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COMMUNITY TRADITIONAL KNOWLEDGE, PERCEPTIONS
AND RESPONSE TO FLOOD RISKS IN NYANDO BASIN,
WESTERN KENYA
NYAKUNDI HELLEN MWANGO (BA)
REG NO: I57/5672/03
A THESIS SUBMITED IN PARTIAL FULFILMENT FOR THE
AWARD OF THE DEGREE OF MASTER OF PUBLIC HEALTH IN
THE SCHOOL OF HEALTH SCIENCES, KENYATTA UNIVERSITY
JUNE 2010
ii
Declaration
This thesis is my original work and has not been presented for a degree in any other
university or any other award.
-----------------------------------Nyakundi Hellen Mwango
(I57/5672/03)
----------------------Date
We confirm that the work reported in this thesis was carried out by the candidate under
our supervision.
-------------------------------------Dr. Isaac Mwanzo
Department of Public Health,
School of Health Sciences‟
Kenyatta University
---------------------Date
-------------------------------Dr. Andre Yitambe
Department of Public Health,
School of Health Sciences,
Kenyatta University
---------------------Date
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Dedication
To my parents, Mrs. Eunice Nyakundi and Mr. Alphayo Nyakundi. This degree reflects
their hard work just as much as it does mine. Without them I would not have been able to
achieve this goal-thank you.
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Acknowledgements
I would like to thank several people who have contributed to the successful completion of
this work:
First and foremost, grateful thanks are extended to my university supervisors, Dr Isaac
Mwanzo, Dr Andre Yitambe and Mr. Steven Mogere, who guided me throughout the
study. The criticism, comments and advice from other members of staff in the department
and classmates at different stages of the thesis are also highly appreciated.
Gratitude goes to the field assistants and all who took part in the field work. I would also
like to show appreciation to the residents of Nyando District for their hospitality and
willingness to participate in the study.
Special thanks to my family: my mum and dad for providing me with everything I needed
to maintain my direction and stay focused; my siblings: Rose, Ben, William and Ruth, for
their encouragement; and my daughter Chudia, for being a constant source of joy and
inspiration.
This investigation received further financial support from the ProVention Consortium and
I am very grateful for the scholarship. Above all, thanks to God for His grace, strength
and sustenance.
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Table of contents
Declaration ......................................................................................................................ii
Dedication ..................................................................................................................... iii
Acknowledgements ........................................................................................................ iv
Table of contents ............................................................................................................. v
List of tables .................................................................................................................viii
List of figures ................................................................................................................. ix
List of pictures ................................................................................................................ x
Abbreviations and acronyms .......................................................................................... xi
Abstract ......................................................................................................................... xii
CHAPTER 1: INTRODUCTION .................................................................................... 1
1.1 Background information ............................................................................................ 1
1.2 The problem statement .............................................................................................. 4
1.3 Purpose of the study .................................................................................................. 5
1.4 Study objectives ........................................................................................................ 6
1.5 The Study was guided by the following research questions: ....................................... 7
1.6 Null Hypothesis ......................................................................................................... 7
1.7 Significance of the study (rationale) ........................................................................... 7
1.8 Scope of study and limitations ................................................................................... 7
1.9 Assumptions .............................................................................................................. 8
1.10 Conceptual framework ............................................................................................. 8
1.11 Theoretical framework ........................................................................................... 10
1.12 Operational definition of terms .............................................................................. 13
CHAPTER II: LITERATURE REVIEW ....................................................................... 16
2.1 Introduction ............................................................................................................. 16
2.2 Nature of flood risks ................................................................................................ 16
2.3 Perception of flood risks to public health ................................................................. 18
2.4 Vulnerability to Flood Risks .................................................................................... 20
2.5 Behavioural response to flood risks ......................................................................... 21
2.5.1 Coping mechanism ............................................................................................... 22
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2.5.2 Traditional knowledge on flood forecasting and warning ...................................... 23
2.6 Attitude towards external support ............................................................................ 24
CHAPTER III: METHODOLOGY .............................................................................. 26
3.1 Introduction ............................................................................................................. 26
3.2 Location of study ..................................................................................................... 26
3.3 Research Design ...................................................................................................... 27
3.5 Sampling techniques and sample size ...................................................................... 28
3.5.1 Sampling technique .............................................................................................. 28
3.5.2 Sample size determination .................................................................................... 30
3.6 Study Population ..................................................................................................... 32
3.7 Construction of research instruments ....................................................................... 33
3.7.1 Household questionnaire ....................................................................................... 33
3.7.2 Interview guide for key informants ....................................................................... 34
3.7.3 Focus group discussion ......................................................................................... 34
3.8 Pilot study ............................................................................................................... 34
3.8.1 Validity of instruments ......................................................................................... 35
3.8.2 Reliability of instruments ..................................................................................... 35
3.9 Data Collection Techniques ..................................................................................... 36
3.10 Ethical considerations ............................................................................................ 37
3.11 Data Analysis Methods .......................................................................................... 38
CHAPTER IV: RESULTS AND DISCUSSIONS ......................................................... 39
4.1 Results..................................................................................................................... 39
4.1.1 Introduction .......................................................................................................... 39
4.1.2 Socio demographic characteristics, education and socio-economic status .............. 39
4.1.3 Traditional knowledge on flood forecasting .......................................................... 46
4.1.4 Existing perceived risk of flooding to public health............................................... 52
4.1.5 Behavior associated with flood risk management in Nyando District .................... 56
4.1.6 External support.................................................................................................... 71
4.2 Discussion ............................................................................................................... 76
4.2.1 Socio-demographic information ............................................................................ 76
4.2.2 Traditional knowledge on flood forecasting .......................................................... 78
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4.2.3 Perception of flood risks to public health .............................................................. 80
4.2.4 Behavior associated with flood management ......................................................... 84
CHAPTER V: SUMMARY, CONCLUSION AND RECOMMENDATIONS .............. 92
5.1 Major findings of the study ...................................................................................... 92
5.1.1 Demographic and socio-economic characteristics ................................................. 92
5.1.2 Traditional knowledge on flood forecasting .......................................................... 92
5.1.3 Existing perceptions of impact and management of flood risks ............................. 92
5.1.4 Response behavior towards health risks ................................................................ 93
5.1.5 Attitude towards external support ......................................................................... 94
5.2 Conclusion .............................................................................................................. 94
5.3 Recommendations for implementation ..................................................................... 96
5.5 Recommendations for further research: .................................................................... 98
REFERENCES.............................................................................................................. 99
APPENDIX I: MAP .................................................................................................... 110
APPENDIX 11: HOUSEHOLD QUESTIONNAIRE .................................................. 111
APPENDIX II: FOCUS GROUP DISCUSSION GUIDE ........................................... 130
APPENDIX III: INTERVIEW SCHEDULE FOR KEY INFORMANTS .................... 133
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List of tables
Table 2.1: Types of floods and their characteristic impacts…………………………….1
Table 3.1: Selection of study area using the Nyando District administrative ladder……30
Table 3.2: Summary of results of Stratified Proportional Sample……………...……….31
Table 4.1: Age, gender and marital status of respondents………………………………40
Table 4.2: Socio-economic characteristics of respondent in the study area…………….42
Table 4.3: Main source of water, wall structure and roof types of households…………45
Table 4.4: Length of residency of study population in Nyando District………………..46
Table 4.5: Local knowledge of flood forecasting and warning…………………………56
Table 4.6: Summary of traditional early warning flood indicators……………………..50
Table 4.7: Use of traditional knowledge in the study area………………………….…..51
Table 4.8: Perceived presence of health hazards as a result of flooding………….….....53
Table 4.9: Survival strategies to deal with damage to shelter adopted by residents
before, during and after the flood season……………………...……………..57
Table 4.10: Reasons for staying in a flood prone area………….………………………59
Table 4.11: Survival strategies to deal with shortage of food in the study area……...…60
Table 4.12: Relationship between shortage of water and main water source…………...61
Table 4.13: Survival strategies to deal with shortage of water………………………… 62
Table 4.14: Summary of diseases suffered by respondents during the flood season……64
Table 4.15: Summary of deaths related to flooding……………………………………..66
Table 4.16: Coping strategies used to deal with loss of crop in study area……………..68
Table 4.17: Coping strategies to handle livestock during the flood season….………….69
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List of figures
Figure 2.1: A conceptual model adapted and modified from Handmer
and Penning-Roswell (1990) that elicits perception and
the behavioural response to flood hazards………...………………………..9
Figure 4.1: A comparison of education levels between male and female respondents....41
Figure 4.2: A comparison of income levels of the male and female respondents…...….44
Figure 4.3: Sources of traditional flood information in the community……...…...……47
Figure 4.4: Perceptions on methods of flood prevention and control: Profile of mean
scores: N=528…………………………….…………………..…………….55
Figure 4.5: Average percentage of health care services sourced by
households during the flood season…………………...…………………....65
Figure 4.6: Effectiveness of coping strategies in study area……….………………..….70
Figure 4.7: Level of preparedness in the study area…………...………………………..71
Figure 4.8: Sources of support received during flood times in the study area……..…...72
Figure 4.9: Satisfaction levels with the amount relief aid received……………………..74
Figure 4.10: Perception of coping capabilities in the absence of external support…..…75
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List of pictures
Photo 2.1: Showing the general state of roads at onset, during and soon
after the flood season………………………………………………………...17
Photo 3.1: Selection of participants for FGD discussion (Chief‟s meeting)………...…..37
Photo 4.2: Picture showing a house with a raised floor and a boat on stand by
for evacuation of people and property during extreme flood conditions…….58
Photo 4.3: Picture shows harvesting of rainwater into a water tank; a coping
mechanism to address water problems ……………………….…………...62
Photo 4.4: A woman in Ayweyo receives 2 Kgs. of maize as an incentive for
digging/clearing a water channel. This is a government initiative:
The Food for Work Program……………………...………………………...73
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Abbreviations and acronyms
APFM
-
Associated Program on Flood Management
APELL
-
Awareness and Preparedness for Emergencies at the Local Level
CHWs
-
Community Health Workers
FGD
-
Focus Group Discussion
GOK
-
Government of Kenya
GWP
-
Global Water Partnership
ICLR
-
Institute for Catastrophic Loss Reduction
IPCC
-
Intergovernmental Panel on Climate Change
IDNDR
-
International Decade for Natural Disaster Reduction
IRIN
-
Integrated Regional Information Network
IRMED
-
Institute for Resource Management and Economic Development
ISDR
-
International Strategy for Disaster Reduction
IUCN
-
International Union for Conservation of Nature
LVEMP
-
Lake Victoria Environnent Management Programme
NGO
-
Non Governmental Organization
SPSS
-
Statistical Package of Social Sciences
TEK
-
Traditional Ecological Knowledge
UNDP
-
United Nations Development Program
UNEP
-
United Nations Environmental Program
WHO
-
World Health Organization
WMO
-
World Meteorological Organization
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Abstract
Flooding is one of the most widespread of climatic hazards that continues to pose serious
multiple threats to public health. Globally, efforts to combat it have shifted towards longterm commitment to capacity building and broad based community involvement in flood
risk interventions. In Kenya, the ability of local people to resist the impact of disasters
has not been given adequate attention. This was descriptive cross sectional study and the
objectives were to explore existing traditional flood knowledge, perceptions and behavior
associated with flood risks and attitude of community towards external support. Most
prone and least prone areas were selected for comparative analysis between the two risk
levels. Flood area residents and institutional representatives were sampled using simple
random sampling and a total of 528 households, 7 FGDs and 11 key informants
participated in the study. The results were derived from questionnaires, Focus Group
Discussions and key informant interviews. Data were analyzed using the SPSS Program.
Chi-square test was used to determine association and difference between two variables.
Results demonstrated in the study show that traditional flood knowledge and coping
mechanism exist in the study area (80%) and these strategies were used as a trusted
source of information and importance to this community. The findings revealed
significantly greater level of awareness of flood hazards in the high risk areas in
comparison to the low risk areas (p=0.001). They also demonstrated significant clear
spatial differences in the level of awareness and use of traditional flood knowledge
between respondents living in high and low risk areas. These were significantly
influenced by demographic variables such as age, occupation, education and length of
residency (p=.0001). Perception of risk was influenced by several variables, most notably
past experience and level of exposure to risk. The burden of diseases was significantly
higher during the flood season but the advantages of living in the flood plains seemed to
outweigh the health risks associated with flooding. The result is a combination of
innovative adjustability and passive acceptability of potential hazards. Most of these
indigenous actions were taken at the household level to adapt to the health risks posed by
floods. Aid dependency during flood disasters was found to have significantly
contributed to decreased ability cope (high risk, p=0.026; low risk, p=0.003). This study
concluded that there was a wealth of traditional flood knowledge which indicated some
ability of the locals to be resilient. Higher perception of risk did not necessarily translate
into better preparedness. Most indigenous coping actions were taken at the household
level to adapt to the health risks posed by floods. The dependency syndrome and its
pitfalls for creating less resilient communities was evident in this community. This study
recommends that programs promoting the use of traditional flood knowledge should be
integrated into official flood warning methods to exploit the local ways of predicting and
coping with floods. The community needs to embrace both structural and non-structural
measures to achieve the greatest results. The Government, NGO‟s and CBO‟s dealing
with flood disasters in Nyando should focus on preparedness by enhancing local coping
capacities on protection measures in anticipation of future flood events. Flood warning
activities tailored to local social contexts will be instrumental in reducing vulnerability
and strengthening capacity of the affected communities to respond more effectively to
flood emergencies.
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CHAPTER 1: INTRODUCTION
1.1 Background information
Flooding is one of the most widespread of all the hydro meteorological hazards causing
huge annual losses in terms of damage and disruption to economic livelihoods,
businesses, infrastructure, services and public health (Few et al., 2004).
Table 2.1: Types of floods and their characteristic impacts
Type
Duration
Characteristic impacts
Predictable regular
Up to 3
Blocks access. Damage and displacement of population
flooding
months
often relatively low depending on levels of protection
Increased size of
Up to 6
Blocks access to many areas. Greater potential for
regular flooding
months
infrastructure damage, livelihoods impacts, and large
displacement of populations.
Flash flooding
A few days
to weeks
Rapid cresting often with little warning. High velocity
flood flows can destroy infrastructure. Population
displacement often localized.
Urban flooding
A few days
Can be rapid-onset, often coming flash floods in urban
to weeks
rivers or from saturation or blockage of urban drainage
systems. Potential for infrastructure damage affecting
larger service area. Population displacement often
localized.
Coastal flooding
A few days
Often combined with wind damage from storms -.
Damage and displacement along coastline with extent
depending on storm size.
Slow-onset from
sustained rainfalls
3-6 months
Bock access. Depending on season, damage to crops
may be significant. Population displacement limited
and may be dependent on food security.
Adopted from McCluskey, 2001, cited in ProVention (2008)
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Flood disasters are on the rise and in the past decade, on average more than 140 plus
million people have been affected each year with annual mortality estimated at 25,000
(World Meteorological Organization (WMO), 2005). Of all natural disaster deaths, 97%
occur in developing countries. Asia and Africa are the most affected continents with
floods accounting for half of these disasters. Much of Africa is vulnerable to flooding
with episodes of floods accounting for 26% of total disaster occurrences (Institute for
Catastrophic Loss Reduction (ICLR), 2004).
In Kenya, many parts of the country experience unexpectedly heavy rainfall in mid-April
which continues through the end of May and from September to November. The areas
that are most prone to flood disasters are the Lake Victoria Basin, comprising of Nyando,
Migori, Kisumu and Busia Districts; the Tana River plains and other parts of Eastern and
Coastal provinces (Mungai, 2002).
Floods in Nyando are caused by rivers overflowing their banks due to their carrying
flows in excess of their carrying capacity within their banks. This generally happens
during the long and short rains, especially after spells of intense and heavy rainfalls in the
catchments of the rivers. The upper reaches of Nyando are in Kericho and Nandi Districts
where annual rainfall is high and it is this rain that causes the most devastating of the
floods in the basin. The flat terrain reduced vegetation cover and predominantly black
cotton soils found in the water sheds do not allow quick infiltration thus increasing
surface runoff which causes flash floods. The situation is aggravated by gulley formation
due to soil erosion, poor land use and deforestation (Onyango, 2005).
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Floods in the Kano Plains have become more severe and frequent and the rivers have
gradually lost their ability to buffer environmental variability. The historical pattern in
Nyando shows consistent deforestation and degradation over the last hundred years,
punctuated by severe worsening of these problems during the heavy rains that
accompanied El Nino events (Mungai, 2002). Flooding in the Nyando is a rapidly
growing public health problem in the area. Floods have increased the incidence of a
number of water associated diseases among people and animals, constrained crop and
tree selection, made transportation more difficult, interrupted schooling and destroyed
property and infrastructure (ibid).
The magnitude of disaster is not determined by floodwater alone but also by the pattern
of vulnerability in which people live. These people, often already vulnerable to other
disasters and stresses such as HIV/AIDS, drought, food insecurity, and on-going conflict,
are forced to live in hazardous places, building their homes and growing their food in
flood plains (ProVention, 2008). Despite the risks, many communities continue to occupy
flood plains due to economic advantages of fertile soils and availability of water supply
(United Nations Environment Programme (UNEP), 1998). Full control of floods is not
possible or economically feasible and complete abandonment of the flood prone areas
may not be reasonable because it is not only a valuable resource but in many areas, the
only means to support life (UNEP, 2008).
The scale of damage by a flood event largely depends on the state of preparedness and
response mechanisms employed by the communities affected to combat the negative
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impact. Vulnerable people individually and collectively develop their own means,
resources and strategies to cope with flooding. Social capital e.g. reciprocal support
among neighbours, support from immediate family members and wider kinship networks
is a vital safety net for people in coping with recurrent flooding. Shahaduzzaman, (1999)
notes: “how people respond will be determined by their personal strengths, those of their
families, friends and community, and the resources which they have or receive.
The fourth assessment report of the intergovernmental Panel on Climate Change (IPCC),
2007 predicts that heavy precipitation events, which are likely to increase in frequency,
will augment flood risks. These floods will affect lives and in human settlements in all
areas, e.g. coastal zones, river deltas and mountains. With increasing climatic variability
ensuring that water related disasters will not abate any time soon, actions designed to
strengthen resilience of communities living in flood-prone locations will be increasingly
important in reducing the human burden from flooding. In this context, a focus on the
role of community perceptions and responses is crucial in developing a comprehensive
understanding of societal vulnerability and how social processes play a decisive role in
shaping coping capacities (Few et al,. 2004).
1.2 The problem statement
Flooding is a recurrent phenomenon in Nyando District. Population pressure, climate
variability, and environmental degradation on flood plain have grown and the risks that
floods pose have become increasingly evident. As per the assessment made after recent
floods, in the Kano plains, the average annual damage is about US$ 850,000 with annual
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relief and rehabilitation measures costing US$ 600,000 (Associated Programme on Flood
Management (APFM), 2004).
In the study area, interventions to address the problem of flooding over the years have not
produced desired results. This is partly because of the conventional conceptualization and
analysis of the flood problem that has ignored local perceptions and experiences and
historical processes that are the triggering factors of flood vulnerability.
There has been relatively little scientific research characterizing health outcomes of flood
hazards and similarly, little social science research targeting how vulnerable populations
perceive, respond to flood risks. There is also a growing frequency of small and medium
scale disasters related to patterns of human environmental intervention, indicating that
disaster risk is accumulating. These disasters have a larger cumulative impact but are
generally ignored by both national and international disaster management or development
policies and represent a challenge for disaster risk reduction.
1.3 Purpose of the study
A major part of improving the management of flood disasters is by gaining a more
detailed understanding of the issues at hand. Research is a vital element in this process.
Much of the existing literature on flood management in Nyando District has explored the
physical aspects of their nature and occurrence (Mungai et. al., 2002; 2004; Walsh et al.,;
2004; the Integrated Regional Information Network (IRIN), 2005). However, there is also
a growing literature that is examining the issue from a social perspective with calls in
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particular for more research into the social responses to flood management, (Few, 2005;
Pratt, 2002; Packham, 1992). Consequently, the present study shifts focus and instead
chooses to understand constructs of flood risk and local coping strategies as important
aspects of flood management in Nyando District.
Perception and evaluation of risk has an influence on the costs paid after a disaster.
Millions of shillings are spent on flood relief programs annually in the study area and that
underscores the relevance of this study. Additionally, in order to develop effective
information strategies and policies (risk communication), there is need for baseline data
on community perceptions and response to flood risks.
1.4 Study objectives
The main objective of this study was to investigate how communities in Nyando District
