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THE IMPACT OF SELECTED SMALL-SCALE IRRIGATION SCHEMES ON
HOUSEHOLD INCOME AND THE LIKELIHOOD OF POVERTY IN THE LAKE
TANA BASIN OF ETHIOPIA
A Project Paper
Presented to the Faculty of the Graduate School
of Cornell University
in Partial Fulfillment of the Requirements for the Degree of
Master of Professional Studies
By
Getaneh Kebede Ayele
July 2011
© 2011 Getaneh Kebede Ayele
ABSTRACT
Poverty reduction has been largely a result of economic growth. The economic
growth and extent of poverty in Ethiopia are determined primarily by the growth of
agriculture because agriculture is the largest component of the economy. One of the
major factors behind the weak performance of Ethiopian agriculture is lack of
adequate rainfall, combined with variability in the onset and duration of rainfall.
Irrigation development is one approach to address this problem, and it has been given
significant attention in economic development programs in the country. This study
examines the impact of selected small-scale irrigation schemes on crops grown, total
income, and the likelihood of poverty at household level for a particular region.
A survey of 180 randomly-selected household heads, semi-structured
interviews and focus group discussions were undertaken in Fogera District, Tana
basin, Ethiopia to assess irrigation impacts. Descriptive statistics and econometric
modeling were used to assess the impacts of irrigation on household income and the
likelihood of a household being classified as poor. The research reported herein had
five major objectives. The first objective was to identify the major field crops and
vegetables grown using small-scale irrigation in the study area. The main field crops
grown using small-scale irrigation schemes in the study region are maize, oat, rice and
vetch and the dominant vegetables are onion, tomato, potato and pepper. Onion
production was the most important source of income from crops grown with irrigation.
The second objective was to compare the relative advantages of four types of
small-scale irrigation system, with emphasis on household gross income. Farmers
using concrete canal river/spring diversion had higher mean cropping income per
household on average than other irrigation types. Statistically significant differences
were found between the household concrete canal river/spring diversion and
traditional river diversion and pedal pump irrigation systems, but no significant
difference exists between concrete river/spring diversion and motor pump, nor
between traditional river diversion and pedal pump. Households using any of the four
irrigation systems had statistically significantly higher mean gross household income
than households not using irrigation.
A third objective was to estimate the marginal impact of small-scale irrigation
on gross household income controlling for other important factors that affect income.
A censored regression model developed for this objective indicated that access to
small–scale irrigation increased mean annual household income significantly (about
ETB 3,353 per year, or a 27 % increase over non-irrigating households).
The fourth objective of this research was to assess the impact of irrigation
access on the likelihood of poverty. Descriptive analysis suggested that irrigating
households had a lower probability of being poor than non-irrigating households: of
households in the lowest quartile of income, only 12% were irrigating households and
the remaining 88 % did not irrigate. A Logit regression model developed to assess the
impact of irrigation on the likelihood of poverty controlling for other factors indicated
that access to irrigation significantly reduced the odds that a household would be in
the lowest quartile of household income, the key poverty threshold used in this study.
A final objective was to examine the major problems encountered in the use of
the small-scale irrigation systems. These were identified by farmers and development
agents as: lack of access to surface water, loss of water through seepage, problem of
irrigation water distribution, lack of spare parts for water pumps, high cost of fuel for
water pumps, lack of market transparency and marketing facilities, crop disease, and
the perceived high cost of inputs.
iii
BIOGRAPHICAL SKETCH
Getaneh Kebede Ayele was born in the Quarit District in Western Gojjam
Administrative Zone, Amhara Region, Ethiopia to his father Kebede Ayele, and his
mother, Workie Gessesse Ayele, on January 21, 1980 GC. He attended his primary
and junior secondary schools at Quarit District in Gebeze Mariam School, and his
secondary education at Damot Senior Secondary School in Fenoteselam town. He
graduated from Alemaya University with a BSC degree in Agriculture majoring in
Animal Science on 3 July 2002 and a BA degree from Bahir Dar University in
Economics on 12 July 2008. He was employed by the Ministry of Agriculture and
worked at the Werota Agricultural College until starting this MPS program conducted
by Cornell University at Bahir Dar University. His opportunity of sharing knowledge
and skill from enormously experienced Cornell University professors inspired him to
continue his study further to PhD.
iv
ACKNOWLEDGEMENTS
First and for most, I would like to extend my unshared thanks to the almighty
God for providing me the opportunity for what I have achieved.
