than usual
Slovic et al. (1980)
Flood
Preparedness
11
1=not at all
5= much more than usual
Mulilis et al. (1990); Brun et al. (1997); van der Veen and
Logtmeijer (2005)
Table 3: Summary of Measurement Reliability
Measured Variables No. of Items Items Remained Cronbach Alpha
1. Flood Experience 11 11 .87
2.
Flood Education
4
4
.71
3.
Livelihood Resilience
15
15
.78
4.
Risk Perception
6
6
.80
5.
Flood Preparedness
11
11
.69
Table 4: Correlation between the Variables
M
SD
FLEX
FLED
LVRS
RSPR
FLPP
FLEX
45.84
11.50
1
FLED
6.77
4.38
.306**
1
LVRS
50.21
.550
-.075
-.413**
1
RSPR
17.90
-623
.585**
.207**
-.011
1
FLPP
17.76
.147
.084
.526**
-.397**
0.17
1
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
experience and flood preparedness (r = .084,
p < .05) was also significant. The correlation
linking flood education and risk perception
(r = .207, p < .01) and flood preparedness
(r = .526, p < .01) was also significant.
4. Factor analysis
4.1. Exploratory Factor Analysis
Factor analysis is an interdependent technique,
which aims to determine the underlying structure
among variables (Hair et al., 1998). As livelihood
resilience scale was prepared by the researcher
through focus group discussion and interview with
informants, therefore, in order to ascertain how and
up to what extent the items of the scale were linked
to the construct in a different context, exploratory
factor analysis (EFA) method was applied on the
sample (N=472). The sample was subjected to
principal components analysis (PCA). Prior to
performing PCA the suitability of data for factor
analysis was assessed. Inspection of the correlation
matrix revealed the presence of correlation
coefficients of .3 and above. The Kaiser-Meyer-
Oklin value of the variable (.628) was exceeding
the recommended value of .6 (Kaiser, 1970) and
the Barlett’s Test of Sphericity (Bartlett,1954)
reached statistical significance (p<.01), supporting
the factorability of the correlation matrix (Hair et
al., 1998).
In EFA, first the unrotated factor matrix was
computed, containing the factor loading for
variable on factor. Factor loading is the correlation
of variables and the factor. The higher loading
makes the variable representative of the factor. The
factor-loading matrix was examined and significant
loading was identified. In the sample size of 472,
factor loading of .35 and higher was considered
significant for interpretive purpose. Variables
having communalities of greater than .50 were
retained in the analysis. The unrotated factor
solution did not provide adequate information of
variables under examination. In the unrotated factor
loading variables, having cross loading and those
with low significance was identified. Catell (1966)
scree test was also used to identify the optimum
number of factors that can be extracted. This was
further confirmed by the results of parallel analysis,
which showed components with eigen values
exceeding the corresponding criterion values for a
randomly generated data matrix of the same size.
To achieve simpler and theoretically more
meaningful factor solution, orthogonal approach
with varimax factor rotation method was used,
which attempted to minimize the number of
variables that had a high loading on factor. The
rotated solution revealed the presence of simple
structure (Thurstone, 1947) with factors showing a
number of strong loadings. The loadings were
improved for almost every item. The factor loading
of the items ranges between .543 to .657, the eigen
value was 3.976 and variance was 25.6. For further
analysis of the constructs, latent variable structural
equation modeling method was used.
4.2. Latent Variable Structural Equation
Modeling (LVSEM)
Latent variable structural equation modeling
(LVSEM) tests the sequential relationship between
a series of independent and dependent variables. It
assists in specifying measurement model as well as
structural models
There are two components of SEM,
measurement model and structural model. The
measurement model was evaluated by using
Confirmatory Factor Analysis (CFA). The
measurement model specifies the posited
relationships of the observed indicators to the latent
construct. Therefore, before testing the overall
measurement model, each construct in the model
was evaluated and analyzed separately by
respecification of the model. The model
respecification procedure was used to identify the
source of misfit and to generate a model that
achieves better fit to the data. The measurement
model was modified by examining the standardized
residuals, modification indices, and the
standardized loading estimates (Hair et al., 2006).
Each of the measures was examined together with
the model fit indices to ascertain if respecification
was needed. The model fit was examined using
multiple indices such as χ² and the χ²/df, GFI, CFI,
TLI, RMSEA. After the modification of the fit
indices, the final CFA model was improved. The
revised measurement model fit the data well.