perceive and respond to flood risks in order to develop effective flood warning activities
that are tailored to local social contexts.
The specific objectives were to:
i. Explore traditional knowledge on flood forecasting and early warning of flood
risks.
ii. Establish communities‟ perceptions of floods risks.
iii. Identify behavior associated with flood risk management in the study area.
iv. Assess attitude of the Nyando communities towards external support systems.
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1.5 The Study was guided by the following research questions:
i. What is the existing traditional knowledge on flood forecasting and early warning
of flood risks?
ii. How do Nyando communities perceive flood risks?
iii. What are the existing response mechanisms to flood risks?
iv. What is the attitude of Nyando communities towards external support systems?
1.6 Null Hypothesis
Level of exposure to risk does not influence awareness and use of traditional knowledge,
perceptions of flood risks, response mechanisms and attitude towards external support of
Nyando communities.
1.7 Significance of the study (rationale)
The potential utility of the study is to reduce vulnerability; to strengthen capacity of the
affected communities to respond more effectively to flood emergencies and to provide
insights into possibility of a more integrated approach to flood prevention and coping
with loss.. This study is envisaged to benefit the following groups of people: rural
communities living in flood prone areas, disaster managers, policy makers, researchers
and scholars, and funding agencies.
1.8 Scope of study and limitations
i. Kenya has experienced several flood disasters that have occurred in different parts
of the country but the present study concentrated on Nyando District with a
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population of 332,137 (Kenya, 2002-2008). This was necessitated by the available
resources and the time frame within which the project was to be completed.
ii. The study was not connected to any concrete flood but to related flood experience/s
by the respondents.
iii. Conclusions are based on information elicited from the fieldwork.
iv. Results obtained may not be generalized to other areas when assessing data and
making interpretations that would be appropriate across broader scales.
1.9 Assumptions
This study was based on the assumptions that:
1. The sample population was assumed to have similar characteristics with the rest
of the population residing in Nyando District; therefore they were assumed to be a
true representation of the Nyando District community.
2. Assumption was made on the information given by the respondents to be true.
1.10 Conceptual framework
This study used a conceptual model adapted and modified from Handmer and PenningRoswell, (1990). In this model, modifications were made to focus on the interrelationships between human responses to a natural hazard and how the perceived threat
influences subsequent actions.
This model helps to illustrate why people continue to live in risk-prone areas. How they
assess risk is influenced by several factor; benefits of living in a flood plain, lack of
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alternatives, the unpredictability and changing nature of the risk.
Probability of a
flood hazard
Perception of risk
Perceived probability
of risk distorted by:
Recognizable and
tangible benefits of
non-hazard experience
Risk not
acceptable
-Social capital: Existence
of friends, relatives and
wider kinship networks
Ignorance or non-comprehension
of flood threats
Risk acceptance
Risk estimation and
Evaluation
Risk reducing measures:
- Adaptation
- Adjustment
- External assistance
---
Individual characteristics:
Age, gender, education, income, length of
residency and flood experience
Resources Availability and Control
(Human, economic, and organizational)
Figure2.1: A conceptual model adapted and modified from Handmer and PenningRoswell, (1990) that elicits perception and the behavioural response to flood hazards.
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The model further highlights important human attributes (some quantifiable and some
non- quantifiable) affect how people perceive risk; socio-economic characteristics,
peoples Traditional Ecological Knowledge (TEK) of the environment and experience of
flood hazards.
Coping is also highlighted in the model, which illustrates risk reducing measures to
respond to unacceptable perceived threats and the role of external assistance. The
underlying factors affect each other in a complex interrelationship. Whether strategies are
effective is ultimately an outcome of resource availability and control.
1.11
Theoretical framework
This study combined the cultural theory paradigm (Thompson et. al. 1990; Dake, 1991)
and the Psychometric approach (Fischhoff et al., 1997; Slovic, 1987; 1992 cited in Plapp,
2006) to reveal the underlying cognitive structure of risk and the influences of social
values. In addition to the cultural theory and psychometric approach, some further
components were included in the research design to obtain a better overview on possible
influences on risk perception and coping strategies.
1.11.1 Cultural Theory Paradigm
The cultural approach perceives environment and risk as social constructs (Wildavsky,
1979 cited in Krimsky and Golding, 1992). It further assumes that cultural patterns
structure the mind-set of individuals and social organizations to adopt certain values and
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reject others. These selected values determine the perception of risks and benefits (Renn,
1992).
According to cultural theory, risk management is the proximate stimulus rather than its
outcome. In addition to being proactive, management strategies in cultural theory include
various coping and adaptive behaviors that tend to be discounted in conventional
approaches (Rayner, 1992). Risk communication in cultural theory emphasizes creation
of shared meaning and trust over the transfer of quantitative information (Rayner, 1988
cited in cited in Krimsky and Golding, 1992).
The cultural theory is fundamentally concerned first with relationships among human
beings and second with societal relationships with nature. Methodological individualism
that extrapolates from individual behavior to social action has no place in cultural
analysis (Rayner, 1992). The cultural theory of risk is arguably the most eloquent and
comprehensive framework, although it has been criticized for its lack of empirical
evidence and apparent relativism (Krimsky and Golding, 1992).
1.11.2 The Cognitive /Psychometric Paradigm
The psychometric paradigm encompasses a theoretical framework that assumes that risk
is subjectively defined by individuals who may be influenced by a wide array of
psychological, social, institutional and their interrelationships can be quantified and
modeled in order to illuminate the responses of individuals and their societies to the
hazards that confront them (Slovic, 1992).
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The psychometric paradigm (Slovic, 2000) concentrates on various risk characteristics or
risk dimensions to explain the sometimes „irrational‟ perceptions of „lay persons‟. This
approach assesses the cognitive structure of risk - not actual behavior. This method uses
questionnaires to ask people directly about their perceptions of risks and benefits and
their „expressed preferences‟ for various kinds of risk /benefit trade-offs.
The psychometric paradigm with its elicitation of perceptions and expressed preferences
assumes that people can provide meaningful answers to difficult, if not impossible
questions. The results are dependent upon the set of hazards studied, the questions asked
about these hazards, the types of persons questioned and the data analysis methods.
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1.12 Operational definition of terms
Acceptable risk:
The level of loss a community considers acceptable given existing
social-economic, political, cultural, technical and environmental
conditions
Adaptation:
Change in behavior and functioning of a system to reduce
vulnerability.
Attitude:
Feelings, beliefs and behavior tendencies towards concepts related
to flood risks and flood management.
Catchment area:
The area from which water runs off to a river.
Cognition:
The conscious or unconscious process of deriving meaning from
sensory data. So „perceived risk‟ is termed cognated risk‟.
Community:
A process where the concerned communities function and
Participation
contribute to a cohesive group to perform an activity.
Education:
Highest level of education attained by the respondent. For
example: primary, secondary and university
Early warning:
The provision of timely and effective information, that allows
individuals exposed floods to take action to avoid or reduce their
risk and prepare for effective response.
Flood:
A temporary covering of land by water outside its normal confines.
Flood control:
Interventions to limit flooding.
Flood damage:
Damage to receptors (buildings, infrastructure, goods), production
and intangibles (life, cultural and ecological assets) by a flood.
Flood forecasting
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A system designed to forecast flood levels before they occur:
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Flood disaster:
A flood event that has the potential to cause harm with resulting
damage or risk to health, life and livelihoods.
Flood vulnerability: Measure of risk combined with the level of social and economic
ability to cope with a flood event
High risk areas:
Areas highly prone to flooding.
Household:
A person or group of people who occupy the same dwelling as
their primary residence.
Low risk areas:
Areas medium prone to flooding.
Income:
Amount of incoming money from various sources at the end of
each month.
Intervention:
A planned activity designed to effect an improvement in an
existing flood management system.
Key informant:
Participant who commands respect in the community either due to
their profession or position of leadership.
Perception of risk:
The subjective assessment of flood risks based on experience and
information acquired within the social, cultural and historical
context of the study area.
Preparedness:
The ability to ensure effective response to flood impact.
Resilience:
The ability of a system/community/society/defense to react to and
recover from the damaging effect of floods.
Response:
Activities that occur in the aftermath of a flood to assist victims
and to rehabilitate or reconstruct the physical structures of the
community.
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Risk:
The probability of harmful consequences to human population
resulting from flooding.
Risk perception:
Risk perception is the view of risk held by a person or group and
reflects cultural and personal values, as well as experience.
Susceptibility:
The
propensity
of
an
individual/household/community
to
experience harm.
Traditional:
The whole body of knowledge developed over time by
knowledge
communities to predict the coming of heavy rains and floods.
Vulnerability:
The conditions determined by physical, social, economic and
environmental factors, which increase the susceptibility of a
community to the impact of flood hazards.
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CHAPTER II: LITERATURE REVIEW
2.1 Introduction
This chapter discusses literature related to the subject of the study. The literature was
reviewed under various major headings which included: Nature of flood risks,
vulnerability to flood risks, perception of flood risks, behavioral response to flood risks
and attitude towards external support.
2.2 Nature of flood risks
Natural hazards, otherwise known as environmental hazards, are generally defined as
geophysical events that can potentially cause large-scale economic damage and physical
injury or death (Johnson et al., 2000: 216). It is into this category that flood hazards fall.
Floods can be predicted to a reasonable extent with the exception of flash flood, whose
scale and nature are often less certain (Asian Disaster Preparedness Center (ADPC),
2005)
When interaction with humans occurs, floods have the potential to exact a huge impact
on the public health of human populations. Since 1900, for example, flood disasters alone
have led to at least 6.8 million reported deaths and 1.3 million reported injuries (Few et
al., 2004). Outbreaks of flood related diseases have been reported following major flood
events. The immediate health impacts are increase in cases of diarrhoea, cholera, malaria,
typhoid, skin diseases and mental problems (Few et al., 2005).
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Access to food stuff may prove difficult or impossible when food distribution networks
are unable to operate. The impact of inundation of crops and agricultural land affects not
only the local community but even those who live further away but are reliant on food
production from these lands (Badjeck, 2004). Floods destroy shelter, schools, hospitals,
power lines, roads and are liable to result in population displacement. This displacement
can result in individuals losing their homes, possessions and livelihoods (Few et al.,
2005).
The consequences of floods are by no means solely negative. Seasonal river floods in
particular play a big role in supporting eco systems, renewing soil fertility in cultivated
flood plains (Wisner et al., 2004). In regions such as the flood plains of Bangladesh, a
„normal‟ level of seasonal flooding is therefore regarded as positive: it is only when a
flood reaches an abnormal level that it is perceived negatively as a damaging effect
(Parker, 2000, cited in Few, 2004).
Photo 2.1: Showing the general state of roads at onset, during and soon after the flood
season.
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2.3 Perception of flood risks to public health
Understanding how a community perceives health risks such as polluted water,
inadequate drainage, or lack of garbage collection is essential to designing effective
programs to address those problems. Individuals perceive risks to their health through a
lens derived from their cultural, economic, societal, and educational backgrounds and
respond accordingly. For example, a squatter in a slum in Calcutta, India, might happily
boil water collected at a public tap rather than move to a house with piped water that was
located far from job opportunities; a middle-class family in Los Angeles would probably
make a very different choice (Messner, 2005).
Until recently, these differences in how people view and respond to risks were not part of
formal health risk analysis, which has traditionally relied on statistical correlations
between exposure to risks and the incidence of various illnesses. Now, health planners
are beginning to realize that using such objective measures of risk to design public health
projects without accounting for how the affected community itself views the health risk
being addressed is a recipe for failure.
It is increasingly recognized that individual values, beliefs and behavior operate within a
social context. There is growing consensus that local perceptions and indigenous
knowledge should be important elements in the evaluation of programs aimed at
improving health. Recent literature on health promotion has focused on the notion that
individual values, beliefs and behavior operate within a social context. As reviewed
recently in Health Promotion International by Whitelaw and colleagues (Whitelaw et al.,
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19
2001), and discussed at length by Poland et al., (2000), „settings‟-based activity has
indeed become very popular, as it offers health promotion a conceptual base that allows a
much broader multi-sectoral and trans-disciplinary approach to health promotion. Of the
various models of settings-based approaches, a preferred approach is one that combines
top level commitment and guidance with a high level of community and individual
participation (Whitelaw et al, 2001).
Perceived health risk is inherently multidimensional, with many characteristics other than
the probability of harm affecting human judgment. How „risky‟ an exposure or behavior
is perceived to be by a given individual depends on a long list of factors, including
whether the risk is perceived to be voluntary, familiar, amenable to easy change,
associated with benefits, and associated with immediate or short-term versus delayed or
long-term impacts. While the relationship between changing health risk perceptions and
changing health behaviors and health status is still quite unclear, understanding the
factors, and in particular the social factors, that impact health risk perception is useful in
designing mitigation strategies (Robert et al., 2003 cited in Messner, 2005).
„Social construction of risk‟ refers to the notion that how a society collectively defines
and responds to a given hazard is determined by social discourse, not merely by science
or technological information (McDaniels, 1998). The use of „change in health risk
perception‟ as an indicator of the impact of the intervention implicitly takes into
consideration the influence of the social construction of risk. Thus, it is important to
understand the very strong influence of social context in evaluating health promotion
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initiatives in Kenya. In this social context is a component of monitoring changes in health
risk perception, which is a particularly useful adjunct to other indicators of effectiveness
of the intervention (Spiegel et al., 2001; Spiegel et al., 2003).
According to various studies on the perception of technical and environmental risks, there
are several factors which influence risk among which are: characteristic of the risk
source, value attitudes, ethnic, cultural and socio economic background (Solvic, 1996,
2000 and Vaughan/Nordenstam, 1991; cited in Messner, 2005) and personal variables
such as profession, individual‟s level of risk tolerance, knowledge, and communication of
changing social views of risk (Barke et al., 1997; Smith, 2001: 59, cited in Messner,
2005). Therefore risk is regarded here as multidimensional concept that combines both
the subjective (quantitative) assessments based on experience and information as well as
the perceived or attributed risk characteristics within a certain context (Renn, 1989).
2.4 Vulnerability to Flood Risks
Dow (1992) and Cutter (1996) have provided reviews of the development of the concept
of vulnerability over the years. Despite differences in the definition of the term
“vulnerability,” two main views have emerged (e.g. Adger et al., 2004 cited in
Nethengwe, 2007). The first view treats vulnerability as a pre-existing condition and
focuses on potential exposure to hazards (Cutter, 1996). The second major perspective on
vulnerability suggests that not all individuals and groups exposed to a hazard are equally
vulnerable; rather, people display patterns of differential vulnerability (Blaikie, 2004).
This differential vulnerability depends on exposure and on the coping ability of those
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affected and their resilience levels (Dow, 1992; Watts and Bohle, 1993; Cutter, 1996;
Clark et al., 1998; cited in Nethengwe, 2007).
Cutter (1996) asserts that a third major theme is emerging in vulnerability literature. The
concept of vulnerability as a “hazard of place” combines elements of differential
vulnerability and vulnerability as a pre-existing condition. This approach called the
vulnerability of places framework by Nethengwe, (2007) treats vulnerability as both a
biophysical risk and a social response within a specific geographic domain. Researchers
such as Yarnal, (1994) and Clark et al., (1998) have employed this approach. Flood
vulnerability is thus not merely proximity to flood zones, but it is the product of the flood
as a physical, political and socio-economic phenomenon (Alexander, 1993; 1997).
Generally, marginalized groups have less social powers and fewer economic resources
and physical capacity to anticipate, survive and recover from the effects of massive
floods (Few et al., 2003). Poverty is a major factor that increases vulnerability and
impacts of floods are likely to persist longer among the poor. People in these areas have
less possibility for evacuation from flood prone areas and are more vulnerable to flood
related diseases which can prove fatal (Coutio, 2004). The elderly, the disabled and the
children are particularly vulnerable, and gender -biased attitudes and stereotypes can
complicate response and extend the time for recovery (Pilon, 1999).
2.5 Behavioural response to flood risks
People take some positive action to reduce losses, and some preventive action much in
advance of the hazard event, and others choose a large number of adjustments. The
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reasons for diversity might be due to differences in what people know about hazardous
events, how they perceive them, and the concepts they use to classify their experiences
and make decisions accordingly (Eyob, 1999). Adjustments vary tremendously, by
hazard and society, but are universally found (Kates, 1978). It has also been emphasized
that for a number of African countries, adaptation is an option not by choice but by
compulsion.
2.5.1 Coping mechanism
Historically, all communities living in flood plains have always co-existed with floods
and many studies identify such communities to have a traditional flood culture,
characterized by adjustments to mitigate flood damage. Due to frequency of long history
of flooding, it is possible to find collective action patterns and cognitive patterns which
are adjusted to the hazard situation; through the elimination of doubt, thus making the
situation predictable (Kates, 1978). Social capital e.g. reciprocal support among
neighbours, support from immediate family members and wider kinship networks, is a
vital safe net for people in coping with recurrent flooding (ProVention, 2008).
The most basic coping mechanism is that of the family. Kinship is a strong bond and in
times of need people will first look up to their families and relatives for support
(Wijkman, 1984). Del Ninno et al., (2000) for example reports on how borrowing and
selling belongings and reducing food consumption became short term economic coping
mechanisms for poor families affected by the extreme Bangladesh flooding of 1998.
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Community level action strongly suggests that response at this level may be of key
importance in influencing public health. One crucial area in terms of public safety is
warning and evacuation, for which community based activities, may provide the key to
survival (Few et al., 2004). Religious/ social institutions help individuals to cope during
emergency periods. They provide leadership, shelter, emotional support and help with
burials. In some areas, churches are also called upon to ensure emergency aid is
distributed equitably. Internal political/ economic organizations serve as point through
which the government can provide assistance to the victims. Mutual aid groups such as
agricultural cooperatives and labor unions provide leadership as well as some degree of
financial support (Wijkman, 1984).
Response to flood risks that involves a change in action or policy is referred to as
adaptation, and the ability of people and systems to bring about such changes is referred
to as adaptive capacity (Few et al., 2004). As with coping capacity adaptive capacity of
people and systems is shaped by social, economic and political processes (Adger et al.,
2003).
2.5.2 Traditional knowledge on flood forecasting and warning
Flood forecasting and warning is one of the most important tools to reduce flood risks
and minimize impact on life and property. At present many rural populations most in
need of hydro-meteorological and environmental information are not able to access it and
have to depend heavily on highly refined perception of nature through the interpretation of
signs (International Strategy for Disaster Reduction (ISDR), 2005).
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Communities have their own early warning systems woven into their culture. They
observe nature and changes that take place in the flora, the behavior of animals, the rivers
and clouds. These changes according to them provide signals for impending disasters
(Sharma, 2002). This knowledge is the sum of facts that are known or learned from
experience or acquired through observation and study and handed down from generation
to generation. Communities identify themselves easily with indigenous knowledge
systems which have enabled them to live in harmony with their environments for
generations (UNEP, 2008).
Indigenous knowledge gained international recognition after the United Nations
Conference on Environment and Development (UNCED) held in June, 99 in Rio de
Janeiro. Agenda one of the environmental agreements signed at UNCED emphasizes that
governments and intergovernmental organizations should respect, record, and work
toward incorporating indigenous knowledge systems into research and development
programs for the conservation of biodiversity and sustainability of agricultural and
natural resource management systems. Other international documents, such as the 1980
“World Conservation Strategy” by the International Union for the Conservation of Nature
and Natural Resources (IUCN), also paved the way for the recognition of the role played
by indigenous knowledge in biodiversity and human development (UNEP, 2008).
2.6 Attitude towards external support
The responsibility of providing relief during natural disasters falls mainly on the
government, which is supposed to have proper machinery, logistics and resources. In
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25
areas frequently visited by disasters of a kind, local and international NGOs are also
known to provide relief and rehabilitation services (Sharma, 2002).
In many emergency contexts, aid agencies hesitate to provide food and other aid for
extended periods because of fears that this may create „dependency‟. Concerns about
dependency can influence decisions about levels of assistance, and affect what type of
assistance people receive, where and when Harvey (2005) argues that framing concerns
in terms of dependency is unhelpful and can result in cutting back relief of people who
may still be in desperate need. The focus should be not how to avoid dependency but
how to provide sufficiently reliable and transparent assistance so that those most in need
understand what they are entitled to and can rely on it as part of their own efforts to
survive crisis.
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CHAPTER III: METHODOLOGY
3.1 Introduction
This chapter presents the following: research design; variables; location of study;
population and sample selection; sampling procedure and sample size; data collection
instruments, data collection procedures; and data analysis.
3.2 Location of study
The study was carried out in Nyando, one of the 12 districts in Nyanza province. It has 3
main topographical land formations namely the Nandi Hills, the Nyabondo Plateu and the
Kano Plains which are sandwiched between the two hills. The district has a total land
area of 1,168.42 km with a population of 332,137 (Kenya, 2002-2008).
Nyando District is divided into five administrative divisions namely, Upper Nyakach,
Lower Nyakach, Nyando, Miwani and Muhoroni. Nyando, Miwani and Lower Nyakach
divisions have been conveniently selected as large parts of these areas fall in the Kano
Plain which over the years has experienced the worst effects of flood hazards and people
who continue to live there are still vulnerable to perennial flooding.
Sondu Miriu, Nyando, Awach and Ombei rivers drain from the Nandi Hills where high
rainfall is received to Lake Victoria through very large low lying plains which are also
very heavily populated and are a major cause of persistent flooding along their banks as
they approach the lake with devastating effects. The Kano plains feature very small
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27
slopes/altitude/gradient, large swamps and comprise of predominantly black cotton soils
with moderate fertility and poor drainage.
Nyando River Basin covers an area of 3517 square kilometres of Western Kenya and has
about 258738 (35%) persons from Nyando District residing within the Basin (Mungai,
2002). The lower reaches of Nyando lie between 1000 and 1300 meters above sea level.
It is the hottest and the driest region of the basin with annual average rainfall ranging
from 800mm to 1200 mm, the annual average maximum temperatures ranging from 29 0
0
31 c while the annual average minimum temperatures range from 12-16 c. The natural
vegetation is open scrubland (Onyango et al., 2005).
Dominant river action is deposition and the region is characterized by flooding as a result
several rice irrigation schemes have been set up. Annual flooding near the delta leaves
rich alluvial deposits that are cultivated and yield good harvests. The deposits also cause
the river channel to shift. This has led to serious inter-clan conflict in the delta region