I am highly indebted to my research advisors Professor Tammo S. Steenhuis
and Professor Chuck F. Nicholson for their generous devotion in encouragement,
insight, guidance, and professional expertise from the early design of the research
proposal to the final write-up of the thesis. No words can suffice to express my
honored thank and gratitude to Dr. Amy S. Collick, Seifu Tilahun and Essayas Kaba
for their generous assistance and helpful encouragement during my study with all their
kindness through sharing the ups and downs. Great appreciation and special thanks to
Dr. Angela Neilan, Dr. Bowman and all other professors who taught me for their
unreserved help. I am also grateful to Cornell University for funding this research.
A special word of thanks goes for all staff members of the Fogera Woreda
Office of Agriculture and Rural Development who provide me technical assistance
and transport service. My special and particular thanks go to my friend Hailesysus
Ambaw, who lived in USA, for his materials support and encouragement throughout
my study. My wholeheartedly thanks should go to Habitamu Addis, Meseret
Belachew and all my classmates. I would like to forward my warm appreciation and
great thanks to my friend Zemenu Yayeh for his support and encouragement
throughout my study.
Finally, I am extremely grateful to my father Kebede Ayele for his dedicated
partnership in the success of my life.
v
I dedicate this thesis manuscript to all participants in Cornell-Bahir Dar Universities
MPS program, especially for Professor Tammo S. Steenhuis and Dr. Amy S. Collick
vi
TABLE OF CONTENTS
BIOGRAPHICAL SKETCH ......................................................................................... iii
ACKNOWLEDGEMENTS .......................................................................................... iv
TABLE OF CONTENTS .............................................................................................. vi
LIST OF FIGURES ....................................................................................................... ix
LIST OF TABLES ......................................................................................................... x
ABBREVIATIONS AND ACRONYMS ...................................................................... xi
CHAPTER ONE ............................................................................................................. 1
1 INTRODUCTION ................................................................................................ 1
1.1 Background and justification ........................................................................... 3 1.2 Statement of the problem ................................................................................. 5 1.3 The Goal of the research .................................................................................. 7
1.4 The specific objectives ..................................................................................... 7 1.5 Hypotheses ....................................................................................................... 8
CHAPTER TWO ............................................................................................................ 9
2 REVIEW OF RELATED LITRATURE .............................................................. 9
2.1 Poverty ............................................................................................................. 9
2.2 Water and agriculture ..................................................................................... 10
2.3 Irrigation development ................................................................................... 11 2.4 Irrigation methods .......................................................................................... 13
2.4.1 Surface irrigation .................................................................................... 13
2.4.1.1 Basin irrigation ................................................................................ 14 2.4.1.2 Furrow irrigation ............................................................................. 14
2.4.2 Flood irrigation ....................................................................................... 14 2.4.3 Border irrigation ..................................................................................... 14
2.5 Sprinkler irrigation ......................................................................................... 15 2.6 Drip irrigation................................................................................................. 15 2.7 Irrigation-poverty linkages ............................................................................. 16
CHAPTER THREE ...................................................................................................... 18
3 THE STUDY AREA AND SMALL-SCALE IRRIGATION TYPES ............... 18
3.1 Description of the study area.......................................................................... 18 3.1.1 The characteristics of the sample PAs .................................................... 20
3.1.1.1 Kuhir Michael ................................................................................. 21 3.1.1.2 Shina ................................................................................................ 21 3.1.1.3 Abana Kokit .................................................................................... 22 3.1.1.4 Bebekis ............................................................................................ 22 3.1.1.5 Werota Zuria ................................................................................... 23
vii
3.2 Small-scale irrigation types ............................................................................ 23 3.2.1 Concrete canal river diversion ................................................................ 23 3.2.2 Spring development small-scale irrigation scheme ................................ 28 3.2.3 Motorized pump ..................................................................................... 29 3.2.4 Pedal pump ............................................................................................. 29
3.2.5 Traditional river diversion ...................................................................... 34
CHAPTER FOUR ........................................................................................................ 35
4 MATERIALS AND METHODS ........................................................................ 35
4.1 Research methods........................................................................................... 35 4.1.1 Approach for data collection, entry and checking .................................. 35
4.1.2 Data analysis ........................................................................................... 39