Further, when each construct had shown an
acceptable fit to the model, then all constructs were
evaluated together (Table 5).
Hypothesis (H1): Risk Perception would mediate
between Flood Experience and Livelihood
Resilience.
The present study also examined (H1) the
relationship between flood experience and
livelihood resilience mediated by risk perception.
At first the direct relationship was determined
(Table 6), i.e., (a) regression was run to predict
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
livelihood resilience from flood experience
(β = .37, p <.01, c.r.= 3.2) was significant and
supported; (b) the regression coefficient for the
prediction of risk perception from flood experience
was negative and statistically insignificant
(β1 = -.90, p > .05, c.r = -1.79); (c) next, regression
was performed to predict the effect of risk
perception on livelihood resilience which was
significant and positive (β3 = .174, p <. 01,
c.r. = 4.0); and, (d) with risk perception in
equation, the regression coefficient was not smaller
than the β1 (β4 = .082, p > .05, c.r = 1.73), further
the β1 was not significant; risk perception had no
mediation in the relationship between flood
experience and livelihood resilience. Table 7
reveals the indirect effect was not supporting the
mediation. Therefore, H1 was refuted.
Hypothesis (H2): Flood experience would
influence livelihood resilience through flood
preparedness.
Next, the hypothesis (H2) of the study is when
mediator flood preparedness was taken into account
the relationship between flood experience and
livelihood resilience would be more powerful.
Before considering the position of flood
preparedness as mediator in the analysis, at first the
bivariate association between flood experience and
livelihood resilience was established (Table 8)
(a) Flood experience significantly account for
variations in livelihood resilience (β = .37, p < .01
,c.r. = 3.2); (b) the relationship between flood
experience and flood preparedness was significant
(β2 = .158, p < .01, c.r. = 4.4);(c)flood preparedness
significantly account for variation in livelihood
resilience (β3 = .164,p <.01, c.r = 2.7); and,(d)
with flood preparedness in equation, the regression
coefficient of flood experience to livelihood
resilience was smaller than the β1 (β4 = .037, p <
.05, c.r. = 2.3), further the β1 was still significant,
flood preparedness had a partial mediating effect
on the relationship between flood experience and
livelihood resilience. Table 9 shows the direct,
indirect, and total effect of mediation. Therefore,
H2 was supported. Figure 3 shows the Hypothesis
H1 and H2.
Table 5: Summary of CFA Result and Model fit Indices (N=472)
Construct
CFA Items
Reliability
4. Flood Experience
6
.82
χ² = 42.3; χ²/df = 3.25; p = .000; RMSEA = .06; GFI = .96; TLI = .96; CFI =.98
5. Flood Education
3
.69
χ² = 48.8 ; χ²/df = 2.9; P = .000; RMSEA = .00; GFI = .99; TLI = 1.00; CFI = 1.00
6. Livelihood Resilience
6
.70
χ² = 18.6; χ²/df = 2.3; p = .000; RMSEA = .05; GFI = .98; TLI = .97; CFI = .98
7. Risk Perception
5
.78
χ² = 17.14; χ²/df = 3.4; p = .004; RMSEA = .07; GFI = .98; TLI = .98; CFI = .99
8. Flood Preparedness
5
.70
χ² = 21.77; χ²/df = 2.7; p = .000; RMSEA = .06; GFI = .98; TLI = .90; CFI = .94
Table 6: Hypothesis Testing of Risk Perception as Mediator between Flood Experience and
Livelihood Resilience
Hypothesized path
Direction
Beta estimate
C.R/ t value
SE
Decision
LVRS ← FLEX
FLPP ← FLEX
LVRS ← FLPP
+
+
+
.037*
.158*
.164*
3.28
4.43
2.74
.037
.058
.060
Supported
Supported
Supported
Note: β = regression weight; *p<.05, **p<.01 (2-tailed)
Table 7: Direct, Indirect, and Total Effects of Risk Perception as Mediator
between Flood Experience and Livelihood Resilience
Variable
Variable
RSPR
LVRS
Direct
Indirect
Total
Direct
Indirect
Total
FLEX
-.90**
.00
-.90**
.37**
.82
.119**
RSPR
.00
.00
.00
.17
.00
-.09
Note: path estimates were reported; *p<.05, **p<.01 (two-tailed)
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
Hypothesis (H3): Risk perception would mediate
between livelihood resilience and flood education.