because the river is used as a boundary and this boundary keeps shifting. The government
is yet to find a lasting solution. The most valued fields are those found in the flood plains.
3.3 Research Design
The study used the cross sectional descriptive survey design, as it sought to establish and
describe a prevailing phenomenon. The design was suitable for this study given that
extensive data on traditional knowledge, perceptions and coping strategies associated
with flood risks was collected at one point in time. Apart from reporting the current
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status, the collected data were used to determine whether and to what extent relationships
exist between and among the variables considered in the study.
3.4 Study variables
i.
The dependent variable was: category of risk (high or low risk)
ii.
The independent variables were: Knowledge, attitude, awareness, perception,
socio-demographic, socio-economic and socio cultural factors.
iii.
Preparedness for floods was measured in terms of measures taken before and after
the flood events.
iv.
Emergency responses were measures taken during the flood events.
v.
Insufficient food supply was measured in terms of households having to survive
on less than two meals a day.
3.5 Sampling techniques and sample size
3.5.1 Sampling technique
Given the very large size of the District, areas of study were selected using a multi-stage
sampling process. In view of the important role of institutional factors in influencing
community responses, the administrative ladder of division and location and sub location
was used for selection of study areas (Table 3.2). Based on meteorological information
on the extent and frequency of flooding, 3 frequently flooded divisions, Nyando, Miwani
and Lower Nyakach were selected out of the five divisions based on most-prone,
medium-prone and least-prone categories, 3 most-prone locations and 3 medium-prone
locations, one from each division were selected out of the total 17 locations. The most-
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prone category consisted of areas that experience extensive high frequency of flooding;
the middle-prone category consisted of areas that experience moderate flooding and the
least-prone category consisted of areas that experience little or no flooding incidences.
A list of most frequently flooded sub-locations having experienced floods in recent years
was drawn from the 3 most-prone locations and two selected from each location.
Following a similar approach, 6 medium-prone sub-locations, 2 from each medium-prone
location were also selected. The reason for selecting high prone and medium prone
(termed low for purposes of comparison) categories was to give a wider coverage to the
sample and to see if there were any significant differences between the two risk levels.
Identification and selection of respondents was divided into two groups; flood area
residents, in order to analyze perceptions and response from the perspective of local
citizens, and institutional representatives chosen in order to analyze perceptions and
response from the perspective of decision makers and their respective institutions. Simple
Random Sampling procedure was used to identify households selected to participate in
the interview.
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Table 3.2: Selection of study area using the Nyando District administrative ladder
Administrative
Location
Division
Nyando
Miwani
Sub-location
Wawidhi/ Kakola
Magina
K. Ahero
Kochogo
Kochogo North
Kochogo central
Ahero Irrigation
Scheme
Kore
Ombeyi
N.East Kano
Lower Nyakach North Nyakach
N. East Nyakach
Kabar West
Ramulla
Gem Nam
Gem Rae
Agoro West
Agoro East
Population
(Division
total)
Households
(Division
total)
64,511
14,029
58,029
13,982
49,247
11,149
3.5.2 Sample size determination
The river basins cover an area of 3517 square kilometres of Western Kenya and have
about 258,738 (35%) persons from Nyando District residing within (Mungai, 2002).
The sample size for all the sub-locations was computed using the fisher formula:
n =Z2 pqD/d2 (Fishers et al, 1998)
Where, N = the sample size
Z = the standard normal deviate (1.96), which corresponds to 95% confidence interval.
P = persons living in Nyando District at risk of flooding = 258,000
q = total population in Nyando District (332,137) – residents at risk of flooding
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d = the degree of accuracy = 0.05
D = heterogeneous population (most prone and medium prone) = 2
Thus, N = (1.962*0.22*0.78)2/0.052 = 528
Stratified and Proportional Sampling Methods were used to identify individual study
participants (Table 3.3). These techniques were used to assure representation on the
relative size of the data.
Table 3.3: Summary of results of Stratified and Proportional Sampling
Stratum by
Division
Stratum by
Sub-location
Nyando (households)
 Most prone
(High risk)
Magina
K. Ahero
 Medium prone
(Low risk)
Miwani
 Most prone
 Medium prone
Lower Nyakach
 Most prone
 Medium prone
Percentage
in sample
household
population
Sample size
in sublocations
(households)
18%
95
18%
95
18%
95
Kabar West
Ramulla
18%
95
Gem Nam
Gem Rae
14%
74
14%
74
100%
528
Kochogo North
Kochogo central
Ahero Irrigation
Scheme
Kore
Agoro West
Agoro East
Households
(Division
total)
14,029
(36%)
13,982
(36%)
11,149
(28%)
39,160
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3.6 Study Population
The study targets all rural populations at risk of flooding. The accessible population for
this study was the Nyando District communities at risk of flooding. The sample
population was composed of 528 households, 6 selected government officials, 5 project
managers of CBOs and NGOs dealing with disaster management in the area and 7 focus
group discussions; 3 groups of women to accommodate the different age categories and
socio-economic status, 2 groups of men to accommodate the different age categories and
socio-economic status and 2 groups involving teaching staff of both primary and
secondary schools. The main sampling unit was the household.
3.6.1 Inclusion criteria
a)
Adult residents in the selected divisions who were at risk of flooding
b)
Local government officials connected with and working on disaster management
c)
Project managers of CBOs and NGOs dealing with flood management in the area.
3.6.2 Exclusion Criteria
a)
Residents in the selected divisions who were not at risk of flooding.
b)
Residents in the other divisions that were not in the sample population.
c)
Local government officials not connected with disaster management.
d)
Project managers of CBO‟S and NGO‟S that were not dealing with flood
management in the area.
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3.7 Construction of research instruments
This research adopted both quantitative and qualitative techniques using pre-tested house
hold questionnaires, desk reviews, focus group discussions and in-depth individual
discussions. The advantage of using such an approach was that both forms of data
collected complemented each other. For example, interviews could not be rigorously
analysed as quantitative data. However, they offered possible interpretations to trends
found within the numbers.
Likewise, questionnaires provided a large amount of nominal data to highlight the major
trends and empirical findings. However, they did not enable more abstract relationships
to be interpreted, for which the qualitative dimension was more suited. Therefore,
combining the two approaches gave a more realistic interpretation of people‟s
knowledge, perceptions, behaviour and attitude to flood risks. Furthermore, it helped to
minimise the limitations of each form of data collection.
3.7.1 Household questionnaire
The questions were designed in such a way that it was able to capture both nominal and
ordinal data. It was used to measure a number of variables including: traditional flood
knowledge, risk perception, community social cohesion, coping action and attitude
towards external support. The survey was designed to take no longer than 30 minutes to
complete, in order to encourage as many people as possible to participate. The layout of
the questions, which predominantly involved choosing from a list of options also made
the questionnaire easy to respond to. Provision for additional responses was made where
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appropriate so as not to restrict people‟s responses unduly. The identical survey was used
in both high and low risk levels.
.
3.7.2 Interview guide for key informants
A total of 11 In-depth interviews were conducted. Arrangements were made to conduct
the half-hour long semi-formal interviews at the respondents‟ homes and offices. The
conversations were taped and brief notes were also taken (in case of technical failure).
The interview schedule guided the conversation but where additional interesting and
useful points emerged these were further pursued. In addition, several questions were
tailored to each interviewee. Key informant discusions provided a cross sampling and
triangulation of public views and concerns.
3.7.3 Focus group discussion
A total of 7 focus group discussions were conducted. Arrangements were made to
conduct the one and half hours long semi-formal discussions at the chiefs‟ camps, the
DO‟s office and in classrooms at nearby local primary schools. The discussion schedule
guided the moderator but where additional interesting and useful points emerged these
were further pursued. The FGD‟s were conducted from the 19th to the 30th of May 2006.
On average, there were 8 participants per FGD.
3.8 Pilot study
Located 80 km from Kisumu City are Gem-Rae and Gem-Nam sub locations in Nyando
District. These areas were purposively selected for the pilot study because they border
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river Awach and are prone to frequent flash floods. The research instruments were pretested prior to the main study on 30 households of similar characteristics as the target
population but which were not included in the final study. The main reasons for carrying
out the pilot study were to test the instruments regarding ambiguity, sensitivity and
appropriateness. Apart from providing accuracy to the tools, the preliminary study helped
to estimate the time it would take to complete an interview session.
3.8.1 Validity of instruments
Prior to taking the survey into the field, it was vetted by a number of sources. An
informal pretest of the survey was carried out with 30 subjects and the data collection
tools were structured around the responses derived from the pilot study. A professional
translator used to translate the instruments from English to Dholuo before the interviews.
Weaknesses detected in the instruments during the pre-testing were corrected in order to
refine them so as to enhance validity. In cases of any flaws and bias, the instruments were
modified for more clarity and accuracy. Validity was also enhanced through triangulation
because of the use of multiple data collection methods.
3.8.2 Reliability of instruments
To achieve standardization, four research assistants were trained to participate in the data
collection of the study. They were given training on the objectives of the investigation,
introduction to survey procedures and sampling procedures. They were also conversant in
English, Kiswahili and Luo (the local language). In both risk levels, the direct contact
with participants provided additional qualitative information that was useful in
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understanding their responses. Field assistants worked in pairs for accuracy and the
researcher (self) accompanied each group on alternate days
Complementing the household survey, FGDs and Key informant interviews were
undertaken with a range of representatives. These interviews were conducted in the local
language and where difficulties, Kiswahili and English were used. All FGDs and in-depth
individual interviews were audio recorded (to carry out an accurate content analysis of
the verbal responses) and notes taken.
All data collected was checked after completion of each interview to make sure that all
questions were asked and the answers recorded clearly. The same information was
counter checked by the researcher at the end of each day. All the survey data was entered
into the statistical analysis program SPSS. Two identical files were created to guarantee
separation of data for each risk level. Once all cases were entered, these files were then
merged to allow for comparison. To avoid interpreter biases the researcher (self) entered
all the data. After the first few cases were entered, a thorough review of the entry process
was undertaken to check for accuracy and consistency.
3.9 Data Collection Techniques
The questionnaires and FGDs involved selected community members.
In-depth
individual discussions included local government officials involved in flood management
and project managers of CBOs and NGOs dealing with flood management in the area.
Before conducting the interview the researcher explained the purpose of the study to the
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respondents and assured them of confidentiality. The interviewer/moderator read out each
question to the respondents/participants and checked the correct answer in the instrument
for the close-ended items while for the open-ended, brief field notes were taken. Audio
tapes were also used to record key informant and FGD discussions.
Photo 3.1: Selection of participants for FGD discussion (Chief‟s camp)
3.10 Ethical considerations
Permission to carry out the research was sought from the ethical board of Kenyatta
University and relevant authorities of the Ministry of Education Science and Technology,
the district and local government. Target respondents were given adequate explanation on
the purpose of the research and thereafter given time any questions or seek clarification.
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All respondents were taken through the required informed consent procedures. This was
done at the point of recruitment and at the start of each interview/discussion.
3.11 Data Analysis Methods
Three classes of data exist within the survey: data that categorizes and describes people,
data that categorizes behavior of people and data that reveals perceptions, attitudes,
opinions and beliefs. Typical topics used to address this data include: knowledge,
perceptions, behavior, attitude and demographics. This data were analyzed using the
computer package, Statistical Package for Social Sciences (SPSS) Version 11.5 and
Excel spread sheets.
Descriptive statistics was used to analyze continuous and categorical data. This was
presented in form of frequencies and percentages. The Chi-square test was used to
determine associations between the dependent and independent variables for categorical
data. It was also used to establish differences between high risk and low risk groups. The
level of significance was fixed at 0.05 (p=0.05).
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CHAPTER IV: RESULTS AND DISCUSSIONS
4.1 Results
4.1.1 Introduction
This chapter contains detailed presentation and discussion of data analysis and the results
of this study. The findings are presented under the following major headings:
demographic and socio-economic characteristics; traditional knowledge; flood risk
perception; coping mechanisms; and attitude towards external assistance. The main
determining factor of response was the proneness of a particular place towards floods.
4.1.2 Socio demographic characteristics, education and socio-economic status
4.1.2.1 Age and sex of respondents
Respondents of all ages (18 through to over 60) were represented, with slightly larger
numbers in the lowest age bracket 18-25 and 41-50
categories
accounting for
117(22.1%) and 116(22%) of the respondents, respectively (Table 4.1). The oldest age
bracket was 60 and above years which accounted for 71(13.5%) of the respondents. The
proportion of ages of males to females was about 43.8% and 56.2% in all age groups.
4.1.2.2 Marital Status of respondents
The findings of this study showed that majority the respondents 353(67.9%) were
married and living with their spouses, Table 4.1. A further, 114(21.1%) were widowed,
56 (8.6%) were single, while 0.8(1%) were divorced. The age and gender distribution is
summarized in Table 4.1.
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40
Table 4.1: Age, gender and marital status of respondents
Variable
Age
Total
Gender
Total
Marital status
Total
Category
18-25
26-32
33-40
41-50
51-60
60+
Male
Female
Married
Single
Divorced
Separated
Widowed
Low risk
Frequency
65
33
39
56
38
33
264
102
162
264
174
34
1
1
54
264
High risk
Percentage
(%)
12.3
6.3
7.4
10.5
7.2
6.3
50%
19.3
30.7
50%
33
6.4
0.4
0.4
10.2
50%
Total
Frequency Percentage
(%)
52
9.8
34
6.4
38
7.6
60
11.4
42
8.0
38
7.2
264
50%
129
24.4
135
25.6
264
50%
179
33.9
22
4.2
1
0.4
2
0.8
60
11.4
264
50%
4.1.2.3 Educational levels of the respondents
Most studies indicate that there is a positive relationship between education and
knowledge and practices of people. Educational levels of the respondents are presented in
Figure 4.1.
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41
Figure 4.1: A comparison of educational levels between male and female respondents
In general, the findings showed that 99(18.8%) had not gone to school at all and an
overwhelming 86(86.9%) were women. Only a quarter 129(24.5%) of the participants
had gone beyond primary level and among these, 124(23.5%) had completed secondary
education while 17(3.3%) had some post secondary education. The low levels of
education could be attributed to high poverty levels and lack of motivation to pursue
higher education.
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42
4.1.2.4 Main source of income in household
The survey indicates the main occupation of a majority 350(66.3%) to be subsistent
farming. A larger proportion of the respondents in the high risk areas were farmers 201
(38.1) as compared to those in the low risk areas 164(31.1). A small proportion
73(13.9%) consisted of large scale farmers and business people. A mere 68(12.9%) were
grouped under the unemployed category and these included the jobless, students and
housewives. The remaining 37(6%) of the respondents grouped under professional
workers included teachers, medical workers, owners and skilled artisan; carpenters,
mechanics, fishermen, vegetable vendors etc Table 4.2).
Table 4.2: Socio-economic characteristics of respondent in the study area
Variable
Category
Main occupation
Subsistence Farmer
Large scale Farmer
Business
Housewife
Student
Professional Worker
Skilled artisan
Jobless
Total
Income
Total
`
<2500
2501-5000
5001-10000
10001-20000
20001-30000
30001-40000
40001+
Low risk
Frequency Percent
162
2
35
15
8
13
16
13
264
202
36
11
9
3
1
2
264
30.7
0.4
6.6
2.8
1.5
2.5
3.0
2.5
50%
38.3
6.8
2.1
1.7
0.6
0.2
0.4
50%
High risk
Frequency Percent
188
13
23
11
9
6
2
12
264
178
46
22
9
5
3
1
264
35.6
2.5
4.4
2.1
1.7
1.1
0.4
2.3
50%
33.7
8.7
4.2
1.7
0.9
0.6
0.2
50%
43
4.1.2.5 Household family income
The modal gross family income was below 2,500Kshs. which represents a huge
proportion 380(72 %) of the households (less than a dollar a day putting them below the
poverty line). A larger proportion of respondents in the low risk areas 202(38.3%) fell in
this category as compared to those in the high risk areas 178 (33.7%) Nearly 115(21.8%)
had a monthly income of between 2501Ksh and 10,000Ksh. while a mere 33(6.3%)
earned above 10,000Ksh. During the flood season, income was supplemented in a small
way through the sale of livestock, farm produce and fish.
4.1.2.6 Incomes of males Vs females
In this study the incomes of the males were compared to those of the females. The study
findings showed income levels to be rather low among the females as compared to their
spouses. A majority of the females 232(78.1%) earned less than 2500 shillings per month
compared to 148 (64.1%) of their male counterparts. The findings further indicate a
significantly smaller proportion of women 50 (16.8%) compared to males 32(13.9%) and
8(2.7%) females to males25 (10.8%) in the 2501-5000 and 5,000-10,000 income
categories respectively. A mere 7(2.3%) of the females were represented in the 10, 000+
categories which is less than one third of 26(11.2%) of their male counterparts. The
results are summarized in Figure 4.2.
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44
Figure 4.2: A comparison of income levels of the male and female respondents
4.1.2.8 House types
It was observed that a high proportion 449(89.0%) of the wall structures were made of
mud. Nearly 47(8.9%) of walls were made of stone or brick 8.4% while a smaller
proportion 5(1%) were of timber. A mere 7(1.3%) of the walls were constructed with
mats and reeds in the high risk areas. Results further indicate that a huge proportion
442(83.2.9%) of the house structures had iron sheet roofing whilst a mere 68(12.9%) and
17(3.2%) had their roofs thatched with grass and Makuti (reeds), respectively (Table 4.3).
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45
Table 4.3: Wall structure and roof types of households
Variable
Category
Household wall Mud
structure
Stone/Bricks
Timber
Mats/reeds
Total
Roof Types
Iron sheets
Grass
Makuti (reeds)
Total
Low risk
Frequency Percent
(%)
224
42.4
36
4
0
264
218
34
11
264
6.8
0.8
0
50%
41.4
6.5
2.1
50%
High risk
Frequency Percent
(%)
225
46.4
11
1
7
264
224
34
6
264
2.1
0.2
1.3
50%
42.5
6.5
1.1
50%
4.1.2.9 Length of residency
Slightly over half 280(53%) of the respondents had been living in study area for more
than 20 years in both high and low risk areas. Nearly 107(20.3 %) had residents for over
10years while a mere 58(11%), 37(7%) and 17(5%) had been residing in the area for 6-10
years, 4-6 years and 2-3 years respectively. The smallest fraction 19(3.6%) had been in
Nyando District for less than a year. They were either newly married, or had recently
relocated to the area due to business or employment (Table 4.4 shows details).
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46
Table 4.4: Length of residency of study population in Nyando District
Length of
Residency
1yrs
2yrs
3yrs
4-6yrs
6-10yrs
10-20 yrs
20+yrs
Total
Low risk
Frequency
Percentage
(%)
14
2.7
7
1.3
9
1.7
21
4.0
33
6.3
51
9.7
129
24.4
264
50
High risk
Frequency
Percentage
(%)
5
0.9
6
1.1
5
0.9
16
3.0
25
4.7
56
10.6
151
28.6
264
50
4.1.3 Traditional knowledge on flood forecasting
Findings of the study revealed that a high proportion 252(95%) of respondents in the high
risk areas had knowledge of traditional flood forecasting and warning. Correspondingly,
huge majority of respondents in the low risk areas 230(87.1) also reported having some
local knowledge on flood forecasting and warning. Results are summarized in Table 4.5.
Table 4.5: Local knowledge of flood forecasting and warning
Local knowledge of flood
forecasting and warning
1 Yes
2 No
Total
`
Low risk
Frequency percentage
230
87.1
34
12.9
264
100
High risk
Frequency percentage
252
95.5
12
4.5
264
100.0
47
4.1.3.1 Main source of traditional flood information
A huge proportion 357(73.8%) of the interviewees in the study reported getting flood
information mainly through personal observation. They observed changes in weather
pattern and river levels. A summary of these results are presented in Figure 4.3.
80
75.4
72.1
70
Percentage (%)
60
50
40.8
Low risk
High risk
40
26.7
30
20
14.2
4.9
10
11.7
5.3
0
Personal
Observation
Old people
Relatives
Friends
Source of flood information
Figure 4.3: Sources of traditional flood information in the community
Smaller proportions of the respondents 163(33.7%), 46(9.5%) and 41(8.5%) received this
information from elderly residents, relatives and friends, respectively.
4.1.3.2 Traditional flood warning systems
In order to implement some of the traditional flood mitigation practices based on the
understanding of climatic changes as described above, the following early warning
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48
indicators have been used by the Nyando communities in the study area (Table 4.6).
Awareness of flood indicators was significantly higher in the high risk areas.
4.1.3.2.1 Behavior of human beings, animals and plants
The physical appearance and behavior of both domestic and wild animals were
considered important indications of future events. Table 4.5 shows respondents in both
low risk 28(11.7%) and high risk areas 43(17.6%) having reported that when the elderly
people experienced aches/pains in joints/bones (Del gi choke maremo)), it was an
indication of approaching floods. Loud distraught noises from domestic animals, the
siting of unusually large number of cow egrets (Okok), loud and persistent croaking of
frogs (ogwal) and movement of ants (ochunglo) to higher ground were other signals of
impending floods.
4.1.3.2.2 Knowledge of weather pattern
When and when not to expect rains helped to reach conclusions on the probability of
flooding and the subsequent course of action on the part of local community. This
involved predicting probability of future flood events by watching for changes in the rain
pattern. Heavy rain in the area accompanied by strong winds blowing from the river
towards the hills (yamo makudho matek) was considered by half 242(50.5%) of the
respondents in both risk areas to signal the approach of heavy rains. Heavy rains in
Kericho and Nandi Hills was believed by nearly 201(38.1%) in both risk levels to be
clear signs of impeding flash floods usually experienced as a result of the ensuing runoff.
If heavy rain was accompanied by lightning and thunder on the river (mil gi mor mar
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49
polo), it was a signal that it will definitely flood. High temperatures during the wet season
were also mentioned as another sign of heavy rainfall.
4.1.3.2.3 Knowledge on nature of river
Changes in the river constitution were considered important indicators of eminent
flooding. Bursting of river banks due to heavy rain in the area or runoff from the Nandi
Hills was reported as one of the main causes of flooding in the study area. As one
respondent in the FGD put it; “When the amount of water flowing in the river increases
alarmingly, we know there is a possibility that it will flooding and therefore take
appropriate action”.
Change in the color of the river water was another sign of approaching floods mentioned
by the respondents. As described by one of the respondents; “When the river turns a dirty
brown with a lot of debris (yugi), we know the floods are fast approaching from the
Nandi Hills and will be here in less than 24 hours. These are the deadly flash floods that
come without warning sweeping everything on their path including people, animals,
crops, trees, furniture etc”.
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50
Table 4.6: Summary of traditional early warning flood indicators
(Multiple answer response)
Traditional Knowledge
Behavior of humans,
plants and animals
Indicators
Low risk
High risk
Freq.
%
Freq.
%
Old peoples bones aching
Large numbers of cow
egrets sited
Loud persistent croaking
of frogs
Domestic animals making
loud distraught noises
Movement of ants to
higher ground
28
32
12.2
13.9
43
34
17.1
14.2
17
7.3
35
14.6
1
0.4
1
1.7
0
0
10
4
Heavy rains in the area for
long periods of time
Heavy rains in Nandi Hills
Lightning and thunder on
the river
Temperatures higher than
usual
Strong winds blowing
from river to the hills
109
45.6
133
54.5
87
30
35.7
12.3
114
42
47.7
17.6
29
11.9
31
13
20
8.2
30
12.6
Rising of the river
Debris in the river
Noise level of river
increases
River turns dirty brown
66
34
18
27
14.2
7.4
123
139
33
51.5
58
13.9
4
1.6
23
9.6
Knowledge of seasons
Knowledge of flood cycles
0
0
0
0
5
4
2
1.5
Knowledge of weather
pattern
Knowledge on nature
of river
Knowledge of flood
cycles
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51
4.1.3.2.4 Knowledge of flood cycles
Knowledge of flood cycles was the least common traditional early warning indicator
mentioned by a mere 9(3.5) of mostly elderly respondents residing in the high risk areas
(Table 4.5). Until very recently, multiyear cycles of drought and rain were regarded as a
strong indication of the weather that might be expected in a given year. These were
products of centuries of observations handed down through oral tradition. The most
commonly cited indicator for floods by focus group discussion participants was the cycle
of 5 years; i.e. 1992, 1997/98, 2002/3. During each of these cycles, floods were observed
in these communities. These cycles represented longer-term weather patterns in the
region as observed over past centuries.
4.1.3.3 Use of traditional knowledge
The results show that for about half of the respondents in both risk levels, traditional
knowledge remained the most trusted flood detection technique in the area, as
summarized in Table 4.7.
Table 4.7: Use of traditional knowledge in the study area
How much do you rely on
traditional flood information?
1 Very much
2 Somewhat
3 Not much
4 Not sure
Total
Low risk
High risk
Frequency percentage Frequency percentage
126
47.7
135
51.5
88
33.3
75
28.4
47
17.8
49
18.6
3
1.1
5
1.9
264
100
264
100
On the current flood warning systems, participants acknowledged that it was difficult to