4.1.2.1 Socio-economic and demographic characteristics of the sample
households ...................................................................................................... 39 4.1.2.2 Income evaluation ........................................................................... 40 4.1.2.3 Poverty level evaluation .................................................................. 48 4.1.2.4 Poverty Line .................................................................................... 49
4.1.2.5 Poverty level comparison ................................................................ 50 4.1.2.6 Econometric model specification .................................................... 51
CHAPTER FIVE .......................................................................................................... 54
5 RESULTS AND DISCUSSION ......................................................................... 54
5.1 Household Socio-economic characteristics.................................................... 54
5.1.1 Family size .............................................................................................. 54
5.1.2 Family labor ............................................................................................ 55 5.1.3 Dependency ratio .................................................................................... 55 5.1.4 Sex and education of the household head ............................................... 56
5.1.5 Age of household head ........................................................................... 57 5.2 Productive resource ........................................................................................ 57
5.2.1 Land holding ........................................................................................... 58 5.2.2 Effect of irrigation on land rent value .................................................... 60
5.2.3 Production assets .................................................................................... 60 5.2.4 Type of houses ........................................................................................ 61
5.3 Major crops grown using small-scale irrigation............................................. 61 5.4 Household income evaluation ........................................................................ 63
5.4.1 Cropping incomes ................................................................................... 64
5.4.1.1 Rainfed cropping income ................................................................ 65
5.4.1.2 Irrigated crop income in PAs .......................................................... 66
5.4.1.3 Total cropping income .................................................................... 68 5.4.2 Livestock income .................................................................................... 68 5.4.3 Off-farm and other incomes ................................................................... 71 5.4.4 Summary of income sources at household level .................................... 72 5.4.5 Econometric model for income analysis ................................................ 73
5.4.6 Comparison of sample small-scale irrigation types at household level . 79 5.4.6.1 Sample small-scale irrigation types and irrigated crop income. ..... 79
viii
5.4.6.2 The small-scale irrigation types and total income of household ..... 82 5.5 Poverty analysis ............................................................................................. 83
5.5.1 Poverty level in the study area ................................................................ 83 5.5.2 Multivariate Logit regression ................................................................. 86
5.6 Problems encountered in small-scale irrigation development ....................... 89
CHAPTER SIX ............................................................................................................ 97
6 CONCLUSIONS AND RECOMMENDATIONS ............................................. 97
6.1 Conclusions .................................................................................................... 97 6.2 Policy implications ......................................................................................... 99 6.3 Limitations and questions for future studies ................................................ 103
REFERENCES ........................................................................................................... 105
APPENDIX- A: TABLES OF CROP VALUES AND CONVERSION FACTORS. 115
APPENDIX- B: SURVEY QUESTIONNAIRE ........................................................ 117
ix
LIST OF FIGURES
Figure 1: Location of Fogera District ........................................................................... 19 Figure 2: Guanta river dam ........................................................................................... 24 Figure 3: Irrigation and livestock ................................................................................. 25 Figure 4: Motor pump irrigation from river diversion canal ........................................ 26 Figure 5: A women and Children fetch water from river diversion for household
consumption. ................................................................................................................ 27 Figure 6: The river diversion dam on Eriza River in Werota Zuria ............................. 27 Figure 7: Tanqua Gabriel spring development ............................................................. 28 Figure 8: Motor pump irrigation using Eriza River near Werota town ........................ 29 Figure 9: Pedal pump .................................................................................................... 30
Figure 10: Sample wells constructed for only one cropping season ............................ 31 Figure 11: Sample of Vertisol ...................................................................................... 31
Figure 12: Well constructed from tire materials ........................................................... 32
Figure 13: Irrigation by fetching water from wells ...................................................... 33 Figure 14: Sample well constructed by cement cylinder .............................................. 33 Figure 15: Water loss through seepage from river diversion canal .............................. 90
Figure 16: Water loss from motor pump ...................................................................... 92 Figure 17: Parts of pedal pump demonstrate loss of tightness ..................................... 93
Figure 18: Non-functional shallow well ....................................................................... 95
x
LIST OF TABLES