The study also looked that (H3) risk perception
would mediate between livelihood resilience and
flood education. Table 10 shows (a) flood
education was significantly accounted for
variations in livelihood resilience (β1 = .224, p
< .01, c.r. = 2.3); (b) the relationship between flood
education and risk perception was significant (β2
= .122, p < .05, c.r. = 3.4); (c) risk perception was
significantly accounted for variation in livelihood
resilience (β3 = .174, p < .01, c.r. = 4.0); and,(d)
with risk perception in equation, the regression
coefficient was significant but negative β2 (β3 = -
.296, p < .05, c.r. = -3.1). Hence, there was no
mediation of risk perception between flood
education and livelihood resilience. Table 11 shows
that the direct effect with mediator was negative.
Therefore, H3 was refuted.
Hypothesis (H4): Flood Education would influence
livelihood resilience through flood preparedness.
The study also explored the relationship (H4)
Table 8: Hypothesis Testing of Flood Preparedness as Mediator between Flood
Experience and Livelihood Resilience
Hypothesized path
Direction
Beta estimate
C.R/ t value
SE
Decision
LVRS ← FLEX
FLPP ← FLEX
LVRS
←
FLPP
+
+
+
.037*
.158*
.164*
3.28
4.43
2.74
.037
.058
.060
Supported
Supported
Supported
Table 9: Direct, Indirect, and Total Effects Flood Preparedness as
Mediator between Flood Experience and Livelihood Resilience
Variable
Variable
FLPP
LVRS
Direct
Indirect
Total
Direct
Indirect
Total
FLEX
.37**
.00
.37**
.37**
.37**
.74**
FLPP
.00
.00
.00
.16**
.00
.16**
Note: path estimates were reported; *p<.05, **p<.01 (two-tailed)
Note. Dotted lines show indirect effects **p < .01, *p<.05
Fig 3: Risk perception and Flood preparedness as a mediator between Flood experience
and Livelihood Resilience
Table 10: Hypothesis Testing of Risk Perception as Mediator between Flood Education
and Livelihood Resilience
Hypothesized path
Direction
Beta estimate
C.R/ t value
SE
Decision
LVRS ← FLED
RSPR ← FLED
LVRS ← RSPR
+
+
+
.224 **
.122*
.174 **
2.35
3.45
4.08
.095
.042
.043
Supported
Refuted
Supported
Note: β = regression weight; *p<.05, **p<.01 (2-tailed)
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
between flood education and livelihood resilience.
Table 12 reveals (a) flood education significantly
accounted for variations in livelihood resilience (β1
= .224, p< .01, c.r. = 2.3); (b) the relationship
between flood education and flood preparedness
was significant (β2 = .472, p < .05, c.r. = 4.02); (c)
flood preparedness was significantly accounted for
variation in livelihood resilience (β3 = .178, p
< .05, c.r. = 2.8) and, (d) with risk perception in
equation, the regression coefficient between flood
education and livelihood resilience was smaller
than the β1 (β4 = .164, p < .01, c.r. = 2.7); but the
β4 was still significant, flood preparedness has a
partial mediating effect on the relationship between
flood education and livelihood resilience. Table 13
shows the direct, indirect and total effect of
mediation analysis, which was significant and
supported. Therefore, H4 was supported.
The fit measures of the direct and indirect path
(including mediators) model indicate that chi
square of all the models were highly significant
(p < .001). As chi-square was sensitive to sample
size, so chi-square for degree of freedom (χ²/df)
was estimated. The result shows that the relative
chi-square was not below the required limit of 3
(Kline, 1998). GFI, CFI, NFI was close to .90
which reveals the good fit of the model. The
parsimonious (PGFI, PCFI, PNFI) measures were
acceptable in both the models. However, it was
slightly low in the direct model because the
mediation was absent in that model (Table 14).
RMSEA show the approximation of the observed
model to the true model, which was acceptable in
this model. However, the indirect model was better
than the direct model because it included all
possible paths.
Therefore, the result of the hypothesized
structural model reveals that the initial model did
not fit the data well, and so, it was not acceptable
(χ² = 380.6, χ²/df = 2.45, p = .01, GFI = .90;
TLI = .91, CFI = .92, RMSEA = .06). The results
indicate that risk perception does not mediate
between livelihood resilience and flood experience
and flood education. The two hypothesized paths
do not show any significant relationship between
exogenous and endogenous variable. Therefore,
these hypotheses paths were removed because the
construct does not have any significant affect on
livelihood resilience (Fig. 3) Revised Model with
Standardized and Unstandardized Path
Table 12:
Hypothesis Testing of Flood education would influence livelihood resilience
through flood preparedness.