accurately predict flash floods using scientific methods and that is why the relied more on
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52
traditional alerts; “What we consider official information is received from the local
administrators at barazas organized by the chief or assistant chief. Most of this
information is very general and just concentrates on flooding zones but not what to
expect”.
4.1.4 Existing perceived risk of flooding to public health
Respondents were asked to indicate their perceptions on 5 items associated with floodrelated risks to health. The resulting perceptions of risk have been classified into five
areas: Social environment, threats to personal health, lifestyle choices, environmental
sanitation and housing conditions. The results are summarized in Table 4.8.
4.1.4.1 Perception of risk to personal health
The profile of perceived “high risk” to personal/community health varied from one risk
level to the other. Table 4.8 shows that epidemics and casualties/death received higher
risk evaluations in the high risk areas as compared to the low risk areas.
4.1.4.2 Perception of risk to food security
There were high risk ratings for damage to crops in both high and low risk areas at
252(95.5%) and 244(92.4%) respectively. Flooding was associated with damage to
livestock by a huge proportion 188(71.2) of respondents in high risk areas. Moderate and
low risk evaluations were recorded for famine in the high and low risk areas,
respectively.
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53
Table 4.8: Perceived presence of health hazards as a result of flooding
(Multiple answer response)
Items of risk perception
Personal/community health
Epidemics
Casualties/loss of life
Food security
Disruption of food supply
Loss of livestock
Famine
Social environment
Displacement/Homelessness
Disruption of schooling
Disruption of transport
Disruption of communication
Burying the dead made difficult
Housing conditions
Damage to shelter
Wet/Damp floor
Sweep away belongings
Collapse of wells and toilets
Cooking made difficult
Environment/sanitation
Contamination of water supply
Land degradation/Soil erosion
Low risk
Frequency Percent
84
31.8
11
4.2
High risk
Frequency Percent
117
48.3
61
23.1
244
119
67
92.4
45.1
25.5
252
188
110
95.5
71.2
41.7
5
24
25
16
0
1.9
9.1
9.5
6
0
174
65
65
24
8
65.9
24.6
24.6
9
3
196
24
15
21
5
74.2
9.1
5.7
8
1.9
250
83
71
44
23
94.7
31.4
27
16.7
8.7
86
7
32.6
2.7
123
36
46.6
13.6
4.1.4.3 Perception of risk to social conditions
Considerable differences in perception of risk to health were found in the area of social
environment. A majority 174(65.9%) associated homelessness with flooding compared to
a mere 5(1.9%) in the low risk areas. In both high and low risk areas low risk ratings
were recorded for disruption of transport, communication and delays in burying of the
dead.
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54
4.1.4.4 Perception of risk to housing conditions
Floods were perceived by a high proportion 250(94.7%) of respondent in the high risk
areas and a majority 196(74.2%) in the low risk areas to cause damage to shelter. Other
risks to health associated with floods included sweeping away belongings, collapse of
wells/boreholes and toilets, wet/damp floors and difficulties with cooking due to scarcity
of firewood and charcoal. The risk ratings for these items were considerably higher in the
high risk areas as compared to the low risk areas.
4.1.4.5 Perception of risk to environment/sanitation
Nearly, 109(39.6%), an average of respondents in both risk levels perceived the quality of
water to decrease during the flood season as a result of contamination. Land degradation
due to soil erosion and gully formation was cited by a mere 43(8.2%).
4.1.4.6. Perceptions on ways of managing flood risks
Respondents were presented with seven statements on management and control fo flood
risks. The mean profile score is indicated in figure 4.4. It is noted that respondents in both
high and low risk areas viewed flooding as more or less inevitable and the likelihood of
controlling its occurrence low. Further analysis revealed that a huge proportion of the
interviewees from both risk levels strongly agreed to the statements that flood preventive
measures are better than relief aid 502(95.1%) and that in the event of a flood, they would
like the establishment of a special fund to give them instantaneous emergency and relief
488(92%).
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55
A high proportion 447(84.6%) of respondents in both high and low risk levels perceived
modern technology to be the preferred solution to solve flood problems and this was
perceived to require huge financial resources to implement. Further results indicate that a
majority 399(76%) of respondents perceived floods to a natural phenomena as apposed to
being divine punishment or „acts of God‟.
Flooding is inevitable
Flood hazard could be reduced
by man-made structures
Huge investments is needed
for flood intervention
Flood preventive measures are
better than relief aid
The state should establish
financial reserves to help
victims
People are capable of
controlling the
occurrence of floods
Modern technology is the best
way to solve flooding
problems
Floods are natural
phenomena
2
High Risk
Low Risk
2.5
3
3.5
4
5
2-3.5: Disagree, 3.6 -5: Agree
Figure 4.4: Perceptions on methods of flood prevention and control
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4.5
56
4.1.5 Behavior associated with flood risk management in Nyando District
4.1.5.1 Coping with damage to shelter
In the study, one of the most serious and direct effects of the flood was damage to shelter.
A huge proportion 222(85.7%) of respondent in the high risk areas and slightly below
half 115(46.7%) in the low risk areas experienced complete or partial damage to their
homes. In addition, items such as utensils, furniture and food were washed away by fast
flowing flood waters. The destruction of these houses resulted in many villagers being
made homeless.
To prevent flood waters entering their homes, it was observed that all homesteads
528(100%) had houses built on raised lands or earthen platforms. The walls and entrances
were elevated so flood water could not reach the plinth, (Photo 4.1). To protect their
homes and farms, a huge proportion 442(83.7%) of the households in both high and low
risk areas dug trenches around the compound while nearly 101(41.6%) and a high
proportion 203(76.9%) in low and high risk areas, respectively planted trees and sisal
fences around their homesteads to break/reduce the flow of flood waters and to prevent
erosion.
During the floods, in homes that were still flooded but occupied, measures taken to
protect property by a huge proportion 342(92.8%) of residents in both risk levels
included, raising items that could be easily destroyed by water like clothes, firewood,
children etc. to higher surfaces like tables and cupboards. During a female FGD
discussion, two female participants gave the following comments: “During the flood
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57
season, it is our responsibility to ensure that our children are safe. We make them play,
eat, and sleep on raised surfaces like tables where they are safe from the flood water; we
cook on top of tables or other raised surfaces; we store household items and food from
our granaries on platforms in the main living room”. To protect the house collapsing
from high volumes of waters, nearly 44(11.2%) of households drilled holes through the
walls to allow flood water to flow through
Table 4.9: Survival strategies to deal with damage to shelter adopted by residents before,
during and after the flood season
(Multiple answer response)
Main coping strategies
Preparation
Built on raised land or earthen platforms
Dug trenches around homestead
Planted trees and sisal around homestead
Piled mud around homestead
During flooding
Evacuated (Went to live with relatives,
neighbors and friends; rented house)
Raised furniture, firewood, food, etc.
Drilled hole through wall
After flooding
Repaired damaged house
Built temporary shelter
Built afresh
Low Risk
High Risk
Frequency Percent Frequency Percent
264
100
264
100
210
87.9
232
79.5
101
41.6
203
76.9
89
33.7
150
56.8
24
16.6
114
64.9
129
11
89.6
7.6
213
33
95.9
14.8
139
0
5
96.5
0
3.48
159
11
52
71.6
5%
23.7
The study found out that during extreme flooding, a majority 144(64.9%) of the families
interviewed in low-lying areas (high risk) were forced to evacuate their homes and move
to higher ground. Many of the families affected were those forced to build close to the
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58
river banks due to land shortage as a result of increase in population. They used canoes
and makeshift rafts to sail to safety people and property that had been marooned in the
floods. The displaced households were accommodated by relatives and neighbors who
live on higher ground while others sought refuge in temporary flood shelters put up by
the government and NGO‟s at the government district offices, schools and churches.
Others lived in lived in rented motels and apartments.
Photo 4.1: Picture showing a house with a raised floor and a boat on stand by for
evacuation of people and property during extreme flood conditions.
Once the floods subsided the displaced households moved back to their damaged houses.
“Once we move back, we then build a fire from cow dung around or in the front yard of
the house. This helps to keep the ground dry after the flood recedes, providing us with dry
ground where we can cook and keep dry.” Results further indicate that a huge proportion
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59
298(84%), had to repair their homes an average from both risk levels and a quarter
52(23.3%) of household in the high risk areas were forced to build afresh. A mere
11(5%) in the high risk areas were still living in temporary shelters during the survey
period.
Additionally, of the households interviewed, 437(82 %) were reluctant to permanently
move from the flood zones. Among the major reasons given were attachment to ancestral
land, poverty, farms not severely affected and the fact that they had gotten used to living
with the floods. The results are indicated in Table 4.10.
Table 4.10: Reasons for staying in a flood prone area
(Multiple answer response)
Major reasons for staying in flood area
Low Risk
High Risk
Frequency Percent Frequency Percent
Ancestral home
152
59.8
172
70.5
Poverty
66
26
109
44.5
Farm not severely affected
70
27.6
7
2.9
Fear of social set up breaking
13
5.1
12
4.9
Used to living with floods
17
6.7
31
12.7
Accumulated property
7
2.8
18
7.3
Availability of water
3
1.2
8
3.3
4.1.5.2 Coping with food shortage
A huge proportion 246(95%) reported food shortages in the high risk areas while a high
proportion 79.5% were similarly affected in the lower risk areas. Table 4.11 indicates that
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60
main survival strategy to deal with shortage of food was to buy food from the market. In
an attempt to make food stocks last longer, households reduced food taken at meal times
and skipped meals. Some household mentioned giving children priority over adults.
When food stocks ran out households received food and monetary assistance from their
relatives, the Government and the NGOs.
Members of few households looked for alternative employment to supplement income
but because the problem was widespread, opportunities were greatly reduced during the
flood season. It was only in extreme conditions that a mere 2(0.8%) of household in the
high risk areas ate carcasses of livestock that had drowned in the flood waters while a
similar 2(0.8%) resorted to trading their assets for money and food.
Table 4.11: Survival strategies to deal with shortage of food in the study area
(Multiple answer response)
Coping strategy
Bought food
`
Low risk
Frequency Percent
163
83.2
High risk
Frequency
205
Percent
80.4
Reduced food intake per meal
32
16.3
89
34.9
Skipped meals
29
14.8
55
21.6
Assisted by relatives
19
9.7
52
20.4
Children given priority
14
7.1
50
19.6
Looked for alternative employment
17
8.8
9
3.5
Government assistance
5
2.6
15
5.9
NGO assistance
2
1.0
4
1.5
Ate animals that drowned
0
0
2
0.8
Sold livestock and assets
0
0
2
0.8
61
4.1.5.3 Coping with clean water shortage
Results indicate that only 142(26.9%) of the respondent interviewed had access to clean
piped water. This access was however reduced during flooding due to contamination.
Consequent shortage of clean water supply adversely affected about 70.3% and 47.1% of
the households interviewed in the high risk areas and low risk areas respectively. Results
further indicate that households that relied mainly on rivers/streams as their main source
of water experienced the highest proportion 113(88.3%) of water shortage followed by
slightly over half 129(54%) of households whose main water source was wells/boreholes.
A young man explained that “Rivers and streams are also used by animals as their
source of water which has sometimes led to their contamination.”
Table 4.12: Relationship between shortage of water and main water source
Main water source
Communal tap
Well/Borehole
River/stream
Total
Household total
Frequency
142
238
148
528
Percent
26.9
45.1
28
100.0
Shortage within water source
Frequency
45
129
113
Percent
31.5
54.0
88.3
To deal with the water shortages, results in Table 4.13 indicate that about half 91(49.2%)
of households in high risk areas and nearly 36(31.3) in the low risk areas boiled water.
Other strategies included harvesting rain in water tanks, use of water purifying tablets and
borrowing or buying tap water.
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Table 4.13: Survival strategies to deal with shortage of water
(Multiple answer response)
Coping strategy
Boiled drinking water
Low risk area
High risk area
Frequency percentage Frequency percentage
36
31.3
91
49.2
Collected rain water
39
34.2
71
38.6
Used water purifying tablets
32
28.1
59
31.9
Used uncontaminated borehole water
32
28.1
31
16.8
Borrowed/ Bought tap water
15
13.3
37
20
Used flood water (without treating)
8
7.2
12
6.5
A community elder pointed out that in extreme conditions households 20(6.7%) were
forced to drink flood water without boiling because the firewood was too wet to light;
“this kind of water makes the population prone to the water borne diseases since they
drink from the source directly without further treatment.”
Photo 4.3: Picture shows harvesting of rainwater into a water tank; addresses problem
of shortage of clean water and reduces incidences of waterborne disease.
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4.1.5.4 Main source of water in household
The study established that well/boreholes 238(45.1%) followed by rivers/streams 148
(28%) were the major sources of water both for drinking and domestic use. A significant
140(94.6%) of rivers/streams users lived in the high risk areas. Slightly below a quarter
142(24.2 %) had access to communal, piped tap water. Further discussions established
that access to clean piped water was a major problem and further diminished during the
flood season.
Variable
Category
Main source of Communal tap
water
Well/Borehole
River/Stream
Low risk
Frequency Percent
(%)
85
13.4
171
8
32.4
1.5
High risk
Frequency Percent
(%)
57
10.8
67
140
12.7
26.5
4.1.5.5 Health morbidity patterns
In the survey, an average 471(93.8%) of the respondents identified flooding with
prevalence of disease and ill health in their households whilst the rest (6.2%) had no such
incidence. The diseases that the respondents reported to have suffered from are presented
in Table 4.14.
Malaria was the single most widely recorded mosquito-borne disease mentioned by a
huge proportion 434(91.1%), an average of the respondents in both high and low risk
areas. Almost twice as many incidences of cholera, typhoid, dysentery and amoeba were
reported in the high risk areas when compared to the low risk levels. Athlete foot was
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mentioned by an average 40(8.5%) of the respondents in both risk levels. Pneumonia,
vomiting and fever were independently reported by an average 70(14.8%), 52(11) and
84(17.8%) of the interviewees, respectively, from the two risk levels.
Table 4.14: Summary of diseases suffered by respondents during the flood season
(Multiple answer response)
Disease
Malaria
Low risk area
Frequency Percentage
198
90.8
High risk area
Frequency Percentage
236
92.9
Typhoid
28
12.8
74
29.1
Cholera
29
13.2
64
25.2
Dysentery
33
15.1
54
21.3
Fever
22
10.1
62
24.4
Pneumonia
26
11.9
44
17.3
Vomiting
10
4.6
42
16.5
Athlete foot
11
5.0
29
11.4
Skin diseases (Others)
10
4.6
18
7.1
Bilharzia
Amoeba
7
6
3.2
2.5
21
14
8.3
5.5
4.1.5.5.1 Treatment of flood related ailments
A majority 291(62%) of respondents took their sick to government hospitals and health
centres. A common practice noted amongst slightly less than a quarter 98(21%) of the
respondents was self treatment. They acknowledged buying drugs from shops and drug
stores to treat themselves without going to qualified medical officers for proper medical
checkup. A mere 33(7%) were able to afford to take their patients to private hospitals
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while 38(8.1%) made use of traditional medicine. A mere 10(2.1%) of the respondents
mentioned getting treatment from community health care workers during the flood
season. The findings are indicated represented in Figure 4.5.
7%
2%
Government facilities
Drug store
Traditional medicine
Private facilities
CHW
8%
21%
62%
Figure 4.5: Average percentage of health care services sourced by households during the
flood season
According to the District Health officer, the central and local governments had stocked
the government health centers with anti malarial drugs which were being given free of
charge to malaria patients, to complement the governments program of the fight against
malaria. A health and hygiene promotion was being emphasized by Red Cross. The Red
Cross worker informed us that they had just launched an initiative to train community
health workers in avoidance and treatment of flood related ailments. Key information
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elicited included use of clean water, food hygiene, safe sanitation and the use of mosquito
nets to avoid mosquito bites.
The Kenyan government, under the ministry of Health, has also carried out a massive
campaign on the use of mosquito nets. However the nets are only distributed to pregnant
women and children below 5 years of age. With a majority 67% of the population in
Nyando District living below poverty levels, a large segment of the participants
complained that they were not able to afford the nets valued at the market price of Kshs.
500.
4.1.5.6 Injuries and death
Despite serious damage to housing and property, only 22(4.7%) households reported
direct loss of human life. Many of the deaths reported were as a result of drowning
14(82%). The number of deaths reported in high risk areas was 13(93%) and 1(7%) in the
low risk areas. A further 8 deaths were as a result of injuries resulting from walls, roof of
houses and trees collapsing on victims. Interviewees from two households reported death
of one member each as a result of snake bite and the other was killed by hippos. The
results are indicated in Table 4.15.
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Table 4.15: Summary of deaths related to flooding
(Multiple answer response)
Low risk area
Cause of death
High risk area
Frequency
Percent
Frequency
Percent
Drowning
1
20
14
82
Wall collapsed on victim
0
0
2
12
Roof collapsed on victim
1
20
0
0
Trees fell on victim
1
20
1
6
Snake bite
1
20
0
0
Killed by hippo
1
20
0
0
Total
5
100%
17
100%
4.1.5.7 Impact on rural livelihoods
4.1.5.7.1 Agriculture
Results from the analysis indicated that 246(95%) and 213(87%) of the respondents in
high and low risk areas, respectively, had their crop submerged or swept away by floods.
Table 4.14 indicates that the most common response to deal with loss of crop was to wait
for the next season to plant. Replanting immediately would have required adjusting
cropping seasons which depending on the time of the year would invite further damage
from drought or pests.
Households received seed donations from the government or borrowed seeds to plant
from relatives, neighbors and friends. Nearly 33(13.2%) and 14(6.5%) of households
from high and low risk areas, respectively, reduced the magnitude of loss in crops by
planting first maturing crops. Some households switched from growing vegetables and
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maize and instead resorted to planting rice, others opted to rent land on higher ground to
avoid expected future loses while others resorted to other businesses to supplement
income. A mere 2(1.2%) in the high risk areas sold livestock to buy seeds and only 1(1%)
household in both risk levels reported having put aside seeds in anticipation of such a
crisis.
Table 4.16: Coping strategies used to deal with loss of crop in study area
(Multiple answer response)
Coping strategy
Waited for next season to plant
Low risk area
Frequency Percent
161
74.2
High risk area
Frequency Percent
187
74.8
Government donated seeds
26
12
72
28.8
Borrowed seeds to plant from
relatives
Resorted to other businesses
11
5.1
34
13.6
27
12.5
18
7.2
Planted short duration variety of
crops
Rent agricultural land on higher
ground
Switched to growing rice
14
6.5
33
13.2
6
2.8
17
6.8
6
2.8
17
6.8
Sold livestock to buy seeds
0
0
2
1.2
Relied on reserved seeds
1
0.5
1
0.5
4.1.5.7.2 Livestock rearing
A high proportion (209(81%) of households interviewed experienced death of their
poultry and livestock in the high risk areas compared to slightly below half 115(47.7%)
of household in the low risk areas. To cope with loss of pasture the highest percentage of
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households moved their livestock to higher ground while other traveled long distances to
look for fodder for their animals. Other coping actions included replacing what had been
lost, treating livestock and selling weak and vulnerable animals before the onset of
floods. A summary of these results are presented in Table 4.17.
Table 4.17: Coping strategies to handle livestock during the flood season
(Multiple answer response)
Coping strategy
Moved livestock to higher ground.
Low risk area
Frequency Percent
50
43.3
High risk area
Frequency Percent
116
55.4
Traveled long distances to look for
fodder/pasture
Bought and replaced what has been
lost
Spray and de-worm livestock
41
35.3
103
49.3
14
11.6
34
16
12
9.8
32
15
Sold weak and vulnerable livestock
0
0
6
2.8
4.1.5.8 Effectiveness of strategies used to cope with flood risks
Respondents were requested to evaluate the effectiveness of their current coping
strategies. Results from the study indicate that on a Likert scale of 1-4, 1 being most
effective and 4 not effective; a higher proportion 168(63.6%) of respondents in the low
risk areas perceived their responses to be effective as compared to150(56.8)of
respondents in low risk areas. Summary of the findings are indicated in Figure 4.6.
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Figure 4.6: Effectiveness of coping strategies in study area
4.1.5.9 Preparedness to deal with future flood events
The respondents were further asked whether they were prepared for the likelihood of a
future flood event. Results from the study indicate that on a Likert scale of 1-4, 1 being
most very prepared and 4 not prepared at all; slightly less than half 121(45.9%) and
129(48.9%) of respondents in low and high risk areas, respectively, felt prepared to deal
with future flood events. The results are summarized in figure 4.7.
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Figure 4.7: Level of preparedness in the study area
4.1.6 External support
The prevailing emergency relief policy guidelines of Kenyan Government require that
local authority provide basic necessities such as food, shelter and medical care to disaster
victims. In this study,166(62.9%) of respondents in the high risk areas received external
support while a much smaller proportion 98(37.4%) received assistance in the low risk
areas. Government disaster programs accounted for a huge proportion 448(85.2%) of the
support received, while 115(28.1%) of the respondents received help from non
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72
government organizations. A mere 35(6.7%) were assisted by relatives, friends, church
organizations and private donations from well wishers (Figure 4.8).
100
90
80
Percentage (%)
70
Low risk
60
High risk
50
40
30
20
10
0
Government
NGOs
Local
Agencies
Relatives
Private
Donations
Source of relief aid
Figure 4.8: Sources of support received during flood times in the study area
Discussions with key informants revealed that flood management initiatives at the district
are coordinated by the District Disaster Management Committee (DDMC) that has
incorporated all key government departments. The DDMC is represented at the location
and sub location levels. These committees, together with the chiefs and sub chiefs
organize, implement and oversee the food for work program introduced by the
government to engage the community in managing floods. The community members
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dig/clear trenches in exchange for food. Red Cross, VIRED, CREPP, World Vision and
ADRA have been the major non governmental contributors during flood disasters.
Photo 4.4: A woman in Ayweyo receives 2 Kgs. of maize as payment/incentive for
digging/clearing a water channel. This is an initiative of the government, The Food for
Work Program
4.1.6.1 Attitude towards relief aid
Results presented in Figure 4.9 indicate that a high proportion 208(79.1) of the
respondents in both high risk and low risk felt the assistance offered was completely
inadequate
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Figure 4.9: Satisfaction levels with the amount relief aid received
4.1.6.2 Attitude on coping without relief aid
The respondents were further asked to what extent they could survive without external
aid. On a Likert scale of 1-4, 1 being most sufficiently and 4 not survive at all. A larger
proportion 162(61.6%) of respondents in the high risk areas felt they would not be able to
survive without relief aid in the event of a flood disaster as compared to 98(37.1%) in the
low risk areas. The responses are summarized in Figure 4.10.
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Figure 4.10: Perception of coping capabilities in the absence of external support
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4.2 Discussion
4.2.1 Socio-demographic information
Respondents of all ages (18 through to over 60) were represented, with slightly larger
numbers in the lowest age bracket 18-25 and 41-50 categories
accounting for
117(22.1%) and 116(22%) of the respondents, respectively. The oldest age bracket was
60 and above years which accounted for 71(13.5%) of the respondents. The number of
males of males interviewed were fewer, 231 (43.8%) compared to females 297 (56.2%.
This can be attributed to the fact that most male household members were engaged in
out-door work during the survey period.
The mechanism by which marital status affects coping mechanisms remains uncertain in
this study. The findings of this study showed that most of the respondents 353(66.9%)
were
married
and
living
with
their
spouses.
Female
headed
households,
widows/widowers and their children are generally perceived to be more vulnerable to
floods as compared to their counterpart households with both spouses. This could be
explained by the fact that households with both spouses are better financially and
psychological placed and hence able respond to flood risks in a better mental and
emotional state than their single counterparts (SERA Project, 2000; Yamano & Jayne
2002). However this is not necessarily true in all cases as shown by the losses experienced
by majority of the households despite the fact that most of them had both spouses alive at
the time of this study. The results are similar to a study done by Rayhan and Grote,
(undated) in which gender of household head of flooded households in Bangladesh were
found to have no significant effect on vulnerability to flood risks . Analysis revealed no
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significant difference between marital categories and loss experienced in both high and
low risk areas.
The relationship between household resources and flood vulnerability is that coping with
and recovery from flood impacts demands financial reserves that can buffer the
household from negative flood impact (Nethengwe, 2007; SERA Project). The study
findings indicate a high degree of poverty and low incomes reflected in the employment
types where the majority of the people were in the informal sector. Most households were
depending on their farms for a livelihood, which is fairly typical of the general
population, as the area supports a large rural population. The modal gross family income
was below 2,500Kshs which represents 380(70%) of the households. These findings are
consistent with the national statistics that indicate high absolute poverty levels (67%) in
Nyando District, based on the 1999 census (Ministry of Finance and Planning, 2002)