Table 1: Summary of sample size by PA and irrigation types ..................................... 37 Table 2: Summary of dependent and independent variables codes, definitions and
expected sign of effect on household income ............................................................... 46 Table 3: Summary of the dependent and independent variables, codes, definitions and
expected signs. .............................................................................................................. 52
Table 4: Family size, family labor and dependency ratio for irrigating and non-
irrigating households .................................................................................................... 54 Table 5: Household member, gender, and education and age characterization ........... 57 Table 6: Average landing size (ha) at household‟s level .............................................. 59 Table 7: Average land rental rate ................................................................................. 60
Table 8: Mean value of agriculture production assets at household‟s level ................. 61 Table 9 : Housing types in samples households ........................................................... 61
Table 10: The major field crops and vegetables grown using small-scale irrigation ... 62
Table 11: Reason for selecting the major field crops and vegetables for irrigation ..... 63 Table 12: Major crop types and their mean annual production values ......................... 65 Table 13: The reasons for non-irrigating households for not irrigating ....................... 66
Table 14: Rainfed income for irrigating and non-irrigating households in ETB ......... 66 Table 15: Income from irrigated crop production in ETB ........................................... 67
Table 16: Total mean annual cropping income at household level in ETB ................. 68 Table 17: Number of livestock (TLU) .......................................................................... 69 Table 18: Average annual livestock income ................................................................ 70
Table 19: The mean off-farm and other incomes ......................................................... 71
Table 20: Summary of annual household income sources: .......................................... 72 Table 21: Tobit estimates of the determinants for household total income ................. 75 Table 22: Marginal effects of determinants on household total income ...................... 78
Table 23: The sample small-scale irrigation types and irrigated crop income per
irrigating household ...................................................................................................... 80
Table 24: The sample small-scale irrigation types and irrigated crop income ............. 81 Table 25: Small scale irrigation types and total income of a household ...................... 82
Table 26:Small-scale irrigation types and the mean annual income of a household .... 83 Table 27: Poverty comparison between irrigating and non-irrigating household ........ 84 Table 28: The average income poverty gap of the poor by sample PAs ...................... 85 Table 29: The average income poverty gap between irrigating and non-irrigating
households .................................................................................................................... 85
Table 30: Parameter estimates of a logit model for determinants of a household
poverty .......................................................................................................................... 87
xi
ABBREVIATIONS AND ACRONYMS
ADLI Agricultural Development Led Industrialization
ACSI Amhara credit and saving institution
AE Adult equivalent
BoARD Bureau of Agriculture and rural development
CSA Central Statistics Agency
ETB Ethiopian Birr
HA Hectare
IPMS Improving Productivity and Market Success
LDC Less developed countries
MOARD Ministry of Agriculture and Rural Development
MOFED Ministry of Finance and Economic Development
PA Administrative unit in a district
PG Poverty Gap
TLU Total livestock unit
WAE Water Aid Ethiopia
1
CHAPTER ONE
1 INTRODUCTION
Poverty alleviation1 has been largely a result of economic growth (Roemer and
Gugerty 1997). Because Ethiopia is an agrarian country, agriculture is the leading
sector as source of income, employment and foreign exchange and national economic
growth is determined by the performance of agriculture. Irrigation plays the key role
in the performance of agriculture, which increases income growth. Income growth is
essential for economic growth (Hussain and Biltonen 2001). Developing countries that
ensure sustainable economic growth can be able to reduce their poverty levels,
building up their democratic and political stability. They also improve the quality of
natural environment and even reduce their incidence of crime and violence (Loayza
and Soto 2002).
To understand the role of irrigation in income growth and poverty alleviation,
it is useful to review the fundamental sources of economic growth. According to
(Maddison 1970) there are three major sources of economic growth. The first is an
increase in the amounts of inputs used in production. Additional inputs can move a
country out on its aggregate production function to a higher isoquant and higher levels
of output. The three major inputs in the development process are population growth
(which affects labor availability and labor), natural resource availability (which affects
the cost of environmental factors such as land with its associated soils, water, and
forest), and capital accumulation (which affects the availability of man-made inputs).
1 Poverty alleviation is the ability to produce goods and services above a minimum level of income
needed to maintain the basic needs.
2
These sources of growth cause movement along a given multifactor production
function. The second source of growth is a change the way in which a country uses its
factors of production, increasing the amount of output produced by these inputs. These
outputs increase can result from better organization of production or from shifts in the
production function. For example, a new technology can shift the total production
curve upward so more output is produced per unit of input. Increases in scale or
specialization, increases in efficiency, or technological change are examples. In many
cases, market conditions (relative prices) can change, in turn stimulating changes in
these factors. The third source is increased human capital as embodied in people (e.g.,
improved education and health) and improvements in social institutions. Human
capital can make labor more productive, contributing to technological progress and
increase efficiency (especially when technologies and markets are rapidly changing).