Hypothesized path
Direction
Beta estimate
C.R/ t value
SE
Decision
LVRS ← FLED
FLPP ← FLED
LVRS ← FLPP
+
+
+
.224 **
.472*
.178*
2.35
4.02
2.88
.095
.117
.178
Supported
Supported
Supported
Note: β = regression weight; *p<.05, **p<.01 (2-tailed)
Table13: Direct, Indirect, and Total Effects Flood Preparedness as
Mediator between Flood Education and Livelihood Resilience
Variable
Variable
FLPP
LVRS
Direct
Indirect
Total
Direct
Indirect
Total
FLED
.22*
.00
.15
.22**
.16**
.48**
FLPP
.00
.00
.00
.17*
.00
.17*
Note: path estimates were reported; *p<.05, **p<.01 (two-tailed)
Table 14: Fit Measures of Two Models Dealing with Mediation
χ2/df
p
GFI
TLI
CFI
PGFI
PCFI
PNFI
RMSEA
Direct model
2.10
.001
.91
.91
.92
.60
.68
.66
.05
Indirect model
2.45
.001
.90
.91
.92
.62
.69
.67
.06
Table 11: Direct, Indirect, and Total Effects Risk Perception as
Mediator between Flood Education and Livelihood Resilience
Variable
Variable
RSPR
LVRS
Direct
Indirect
Total
Direct
Indirect
Total
FLED .22** .00 .22** .22** .29** .51**
RSPR
.00
.00
.00
.17**
.00
.17**
Note: path estimates were reported; *p<.05, **p<.01 (two-tailed)
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
Coefficient). Consequently, a more parsimonious
model (Table 15) was made after deleting the non-
significant path from the initial model (χ² = 326.8,
χ²/df = 2.04, p = .00, GFI = .94; TLI=.96, CFI=.98,
RMSEA= .06). Figure 4 shows the Hypothesis H3
and H4.
5. Discussions
Objective1: To assess the mediating role of risk
perception, flood preparedness on flood experience,
and livelihood resilience
Risk perception is not found to mediate between
flood experience and livelihood resilience as the
findings of the study reveal. Although, flood
experience plays significant role in both flood
protective behavior and flood risk perception of
households, their perceived flood probabilities and
perceived flood consequences do not intervene in
livelihood resilience. This is consistent with the
heuristic theory, which emphasizes that households
do not unreasonably worry about flood impact
because of their flood experience (Grothmann and
Reusswig, 2006). Rather, learning from repeated
exposure to flood comes in handy to households in
their efforts to skillfully arrange livelihood, as it
provides them added advantage when it is most
needed. The learning from flood experience
enables households to resist, recover, and bounce
back to normal livelihood after flood. They adjust
and learn to live in hazardous condition on the
basis of their previous flood experience which
saves them from much of their likely losses. Flood
experience is further found to provide stability and
enhances households’ capability to skillfully and
effectively handle flood challenges (Fig 5 and Fig.
6).
Fig. 5: Households Shifting their Belonging to a Safer
Place
Fig. 6: Households Tie their Belongings to the Rooftop
of the House
Table 15: Goodness of Fit Results for Structural Model
Measurement Model
Goodness-of-fit Indices
χ²
χ²/df
p
GFI
TLI
CFI
RMSEA
Initial Model 380.6 2.45 .001 .90 .91 .92 .06
Final Model 326.8 2.04 .000 .94 .96 .98 .07
Note. Dotted lines show indirect effects **p < .01, *p<.05
Fig 4: Risk perception and Flood preparedness as a mediator between Flood
education and Livelihood Resilience
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The study is consistent with the previous
literature (Bubeck, Botzen and Aerts, 2012), which
found weak relationship between flood risk
perceptions and mitigation measures. Households’
views and perceptions about flood changes in
course of time because of their repeated flood
experience. As a result, they no more remain
fearful of flood impacts. Their flood experience and
capabilities instill further confidence in them with
regard to livelihood resilience, diversification of
livelihood, and income generating activities. The
protection motivation theory (threat coping and
threat appraisal behavior) does not hold relevance
and is not imperative in livelihood resilience. The
study is contrary to the study by Wachinger and
Renn (2010) which found that risk perceptions
influence vulnerability of the households. The
study also differs with the study of Bradford et al.