The low-income levels among the study population and especially the females may be
attributed to low levels of education with only 41(13.9%) having gone beyond primary
level. Low education levels are associated with lack of well-remunerated employment
and therefore less social powers and fewer economic resources and physical capacity to
anticipate, survive and recover from the effects of massive floods. Higher family income
is of relatively greater benefit and often accompanied by a rise in expenditure on
preparation and protection strategies (Few et al., 2004).
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A larger proportion 71(29%) of the women had no formal education as compared to
13(5%) of their male counterparts. Further results showed that 77.5% of female income
per month fell in the <2500 category and they therefore had to depend on their spouses or
relatives for a livelihood. These circumstances have been found to affect the women‟s
ability to respond appropriately to flood hazards as well as their capacity to participate in
flood management at both household and community levels (Wiest et al., 1994; Few et
al., 2004; Bhatta, 2008).
4.2.2 Traditional knowledge on flood forecasting
Traditional knowledge on flood forecasting and early flood disaster management had
enabled communities, particularly those living in flood prone areas to adopt and live with
extreme weather conditions for generations (UNEP, 2008). In the study, 482(83%) of the
respondents were aware of local ways of knowing whether it would flood or not and
465(80%) of these respondents acknowledged the use of the traditional knowledge These
results demonstrated that traditional strategies were considered a trusted source of
information and importance to this community.
Results from the study further indicated a significant difference between level of
awareness of traditional knowledge in the high and low risk areas (χ2=; 11.526 df =1;
p=.001) with a considerably larger proportion of respondents in the high risk areas being
more aware of traditional flood knowledge than those residing in the low risk areas. The
most likely explanation for the difference is flood experience. This supported
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observations by Jinchi, (2003) who concluded that people‟s level of flood experience and
their place of residence had an important impact on levels of flood awareness.
Discussions from the focus groups further revealed that majority of the young people and
those engaged in off-farm or non-farm activities did not feel confident about sharing
traditional knowledge. The reasons given were that the opportunity to learn from the
elderly was gradually becoming rare and they had not spent sufficient time in the field to
develop accurate forecasts. Interestingly, this did not seem to bother them.
These
findings match those of study carried out by Eyob, (1999) in Eritrea in which most
young respondents interviewed associated indigenous knowledge with low prestige rural
life; believing it to be inferior.
It is generally accepted that traditional flood knowledge is in many cases preserved as an
oral tradition and is passed on by word of mouth (UN/ISDR, 2008). The study findings
contradicted this as only 163(38%) of the respondents received this information from
their elders. A huge proportion 357(73.8%) reported getting flood information mainly
through personal observation. This might be attributed to the processes of urbanization,
development and formal education contributing to the decreasing traditional practice of
passing on of early warning strategies by word of mouth.
4.2.2.1 Influence of demographics on awareness and use of traditional knowledge
The results in the study revealed the converge side to age and length of residency and that
was the benefit of experience. The association between these two demographic variables
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and awareness and use of traditional flood knowledge were found to be significant in
both high and low risk areas. The highest proportion of respondents with traditional flood
knowledge were in the 33 plus age groups and had lived in the area for more than 4 years
This could derive from a life spent in flood prone areas and the greater chance that older
people have more flood experience. The results are similar to those of a survey carried
out on flood victims of the 2002 Melde Flood in Eilenburgh (Kuhlicke, 2002) in which
respondents with extensive local flood knowledge were those who had lived in the area
for a long time and had experienced major floods in 1954 and 1974.
Occupation wise, farmers were more aware of traditional flood knowledge than the rest
of the categories. The difference in awareness of the information within the occupation
categories was found to be significant in both high (χ 2=; 47.309 df =21; p=.001) and low
risk areas (χ2=; 40.866 df =21; p=.001). These results imply that people whose
livelihoods are directly affected by flooding have more use for the local flood knowledge
which they apply to minimize loss. These results concur with those of a study done on
indigenous responses to flooding in Bangladesh (ITDG-B, 2001) in which a significant
number of the responses related to agricultural coping measures. The majority of
households engaged in crop production suffered loss of standing crops and loss of
employment during the period.
4.2.3 Perception of flood risks to public health
General findings from the study revealed that the degree of perceived risk of flood threats
to health was significantly higher among the respondents living in the high risk areas
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compared to those in the low risk areas. The demonstrated difference in perceptions is
undoubtedly attributable to the level of awareness of risk and the degree of exposure to
the health hazards. A similar perception of flooding described by Ockzyk (2004): flood
plain inhabitants generally perceive a risk from flooding only to the extent or magnitude
that they have previously experienced, thus leaving themselves vulnerable in the event of
a larger flood. Slovic et al., (1979) concluded that the memorability of past events play an
important role in the determination of how individuals will perceive and react to future
flood.
Results from this study also indicated that for this community, the advantages of their
location--close to the river with easy access to fertile land, water, and strong community
ties-far outweighed the health risks associated with flooding. Although flooding was
viewed as a recurring problem, the fact that the study established that a large segment of
the people interviewed 437(82.8%) were reluctant to permanently vacate their flood
prone land reinforces the fact that flooding is not perceived as a serious threat in the area.
These findings are similar to those of a study carried out in Tanzania (Gaston,
unpublished) which revealed that pressure to live in flood-prone areas, which typically
are surrounded by rich alluvial soils, abundant water supplies is on the increase as the
country‟s population increases. Similarly, following the 2000 Mozambique floods, where
livelihood of people depended on the flood plain, government action to relocate
vulnerable populations was met with a lot of resistance as the affected population moved
location but maintained temporary housing in the flood plains and eventually moved
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back. The people feared leaving and potentially losing their possessions or their property
claim. (Rojas, 1997; Few et al, 2004).
This implies that for this community, health is a luxury they cannot afford because their
immediate economic survival is at stake. The problem is often not simply a lack of
awareness, but rather, assessments of local risk based on experience that underestimates
the impact of accumulating risk (Few et al., 2005).
4.2.3.1 Perception on methods of managing flood risks
Despite the recurrent nature of the hazard, results showed that flood events were
perceived to be inevitable and fairly unpredictable especially in the high risk areas,
limiting scope for action and response. This might indicate the nature of flash floods and
lack of possibilities to prepare for the hazard. It could also point to increased
vulnerability that could be attributed to climate change thereby reducing the community‟s
ability to precisely predict and warn future flood events (Salick et al., 2007; Macchi et
al., 2008). Historical trends have allowed for reasonable predications of future weather
patterns. However, the increasing severity and frequency of floods over the last decade
have rendered this latter form of forecasting less reliable than it has been in the past. In a
number of studies conducted on climate change (Vordzorgbe, 2007; Few et al., 2007,
IPCC, 2007; Macchi et al., 2008;) climate experts confirm that intensity of flood events
has increased, especially around the Lake Victoria Region.
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Regarding floods control measures, flood preventive measures were elected as a priority
in both high and low risk areas. A relatively surprising outcome was the fact that in both
surveyed areas flood risk was perceived to be controllable with structural measures. This
was perceived to require huge investments to implement. When asked directly, most
respondents mentioned the dyke currently under construction to be the main reason
incidences of flooding had reduced in the area. These results displayed a growing belief
and dependency on the technical approach. This was noteworthy as a number of studies
on risk perception (Linnerooth-Bayer, 2002; Ikeda, 2003; APFM, (2006) had indicated
that an excess of confidence on the structural alternative performance in reducing flood
frequency may bias the decision-making process and eventually lead to an inadequate
occupation of flood prone areas, increasing flooding potential impacts in case of
structural failures. This suggested that it was not practical to reduce flood disasters only
by structural measures under the concept of need to control, because it had physical and
financial limitations.
Despite these findings, the need to attribute disasters to some supernatural was obviously
still felt by a substantial 129(24%). Bhutta (1999) and Bhatti, (2005) shed more light on
these views by stating that there are multiple interpretations of risks and disasters, yet the
divine element is dominant. People do recognize other tangible and structural factors
involved in disaster and relating disaster to natural forces is not just a religious expression
rather it reflects the social meanings of harm happening in certain time and space
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4.2.3.2 Demographic influences on perception of flood risks
Differences in occupation categories indicated that small and large scale farmers
perceived significantly higher levels of threat than the other occupation categories. This
could be as a result of huge losses being incurred directly affecting their livelihoods
4.2.4 Behavior associated with flood management
A considerably high percentage of respondents reported damage to their shelter in both
high and low risk areas. Traditionally, Luo houses are built from mud and thatch. These
are susceptible to damage by heavy rain, wind and flooding. The respondents seemed to
understand the dangers of using these housing materials but only few (considered rich)
could afford to build concrete houses with cemented walls.
To prevent flood waters entering their homes, it was observed that all homesteads had
houses built on raised lands or earthen platforms. The walls and entrances were elevated
so flood water could not reach the plinth. To protect their homes and farms, a huge
majority dug trenches around their compounds and planted trees and sisal fences around
the homesteads to break/reduce the flow of flood waters and to prevent erosion. These
results depict other studies of a similar kind done in flood prone locations (Del Ninno et
al., 2001; Few et al, 2005) in which housing techniques were adapted according to the
risk posed by floods and erosion.
Further findings showed that during extreme flood events, families affected vacated their
homes and moved to camps or were accommodated by relatives and friends. The study
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established that those who were accommodated in the temporary flood shelters put up by
the government and NGO‟S got the most assistance whereas the majority of those
accommodated by neighbors and relatives receive little assistance as coordinating widely
scattered households is usually difficult. After a few days away from their flooded
houses, displaced families always moved back to their homes. Gaston (unpublished) in
his study on flood risk management in Tanzania reported that flood victims always
moved back to their damaged houses and their safety remained a concern because the
structural stability of the houses were unknown. There was also the likelihood of
contracting diseases due to lingering stagnant water.
Respondents reported food and water shortages during the flood season. The study
indicated that the households had to borrow money and food in order to survive through
the flood season. Most people borrowed money from informal sources like relatives,
neighbors and friends. Quite a good number of households looked for alternative
employment to substitute income. In extreme conditions some households traded their
assets for money and food. Borrowing and selling of assets by families in distress are
coping actions that have been mentioned in findings of other researches (Jahan, 2000;
Few et al., 2004; Sharma, 2000).
Specific health risks related to flooding were reported by a huge majority of respondents
in both high and low risk areas. Malaria was the most commonly mentioned flood related
disease. Even though it was endemic in the region it was reported to be more prevalent
during and immediately after the flood season. The mosquito-borne disease could be
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related to favorable breeding conditions for mosquito larvae created by stagnant flood
waters.
Interviewees strongly associated flooding with increased incidences of cholera, typhoid,
dysentery, amoeba and fungal skin disease. The district public health officer claimed few
cases of cholera had been reported in the district but in the study it was ranked second
after malaria. It was observed that almost all households had shallow and temporary pit
latrines that easily fill up during the rainy season. This is the most probable way the
diarrheal diseases spread since the feces could easily have found their way in to water
sources such as wells, unprotected springs and rivers. Fungal skin disease; in particular
athlete foot could be associated with respondents being constantly in contact with flood
waters when performing domestic chores. This results are similar to those of Mungai et
al., (2004) in which Malaria epidemics was found to occur annually between May and
July in Nandi and Kericho upper parts of Nyando river basin after long rains with the
only exception being during the 1997/98 El Nino phenomenon which occurred during
end of 1997 and early 1998, and was followed by malaria epidemic. An upsurge in water
borne diseases like diarrhoea that normally coincides with flooding in the lower part of
Nyando river basin was also noted.
An issue that came up during the interview process was that conditions like vomiting and
fever were independently reported. Discussions with the district public health officer
confirmed to us that many people could not identify the difference between symptoms of
common ailments. These results were similar to those of a study carried out by Few et.
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al., (2005) in Vietnam in which respondents were not able to tell the difference between
dengue fever and other common fevers.
To deal with the diseases, respondents made use of both traditional and modern medicine.
A good number of respondents acknowledged buying drugs from shops and drug stores
to treat themselves without testing what they were suffering from. It was only when a
member of the household was gravely ill that appropriate medical care was sought. This
behavior is consistent with findings of Few et al., (2005) in Vietnam and can be
attributed to low levels of education.
Despite serious damage to housing and property, few households reported direct loss of
human life. Many of the deaths reported were as a result of drowning and injuries
resulting from walls, roof of houses and trees collapsing on the victims. Most of these
deaths were blamed on flash floods.
4.2.4.1 Preparedness and effectiveness of coping action
Generally speaking, neither respondents from the two risk levels displayed high levels of
preparedness. There were several reasons why the respondents may have been unwilling
to prepare for disasters. One reason was the dyke under construction. This was a highly
visible measure that may have generated perceptions of a flood free area and may have
largely contributed to reduced motivation to prepare. Another postulated reason was that
an individual‟s expectation of damaging disaster does not necessarily lead to
preparedness suggesting that the sense of being at risk does not in itself move people to
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action (Turner et al.,1986). In a similar study, Kaiser et al., (2004) indicated that no
correlation existed among personal experience and precautionary actions and that
knowledge about the risk does not automatically imply knowledge about the
consequences and precautionary actions as e.g. 90% of the persons estimated the
probability of a storm flood as very high, had not taken any personal preventive
measures.
Vulnerable people individually and collectively develop their own means, resources and
strategies to cope with flooding. All of these mechanisms, however, have financial, social
and/or opportunity implications (ISDR, 2004). A review of a preparedness program in
Bangladesh showed that vulnerable people had little or no surplus income to invest in the
measures that could protect them from flooding although they knew what to do (Alam et
al., 2007b cited in Pro Vention, 2008). To some extent results in Nyando followed the
same trend with slightly higher percentage of respondents in the low risk areas reporting
their coping actions to be more effective as compared to those in the high risk areas. Low
income levels and repeated destruction of assets, which function as a buffer, may have
compromised the ability to respond appropriately to subsequent floods. The frequency of
climate shocks exacerbates the fragility of poor people‟s assets and thus further
compromises recovery (Fuente, 2008).
Findings from the study further indicated a highly significant association between
preparedness and level of effectiveness of coping action in both low and high risk levels
at (χ252.822; df =9; p= .0001) and (χ231.833; df =9; p=.0001), respectively. The practical
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implication of these findings is that preparedness raises participant‟s levels of confidence
in their ability to cope with flood risks.
4.2.4.2 Demographic influences on preparation and effectiveness of coping action
It is generally accepted that there is a decreasing perception of hazard with age. The
explanations for this are that older people may consider themselves less vulnerable due to
their increased experience (Beringer, 2000). Alternatively, elderly residents are often
more sceptical about the danger and thus more likely to discount the risk (Mileti et al,
1975). To a certain extent the results for Nyando District did follow this trend with
respondents in the 40plus age categorise reporting significantly lower levels of
preparedness as compared to the younger age groups. Additionally, the 60plus age group
had the lowest percentage of those who felt their coping actions were effective.
Gender wise, the women reported considerably lower levels of preparedness 119(40%) as
compared to their male counterparts 127(55%). These findings are similar to those of a
study carried out in Pine Lake, Alberta area, Ontario (Murphy et al. 2005) in which men
appeared to dominate both outdoor and indoor preparedness. This could be attributed to
low income and education levels that may have reduced the women‟s coping choices.
The same would be implied for the income category in which respondents with incomes
in the 10,000+ categories reported being better prepared and their coping actions more
effective as compared to respondents in lower income levels.
These results also confirm findings of other studies (UNDP, 2007; Mitchell et al., 2007)
which indicate that although climate change affects everyone, it is not gender neutral.
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Climate change magnifies existing inequalities, reinforcing the disparity between women
and men in their vulnerability to and capability to cope with climate change. Studies by
Enarson, (2000) and O’Brien, (2007) have highlighted the fact that natural disasters could
also provide women with a unique opportunity to challenge and change their gendered
status in society. Women have been willing and able to take an active role in what are
traditionally considered ‘male’ tasks in responding to disasters, e.g. following Hurricane
Mitch in Guatemala and Honduras in 1998 (Schrader and Delaney, 2000).
It was interesting to note that respondents who had more education levels reported less
effectiveness of their coping action as compared to people with less education levels.
This could be due to lack of appreciation of local coping strategies. According to Faupel
and Styles, (1993) an explanation for this could be that education raises participant‟s
levels of expectations regarding what they should have been able to accomplish.
4.2.4 External Support
Respondents living in the high risk areas received nearly twice as much external support
compared to those living in the low risk areas. Despite receiving relief support majority
of the respondents in both high and low risk areas felt the aid was insufficient and
inappropriately (corruptly) handled and distributed. They were therefore forced to resort
back to household level adjustments to compensate for damages caused by the floods. A
study carried out in Krishna District West, Bengal by Nayak, 2007) described a similar
circumstance in which people were anxious to get relief material but there were lots of
complaints from the people that relief material had not so far reached them. In this
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91
particular case, the media was at the same time giving reports on the malpractices in
weighing the relief material, which was being supplied to the affected people.
One of the major concerns was the extent to which respondents were able to cope without
external aid. Findings from the study revealed that majority of the respondents living in
the high risk areas felt they would not be able to cope with future floods in the absence of
external support. Study findings further revealed that length of residency was the only
demographic variable that was found to be highly significantly associated with attitude of
the respondents towards external support in the high risk areas (χ2= 69.096; df =24;
p=0.001). Confidence in ability to survive without external aid increased as the length of
residency increased. A key issue emerging was the extent to which relief measures and
programs were able to strengthen the resilience of the communities to floods.
Findings from the study revealed that most relief agencies were offering emergency
supplies, but were reluctant to invest in pre-disaster and post-disaster phases. The main
explanation for this was lack of funding for long term projects. Key informants also felt
the government sponsored food for work program was creating a dependency syndrome.
Activities that were previously undertaken by community members on voluntarily basis
were now being performed in exchange for food. When food supplies delayed or ran out,
the people refused to continue working. Similar results were reported in a study carried
out by Wilk and Kgathi, (2008) in the Okavango Delta, Botswana in which heavy
reliance on government assistance increased especially among female-headed households
and high-risk households in the face of recurring flood regimes
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CHAPTER V: SUMMARY, CONCLUSION AND RECOMMENDATIONS
5.1 Major findings of the study
5.1.1 Demographic and socio-economic characteristics
Respondents of all ages (18 through to over 60) were represented in the survey. From the
findings of the study, the main occupation of most households was subsistent farming.
Incomes were generally low among the respondent as employment patterns among the
respondents showed only a small minority of them as wage earners. These low-income
could be attributed to low levels of education with only a quarter of the respondents
having gone beyond primary level.
5.1.2 Traditional knowledge on flood forecasting
Results of the study demonstrated that traditional flood knowledge does exist in the study
area and these traditional strategies are a trusted source of information and importance to
this community. Flood prediction was based on knowledge of weather pattern,
observation of changes in animal and insect activities, changes in the weather pattern,
river levels and flood cycles. Ancestral knowledge was regarded as playing a minimum
role since most respondents claimed they acquired their knowledge within their lifetime.
5.1.3 Existing perceptions of impact and management of flood risks
General findings from the study revealed that public health risks evoked significantly
higher degrees of anxiety in the high risk areas compared to the low risk areas. This was
attributed to the level of exposure to flood related health risks. Damage to shelter and
food insecurity were perceived to be the greatest flood related health risks. This flood
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93
related risks were perceived to be controllable with structural measures. This would
require huge investments to implement.
Despite the health risks, an overwhelming majority were still reluctant to permanently
vacate the area because they predominantly felt that the advantages of living there
outweighed the risks involved. To the area residents, health is a luxury they cannot afford
because their immediate economic survival is at stake. This implies that for this
community, the problem is often not simply a lack of awareness, but rather an assessment
of risk is based on the experience of having survived previous flood disasters that
underestimates future risks.
5.1.4 Response behavior towards health risks
Local coping strategies had both dimensions: innovative adjustability and passive
acceptability of potential hazards. Most of these indigenous actions were taken at the
household level to adapt to the health risks posed by floods. At the community level,
technical and engineering preparedness such as construction of dykes were seen to
dominate the mitigation approach. Given the financial limitations of the Kenyan
Government in completing structural measures, focus was mainly on small scale
mitigation efforts. It was noted that most local-level-collective response, even if
classified as community effort was officially organized by the central government for
example, digging and clearing of trenches and sandbagging weak points along the river
banks. The current food for work initiative was put in place by the government to support
these ventures.
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94
In terms of assessing individual ability to control the hazardous situation, respondents
from the two risk levels did not display high levels of preparedness. As a result, more
respondents in the low risk areas reported their coping actions to be more effective as
compared to those in the high risk areas. Women reported considerably lower levels of
preparedness as compared to their male counterparts while low income earners, elderly
respondents and those in the secondary-plus education categories reported less
effectiveness of their coping action compared to the other categories.
5.1.5 Attitude towards external support
Despite receiving some external support, respondents in both high risk and low risk felt
the assistance offered was completely inadequate and most of the community members
had to resort back to household level adjustments to compensate for damages caused by
the floods. Respondents who received relief aid indicated significantly higher levels of
dependency on external support compared to those who did not receive external
assistance. The dependency syndrome was seen to be created by relief agencies which
were offering emergency supplies, but were reluctant to invest in pre-disaster and postdisaster phases. Key informants felt the government sponsored food for work program
was also responsible for creating the dependency syndrome.
5.2 Conclusion
From the above summary, the following can be concluded from this study:

Significant distinctions could be drawn between the high and low risk areas.
Residents in the high risk areas had significantly higher levels of awareness and
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use of traditional knowledge. They were more aware of the nature of flood related
health risks they were exposed to and appeared better prepared for future flood
risk but were more dependent on external aid. On the other hand residents living
in the low risk area reported better success with their response mechanisms. The
demonstrated differences were undoubtedly attributable the degree of exposure to
the health hazards and socio demographic influences.

The burden of diseases was significantly higher during the flood season but the
advantages of living in a flood plain seem to outweigh the health risks associated
with flooding. The result is a combination of innovative adjustability and passive
acceptability of potential hazards. Most of these indigenous actions were taken at
the household level to adapt to the health risks posed by floods. Perception of risk
was based on the experience of having survived previous flood disasters an excess
of confidence on structural measures thereby underestimating the impact of
accumulating risk. This appeared to bias the decision-making process.

Based on these findings, the study failed to accept the null hypothesis that the
level of exposure to risk does not influence traditional knowledge, perceptions of
flood risks, response mechanisms and attitude towards external support of
Nyando communities. There was evidence from these results to conclude that
level of exposure to risk does have an influence on awareness and use of
traditional knowledge, perceptions of flood risks, response mechanisms and
attitude towards external support of the Nyando communities.