(2012) which proposed to develop a model of
social resilience based on risk perception.
However, the study confirms the assumption that
risk perception largely depends on recency
(Hertwig et al., 2004), frequency, and intensity of
households’ flood experience, but does not play
role in adaptation of resilience measures.
Flood preparedness partially mediates between
flood experience and livelihood resilience. The
study is in contrast to the findings of the study
which had found high level of emergency
preparedness (Lindell and Prater, 2000), but is
consistent with the study which found low and
minimal preparedness (Jackson, 1981; Turner et al.,
1986; Miceli et al., 2008). The study is further
consistent with the study of residents in a flood-
prone area of Italy, which showed low level of
individual-level domestic protection (De Marchi et
al., 2007). Hung-Chih (2009) found a similar
pattern among Taiwanese participants. Flood
experience is also found to stimulate households in
flood preparedness based on their understanding
and familiarity with flood devastation as was found
in previous studies (Basolo et al., 2009; Harvatt,
Petts and Chilvers, 2010; Kirschenbaum, 2002).
The result is consistent with the study of Nyakundi,
Mogere, Mwanzo, and Yitambe (2010) which
concluded that households’ indigenous knowledge
play crucial role in livelihood resilience. The
resilience measures of flood control are a by-
product, or an outcome of households’ direct
experience of flooding and reactive mechanism to
reinstate livelihood to its normal condition.
Households do not evacuate or shift their
belongings and livestock to safer places unless all
options have not been ruled out, and households do
not find themselves placed in much deep water.
Absence of boat, dinghy and other means of
transportation complicate the process of
households’ evacuation. As a result, household
follow their own ways and shift their belongings to
the rooftop of the house. Dwellings of households
in active flood zones are generally built on silt or
elevated ground.
Objective 2: To assess the mediating role of risk
perception, and flood preparedness between flood
education and livelihood resilience.
The results of the study do not find mediation
by risk perception between flood education and
livelihood resilience as because households, in
course of time, adjust with flood, live with
uncertainty, and accordingly adapt resilience
measures. Though there is no formal flood
education programs in the study areas, households
always learn from the experience of the senior
persons of the community about the pros and cons
of flood, and what measures may be more effective
in different flooding situations. This facilitates
households in making better use of the available
resources to recreate livelihood. This, possibly,
may be for the reason that households are neither
warned, nor informed beforehand about the
probable occurrences of flood and its impact on
their livelihood. Besides, the government’s
awareness programs are often superficial and
perfunctory, do not lay focus on households’
attitudinal change. It does neither focus on which
adaptive measures should they follow, nor which
new opportunities are available to them to earn
their livelihood. It only focuses on preventive
measures, which though provide temporary relief to
households, but does not offer any effective or
lasting solution to livelihood resilience of
households to reduce vulnerability. The
government sponsored flood mitigation programs
do not focus further on livelihood promotion.
The result of the study shows that flood
preparedness mediates between flood education
and livelihood resilience. Though, there is no
formal flood education in the blocks of the study
area, households informally learn from the
experience of elders and senior members of the
community about what steps should be taken in
what kind of flood situation, how to mobilize
resources, what measures should be adapted to
protect life and property of households effectively,
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
what preparatory measures should be taken to meet
flood challenges, and how to approach political
leadership and other external agencies to support
livelihood resilience of the affected households etc.
All potential problems are discussed in informal
village gatherings and village chitchat sessions at
length along with their possible solutions to
safeguard the interests of the households in the
flooding situations. In fact, households realize the
significant role of elders and senior members of the
community in creating awareness, dissemination of
information, and flood preparatory mechanism
more than what may be achieved through formal
system of education (Fig. 7).
Fig. 7: Households take their livestocks to safer place(s)
However, households do acknowledge the
importance of flood education with regard to
various aspects of flooding. i.e., knowledge about
potential impact of flooding, training to effectively
handle flood situation, viability of various
strategies to meet flood challenges and how to
make preparation, and how to make optimal use of
available resources in the given situation of
flooding etc. In the opinion of majority of the
households, though education about flood does
exist informally, formal flood education may
further add, supplement, provide or train ‘flood
folks’ 1 about how to behave them in a flooding
situation, and how to act effectively to meet flood
challenges. In the community, threadbare
discussions take place with regard to pros and cons
of various strategies of livelihood resilience and
various strategic measures the community should
initiate to safeguard their interest and contain flood
fury. Households’ live with the flood ‘as a way of
life’.