This study was envisaged to benefit the following groups of people: rural
communities living in flood prone areas, disaster managers, policy makers,
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96
researchers and scholars, and funding agencies. The potential utility of the project
was to reduce vulnerability; to strengthen capacity of the affected communities to
respond more effectively to flood emergencies and to provide insights into
possibility of a more integrated approach to flood prevention and coping with
loss.
5.3 Recommendations for implementation
The following are recommendations for future planning and implementation:

Existing traditional knowledge is largely underutilized in the current flood
management strategies. The Kenya Government Disaster Management Unit
should promote the use of traditional flood knowledge to boost preparedness at
the local levels. It should also be noted that traditional knowledge on flood
forecasting cannot function independently; it needs to be supported by official
flood warning methods and a wider range of support and flood risk management
measures.

The Nyando community needs to shift from the current perceptions and
preference for 'hard' defenses that are costly to implement. They should also
embrace non-structural measures that are low cost, have low maintenance
requirements and are ultimately more sustainable i.e Flood warnings should
include more information about possible protection measures. In addition,
different information leaflets could be distributed with flood mitigation options
for specific groups of people, e.g. elderly people or households with children.
This, however, does not necessarily diminish the importance of structural
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97
measures; rather it points to the necessity of combining structural and nonstructural measures in a way that minimizes loss and achieves the best results.

There is need to Strengthen the capacity of extension services like Community
Health Workers (CHWs) who can be easily accessed by the community during the
flood season. The Ministry of Health should train CHW‟s on environmental
sanitation. During the flood season, they should be supplied with enough
medicine for flood-related illness and water treatment products.

The Ministry of Water should extend clean water and sanitation services to all
households and to ensure a constant supply of clean water during the flood
season. Alongside these services, the Ministry should also educate the community
members on the key importance of good environmental health. This will help
keep to a minimum outbreak of waterborne diseases.

The Government, NGO‟s and CBO‟s in dealing with disaster management in
Nyando District are currently focused on either emergency health preparedness or
post emergency relief. There is need for them to shift their mindsets from reaction
and charity to anticipation and preemption.

The study highlights social differentiation in perception of risks and socio-cultural
and economic factors as barriers to effective coping and take-up of interventions.
This draws attention to the need for flood warning activities to be tailored to local
social contexts.

Potential for climate change to intensify or alter flood patterns means that it is
likely to become a major additional driver of future health risk from flooding in
Nyando District. There is need for the Government Disaster Management Unit,
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98
NGO‟s, and CBO‟S managing flood disasters to educate the Nyando communities
on the global climate trends and see how local coping capacities can be improved
to prepare the communities for future flood events.
5.5 Recommendations for further research:

Gender dimensions of vulnerability to flood hazards in areas severely affected
by HIV/AIDS.
`

Community insurance to and property security in flood prone areas.

Community –based risk communication and advocacy strategies.
99
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`
110
APPENDIX I
Map showing high and low flood risk areas sampled during the study in Nyando and
where Nyando is Located in Kenya
`
111
APPENDIX 11: HOUSEHOLD QUESTIONNAIRE
Instruction to interviewer






Thank the interviewee for agreeing to be interviewed.
Share with him/her that the following information will be used to improve and
strengthen programmes on flood management in Nyando – his /her observations
are therefore very important.
Reassure him/her that all responses will be kept private and confidential.
Let him/her know that we appreciate all comments on these questions.
Encourage the interviewees to ask any questions they may have, at any time
during the interview or after its completion.
After completing the interview, thank the interviewee once again for cooperating
and for taking time to respond.
IDENTIFICATION
SUB-LOCATION:
__________________________________________
DATE OF INTERVIEW
__________________________________________
TIME OF INTERVIEW: START AT _______________ END AT _____________
Introduction
My name is Hellen Nyakundi. I am a Master of Public Health and Epidemiology student at
Kenyatta University currently conducting research on the above topic. Flooding along the Nyando
River affects many people in Nyando District and as part of a thesis project to meet academic
requirements I am researching Nyando District residents‟ perceptions and response to this
perennial hazard. This study seeks to understand the strengths of community flood hazard/risk
management strategies. Your household has been randomly selected to participate in this
confidential survey and your name and address will not be disclosed. Your response to this survey
is very important, as it will provide valuable information about flooding in your community. I
will request 30 minutes of your time to ask you a few questions to enable me complete the
questionnaire. I want to assure you that your answers and opinions will be treated in the strictest of
confidence.
Would you like to participate?
Yes………….. > Continue
No…………... > Terminate and thank respondent
`
112
1) Questionnaire identification number (For official use only)
001

I Demographics (Please complete this part fully)
002 Age
003 Gender
004 Marital status
005 Main occupation
006 Classification of
earning per month
a.
b.
c.
d.
e.
f.

26-32

33-40

40-50

50-60

60 –above 
18-25

Female 
a. Male
b.
a. Married

b. Single

c. Divorced

d. Separated

e. Widow

Other (specify
f.

Farmer (large scale) 
Business person

House wife

Student

Professional worker 
Skilled artisan

Jobless

a. Farmer (subsistence)
b.
c.
d.
e.
f.
g.
h.

______________
007 Level of education
008 House hold
009 Roof type
wall
structure
a.
No formal education
b.
Primary incomplete
c.


Primary complete

d.
Secondary incomplete
e.
Secondary complete
f.
Post secondary incomplete
g.
Post secondary complete




`
0010
Main
water source
1. Mud

1. Iron sheets

1. tap

2 .Timber

2. Grass

2. communal tap

3. well/borehole

3. Cement/t/
/bricks/stone


4. Other (specify)
3. Thatched/Makuti

a.
Less than 2,500

b.
2,501-5,000

c.
5,001-10,000

d.
10,001-20,000

e.
20,000-30,000

f.
30,001-40,000

g.
40,001 and above

0011
Length
of residency
a. 1 yrs
b. 2 yrs
c. 3 yrs
d. 4-6 yrs
e. 6-10 yrs
4. Tiles/Asbestos
5. Other (specify)


4. river/stream
5. other (specify)


f.
10-20 yrs
g. 20-above







113
1.
How often do you think about floods?
a.
Always
b.
Often
c.
Not often
d.
Never
0012




2
What are the effects of flooding?
`

a.
Damage of physical structures
b.
Damage to crops and food supplies
c.
Damage to livestock
d.
Contamination of water supplies
e.
Causalities and Loss of life
f.
Epidemics
g.
Famine
h.
Disruption of schooling
i.
Transport disrupted
j.
Communication is disrupted
k.
Other











0013

114
3
What are the factors that contribute to these flood disasters in your area?
a.
b.
c.
d.
e.
f.
g.
h.
i.
j.
0014

Transition in cultural practices

Rapid urbanization

Poverty

Population growth

Environmental degradation

Location of settlement on flood plain

Non resistant buildings and foundation

Unprotected food stocks, standing crops and livestock. 
Other

Lack of awareness and information
What are the most common ways of avoiding negative effects flood risks?
4
0015
(Preparation)
a. Dig/ clear trenches
b. Raise floor of houses
c. Pile mud around homestead
d. Seal lower door entrance with mud
e. Build dykes
f.
Plant trees/sisal
g. Other
`









115
5
What are the most common ways of dealing with floods?
a. Evacuate to higher ground
b. Dig trenches
c. Rely on Government/NGO aid
d. Raise what can be destroyed
e. Buy food from the market
f.
Wait for another season to plant
g. Remove excess water from the house
h. Treat/Boil drinking water
i.
Rebuild/buy what has been destroyed
j.
Other
0016










6
Please rate the following assumed flood characteristics on a scale rate of 1-4
(1. Low 2. Medium 3. High 4. Not sure)
1.
2.
3.
4.
5.
6.
7.
8.
`
Low threat
Certain not fatal
Old risk
Evokes no anxiety
Influence possible
Happens seldom
Predictable
Decrease in future
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3

4
4
4
4
4
4
4
4
high threat
very fatal
new risk
evokes anxiety
influence impossible
happens often
not predictable
increase in future
0017

116
7
I am now going to read out the following statements and would like you to
tell me to what extent you agree or disagree with them.
0018

1. Strongly agree, 2. Agree, 3. Not sure, 4. Disagree, 5. Strongly disagree
a. Flooding is inevitable and cannot be prevented
b. Flood hazard could be reduced by man-made structures
c. Huge investments is needed to reduce flood hazards
d. Flood preventive measures are more important than emergency
relief and rehabilitation work.
e. The state should establish financial reserves to help victims
f.
People are capable of controlling the occurrence of floods
g. Modern technology is the best way to solve flooding problems.
h. floods are a natural phenomena or „acts of God








HOUSEHOLD BEHAVIOR DURING THE MOST RECENT FLOODS
Have you experienced floods in your life time?
8
a.
Yes
b.
No


0019
(if yes, proceed to question below)
(if no, proceed to question?)
9
Which year did you experience the most recent floods?

`

0020

117
10
Did your family experience any damage to shelter
a.
b.

No 
0021
Yes
(if yes, proceed to question below)
11
How did you deal with the damage?
a. Build afresh
b. Compact soft parts with mud
c. Evacuate to higher ground
d. Build temporary shelters
e. Other
0022
Did your family experience loss of crops in the field?
a.
Yes
b.
No








12
`

(if yes, proceed to question below)
0023

118
13
0024
How did you cope with the loss?
a. Waited for next season to plant
b. Rented land on higher ground
c. Started growing rice
d. Planted fast maturing crops (which one) indigenous crop?
e. Bought food from the market
f.
Sought assistance from relatives
g. Relied on Government/NGO aid
h. Resorted to other businesses
i.
Other









14
Did your family experience loss of livestock?
a. Yes
b. No


0025
What type of livestock did you loose?
Animal
b. Goats
c. Sheep
d. Poultry
e. Pigs
f.
Donkeys
g. Other
`

(if yes, proceed to question below)
15
a. Cows

Number Lost (indicate)














0026

119
16
How did you cope with the loss?
a. Bought and replaced what has been lost
b. Reported loss to the chief
c. Sold vulnerable stock before floods
d. Treated livestock-sprayed and de-wormed
e. No action taken
f.
Other
0027






17
Did your family experience any shortage of food during the floods?
a. Yes
b. No
c.


0028
If yes, how did you deal with the shortage?
a. Bought food from the market
b. Reduced intake of food
c. Skipped meals
d. Was assisted by relatives
e. Children given priority
`
Other

(if yes, proceed to question below)
18
f.







0029

120
19
Did your family experience shortage of clean water during the 0030

floods?
a. Yes
b. No


(if yes, proceed to question below)
20
If yes, how did you deal with the shortage?
a. Boil drinking water
b. Collected rain water
c. Used tap water
d. Started using chlorine and water guard
e. Used borehole water
f.
Other
0031






21
Did your family experience any diseases that were more prevalent
during the flood times?
a. Yes
b. No
`



(if yes, proceed to question below)
0032

121
22
0033
If yes, what diseases?
a. Cholera
c. Typhoid
e. Athlete foot
g. Bilharzia
i. Fever
k. Amoeba






b. Malaria
d. Dysentery
f. Vomiting
h. Foot and mouth disease
j. Pneumonia
l. Other






23
0034
How did you deal with the diseases?
a. Took the sick to Government dispensaries/hospitals
b. Took the sick to private clinics/ hospitals
c. Bought drugs from the store
d. Used traditional medicine
e. Used mosquito nets
f.
`
Other








122
24
Was there any death in the family that can be attributed to the
floods?
a. Yes
b. No


0035

(if yes, proceed to question below)
25
If yes, what caused the death and how many members of the
0036

family did you loose?
a.
One member
b.
Two members
c.
Three members
d.
Other




Cause of death ---------------------------
26
Was schooling interrupted during the floods?
a. Yes
b. No


0037
(if yes, proceed to question below)
27
How did you deal with the situation?
a. Schools were closed
b. Children stayed at home
c. Children went to school during holidays
d. Bought gumboots for children
e. Community cleared the path off debris
f.
`
Other







0038

123
28
Generally, how effective is your household response in dealing with
0039

negative flood effects
a.
Very effective
b.
Somewhat effective
c.
Not effective
d.
Don‟t now/Not sure




29
0040
How can your responses be improved?
a.
Government assistance
b.
Community education on how to live with floods
c.
Work harder to replace what is lost
d.
Government dispensaries to be improved
e.
Introduction of mobile clinics
f.
Store food reserves
g.
More community initiatives
h.
Plant trees
i.
Plant more crops
j.
Other
30










Do you expect that you will experience flooding this year?
`
a.
Extremely likely
b.
Very likely
c.
Neutral (50/50)
d.
Extremely unlikely





0041

124
31
Are you prepared for the likelihood of a future flood?
a. Very prepared
b. Somewhat prepared
c. Not very prepared
d. Not prepared at all
0042




32
What plans do you have to deal with future floods?
a. Evacuate when floods come
b. Relocate to different area
c. Rent land on higher ground
d. Dig trenches
e. Pile mud around the homestead
f.
Raise foundation of the house
g. Digging dykes
h. Store food
i.
Plant more rice
j.
Plant trees
k. Other
0043
How likely is it that you will continue staying in this area in the next
5 years?

Probably stay

Definitely not stay 
Don‟t know

b.
c.
d.
`












33
a. Definitely stay

0044

125
34
0045
If yes, why would you continue to live in flood prone area?
a. Poverty
b. Accumulated property
c. Farm not severely affected
d. Ancestral home
e. Fear of social set up breaking
f.
Availability of water
g. Used to living with floods
h. Other









TRADITIONAL KNOWLEDGE AND FORECASTING
35
When do you first become aware of the possibility of flooding?
a. Official flood warning
b. Unofficial or informal flood detection and warning process
c. Form own judgment
d. Don‟t know/not sure
e. Other
0046





36
Do you have local ways of knowing whether or not it will flood?

No 
a. Yes
b.
`
(if yes, proceed to question below)

0047

126
37
Which traditional knowledge do you have that warns you of the
0048

likelihood of flooding?

When the river levels start increasing

Heavy rains in Kericho and the Nandi Hills

Strong winds blowing from the river towards the Hills

When it shines for long& temperatures are higher than normal
Certain movement and chirping of the cow egret

Heavy rainfall in the area over long period of time

Thunder and lightning on the river

Certain way the frogs croak

When noise level of the river increases

When river water turns dirty brown

Other

a. When the old people bone‟s start to ache
b.
c.
d.
e.
f.
g.
h.
i.
j.
k.
l.
38
Where does the above information come from?
a. From old people
b. Relatives
c. Friends
d. Own judgement
e. Observing the rain pattern
f.
Observing river level
g. Don‟t know
h. Other
`




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0049
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39
Would you please rate how the following are useful as sources of
information?
0050

Most useful Adequate Inadequate Not useful
a. Friends/family
b. Neighbour
c. Radio stations
d. Other (specify)
















40
How much do you rely on traditional flood information?
a. Very much
b. Somewhat
c. Not much
d. Don‟t know
0051





41
How much do you rely on official flood information?
a.
Very much
b.
To some extent
c.
Not much
d.
Don‟t know
0052




EXTERNAL SUPPORT SYSTEMS
42
Did your household receive any help during the flood times?

No 
a. Yes
b.
`
(if yes , proceed to question below)
0053

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43
Where did the help come from?
a. Relatives/families
b. Local agencies
c. Government
d. NGO
e. Other(Specify)
0054





44
What kind of external assistance did you receive?
a. Food
b. Temporary shelter/Tents
c. Mattress
d. Blankets
e. Clothes
f.
Money
g. Mosquito nets
h. Medicine
45
i.
Structural measures
j.
Other
0055
it will meet?
b. Sufficient
c. In sufficient
d. Not useful
`

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










To what extent does the assistance meet the need you hope
a. Most sufficiently

0056

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46
To what extent can you cope without external assistance?
a.
Fully cope
b.
To a large extent
c.
To a small extent
d.
Not at all




THE END
`
0057
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APPENDIX II: FOCUS GROUP DISCUSSION GUIDE
I. INTRODUCTION
My name is Hellen Nyakundi. I am a Master of Public Health and Epidemiology student
at Kenyatta University currently conducting research on the above topic. Flooding along
the Nyando River affects many people in Nyando District and as part of a thesis project
to meet academic requirements I am researching Nyando District residents‟ perceptions
and response to this perennial hazard. This study seeks to understand the strengths of
community‟s perceptions and response in flood hazard/risk management strategies. I am
talking to women and men living in Nyando District. The opinions and information that
you provide today will be helpful to us in planning a fresh approach to dealing with
floods in Nyando. Everything discussed here today will be confidential. The FGD will
last approximately 1:30 hours.
Other study notes – explain:
 That there feedback is important
 No „right‟ or „wrong‟ answers
 All views are valued and that they should speak their minds
 They should not worry if their views differ from other people present in the
session
 Mobile phones turned off ( if applicable)
II. WARM UP
Let‟s start by going around the circle and having each person introduce herself/himself. If
you like, you can tell the group your first name an d how many children you have
III.
HISTORY OF FLOODS
1. Describe the pattern of flooding in this area. (Probe: timing, level and reason)
2. Tell us about how floods have affected you? – (Probe: What property or business
has been affected by the floods-at house hold and community levels)
3. Has the pattern changed in your life time? (Probe: how)
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131
IV.
RISK PERCEPTION
1. What risks in general do you think result from flooding? (Probe: How they occur,
the most serious risks)
2. What health risks do you think result from flooding? (Probe: How they occur, the
most serious risks)
3. Who is most vulnerable to the floods? Why?
V.
ACTIONS AND EFFECTIVENESS OF RESPONSES
1. How do individual families (households) respond when faced with a flood
emergency?
2. How does the community respond when faced with a flood emergency? (Probe:
How efforts can be improved)
3. On average, how long after the rains start do men and women wait before taking
action?
4. What are some of the reasons that would make people choose a particular
response
5. How do women/men respond when faced with a flood emergency? (Probe: How
could these efforts be improved?)
6. How do women/men decide on the appropriate response to use?
VI.
EARLY WARNING INFORMATION
1. How do you get most of your information about flood issues
2. Where could a man or woman go to get any information on imminent floods?
(probe for accessibility)
3. What type of information do you get from these sources?
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132
4. What do you think about this information (probe: adequate, reliable, timely, and
helpful?)
5. What sort of flood information would you like to receive?
6. How would you like to receive this information?
VII.
COMMUNITY PARTICIPATION IN FLOOD MANAGEMENT
1. How do you believe flood decisions are made? Who is involved?
2. What are the factors that have influenced the present decisions made on flood
management?
3. How does the community influence flood decisions?
4. Do you feel the community‟s views have been given equal weight?
5. In your opinion, who are the key players in the decision making process?
6. Who do you think should be involved in the decision making process?
7. Are women involved in making flood decisions?
8. What is your understanding of the purpose of various local committees that deal
with flooding?
9. Which plan of action do you think will best reduce the flooding problem?
Thank you for participating in this FGD
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133
APPENDIX III: INTERVIEW SCHEDULE FOR KEY INFORMANTS
I. Introduction
My name is Hellen Nyakundi. I am a Master of Public Health and Epidemiology student
at Kenyatta University currently conducting research on the above topic. Flooding along
the Nyando River affects many people in Nyando District and as part of a thesis project
to meet academic requirements I am researching Nyando District residents‟ perceptions
and response to this perennial hazard. This study seeks to understand the strengths of
community flood hazard/risk management strategies. I am talking to local officials who
are connected with and working on disaster management. Your opinion and information
that you provide today will be helpful providing data that assist in planning a fresh
approach to dealing with floods in Nyando. I assure you that your answers and opinions
will be treated in the strictest confidence and that in the analysis; the result of this
interview will be combined with the result of interviews with other people, so that no
individual can be identified. The interview will last approximately 45 minutes.
II. WARM UP
1. I would like to ask you some general questions about yourself. Firstly, could you
please tell me your name and age?
2. Could you please tell me in which GOK department or organization are you
working in?
3. What is your official designation in your department or organization?
4. How long have you been in this position?
5. What is the highest level of education you have completed?
6. How many different training courses have you attended on disaster management(
start with the most recent)
III. GENERAL FLOOD HISTORY
1. Tell me the history of flooding in Nyando district and the effects on the economy
and development
2. How have you been involved in the management of floods? (Probe: how local
authority respond to floods)
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134
3. What organizations are you involved in that deal with flood management? Probe:
At what level, what role the organizations play in flood management)
PARTICIPATION IN FLOOD MANAGEMENT
1. What has been the local authority‟s involvement in planning flood emergency
response?
2. How do you get most of your information about flood issues?(Probe: information
about impending floods, other flood issues and flood control proposals)
3. How do you believe flood decisions are made? Who is involved?
4. How does the community influence flood decisions?
5. What do you believe are the short term and long term goals for flood management
in Nyando?
6. How could these efforts be improved?
PERCEPTION OF CURRENT FLOOD MANAGEMENT POLICIES
1. What are the factors that have influenced the present decisions made on flood
management?
2. In your opinion, who are the key players in the decision making process?
3. Who do you think should be involved in the decision making process?
4. Do you feel the community‟s views have been given equal weight in
influencing flood decisions? Why?
5. What is your understanding of the purpose of various local committees that
deal with flooding?
6. What do you think would be the most important way to get better protection
from flood risks?
Thank you for participating in this interview
`
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