Resources are pulled, specific steps of action
are chalked out, round the clock monitoring of
floodwater is arranged, responsibilities are
1 It refers to a grou p of households who are aff ected by flood.
distributed and all households are asked to standby
if situations so warrant. The community is found to
remain alert to collectively act to meet any flood
eventuality. Throughout the entire flooding period,
the community remains together and jointly
initiates actions to support each other at the time of
flooding. Loud speakers are used to update
households, and petromax and other lighting
arrangements are made to keep close watch over
flood development.
Households flood preparedness includes storage
of relief materials, storage of seeds, monitoring of
floodwater, and exchange of information about safe
places of shelter. Flood preparedness may further
be improved and flood impacts be lessened by
making arrangements for formal flood education,
by organizing awareness programs, and by issuing
early warning to households to remain prepared to
meet any flood eventualities. The study envisages
the necessity for accurate flood education program
to create awareness in households in respect to
flood and its accompanying problems as it may
install confidence and create hope in households in
the situation of despair (Berke, 1998; Burby et al.,
2000; Botzen, 2009).
In the opinion of households, since the
government relief assistance always comes late it
may be taken care of by arranging a camp office at
the site of flooding. The camp office may be
interested with the responsibility to maintain liaison
with the flood headquarters of the government to
continuously update the government about the
flood progress. A roster of households may be
maintained closely monitor and watch the flood
movement for onward transmission to the flood
headquarters.
6. Conclusions
Flood experience of households and their
knowledge work as strategic inputs in their
livelihood resilience. Flood experience is acquired
from their frequent exposure is far more the most
effective and powerful weapon, which households
use advantageously to fight against flood vagaries.
It is used as a strategic resource input by them in
their livelihood resilience. It is a process of
continuous learning, which creates confidence in
households and enables them to adapt measures to
meet any flood eventuality. As a result, they do not
perceive flood as a threat because of their
experience and knowledge and their confidence in
finding ways to overcome it. Households adapt the
strategy of ‘watch and act’ and accordingly remain
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Madhuri et al. / Living with Flood: A Livelihood Resilience Approach of Rural People in Bihar, India
prepared with contingency plans to overcome flood
impacts.
Although, flood education is not found to exist
formally, younger persons informally learn from
the experience of senior persons about the
preventive measures to be adapted and likely to be
effective in coping with flood. Wide discussion
takes place among the households and in the
community with regard to proactive measures when
flood is visualized and considered inevitable.
Livelihood resilience depends on the ingenuity
of the households, the support they receive from
the community and the government, and how
optimally do they use their flood experience and
knowledge. In the flooding situation, the
community acts together as a cohesive unit, for all
being risked to the same problem. The long
experience of flood enables affected households’
learning and adaptation of suitable ways and means
to livelihood resilience, which may further help
policy makers in devising effective strategy.
Therefore, there is a need to take benefit of the
strategic value of people’s indigenous knowledge
and flood experience in livelihood resilience, as it
does not depend only on distribution of relief
materials, but more so depends on people’s access
to resources and their attitude and aspirations for
livelihood resilience. The government focuses on
preparedness activities but does not promote
livelihood diversification strategy, which may help
households in generating income and different
livelihood activities. Moreover, lack of formal
flood education programs does not pose any
problem in households’ awareness as it takes place
in different informal meetings of the households. In
order to meet flood challenges, involvement of all
the stakeholders need to be duly considered at all
levels of flood operations. People’s experience and
knowledge to flood which come in handy and guide
them at each step in their efforts to reestablish
livelihood may be advantageously utilized in
strategic intervention by the government. It helps
households in their strategies, according to
situational requirement.
7. Limitations
The study though shows risk perception as
mediator, but risk perception changes over time and
cognitive emotions may enhance or lessen after
certain time and thus, may influence livelihood
resilience. This may be taken care-off by making
pre and post studies, but this could not be done in
this present study. An effective model by involving
different stakeholders and by incorporating local
issues including households’ strategies may be
prepared for different phases of livelihood
resilience.
Acknowledgement
We are very grateful to IIT Kharagpur for
providing fund to carry out the research.
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