Agriculture contributes substantially to the economic growth of many low-
income countries. It is often the leading sector of the economy as source of income,
employment and foreign exchange. Agriculture employs more than 70 percent and
contributes 30 to 60 percent of the gross domestic product (GDP). More than half of
the less developed countries population gets their food from own-production.
Agriculture output also is used as an input for industries so it can stimulate the growth
of industrialization. Improving agricultural productivity thus has contributes to income
growth (UNDP 2007).
Ethiopia ranks 170 out of 177 the poorest countries on the Human
Development Index (UNDP 2006). Its GDP per capita was $ 350 in 2010 compared to
$ 809 for Kenya and $ 1,705 for Sudan (IMF 2011). Half of Ethiopia‟s GDP depends
on agricultural activity. Thus, the economy of Ethiopia is largely dependent on
agriculture, and about 85% of the population is engaged in it. The dependency on
rainfed agriculture coupled with the erratic nature of rainfall is the major factors
3
blamed for the poor performance of the agricultural sector and main cause of
widespread food insecurity in the country (FAO 1994).
Irrigation has served as one key driver behind growth in agricultural
productivity, increasing household income and alleviation of rural poverty, which
highlights the various ways that irrigation could have an impact on poverty. According
to Lipton et al. (2004) cited by Haile (2008), there are four interrelated mechanisms by
which irrigated agriculture can reduce poverty, through: (i) increasing production and
income, and reduction of food prices, that helps very poor households meet the basic
needs and associated with improvements in household overall economic welfare, (ii)
protecting against risks of crop loss due to erratic, unreliable or insufficient rainwater
supplies, (iii) promoting greater use of yield enhancing farm inputs and (iv) creation of
additional employment, which together enables people to move out of the poverty
cycle. In the same way, Zhou et al. (2008) mentioned that irrigation contributes to
agricultural production in two ways: increasing crop yields, and enabling farmers to
increase cropping intensity and switch to high-value crops. Therefore, irrigation can be
an indispensable technological intervention to increase household income. This study
will examine the impacts of irrigation on incomes at the household level for one
region of Ethiopia.
1.1 Background and justification
Irrigation use in Ethiopia dates back several centuries, and continues to be an
integral part of Ethiopian agriculture. In Ethiopia, modern irrigation began in the
1950s through private and government owned schemes in the middle Awash valley
where big sugar, fruit and cotton state farms are found (FAO 1997).
The main purpose of irrigation development in the 1960s was to provide
industrial crops to the growing agro-industries in the country. The agro-industries
4
were established by foreign investors and had the objective of increasing export
earnings. During the 1960s, irrigation was seen as part of the modernization of the
country's agricultural economy. It was considered as an important investment for
improving rural income through the increased agricultural production. But, in 1975 the
rural land proclamation was introduced in the country. Following the rural land
proclamation, the irrigated private farms were nationalized and converted to state
farms by the Derg regime.
By early 1985 in Ethiopia, some 7.7 million people were suffering from
drought and food shortages. More than 300,000 died in 1984 alone, more than twice
the number that died in the drought a decade before. Before the worst was over, 1
million Ethiopians had died from drought and famine in the 1980s. The recurring
cycle of drought produce the need for small-scale-irrigation development expansion to
other parts of the country to address drought and food shortages, and the need for
more food for the internal market.
Agricultural growth is not produced by passive policies. There is no unique
policy prescription that fits the diversity of the agricultural sector in the less developed
countries. Enhancing productivity is a common essential requirement. The increase in
productivity will determine by the appropriate policy mix. The major lesson that
emerges from country experiences is that for agricultural growth to occur, a number of
factors need to be addressed in the rural sector such as infrastructure, social services,
technology, marketing infrastructure, and seasonal credit availability, along with the
building of an appropriate institutional environment (UNDP 2007).
The current government has undertaken various activities to expand irrigation
in the country. The country‟s Agricultural Development Led Industrialization (ADLI)
strategy considers irrigation development as a key input for sustainable development.
5
Thus, irrigation development, particularly small-scale irrigation is planned to be
accelerated (MOFED 2010).
Ethiopia is believed to have the potential of 5.1 million hectares of land that
can be developed for irrigation through pump, gravity, pressure, underground water,
water harvesting and other mechanisms (MOFED 2010). According to BOARD
(2010) and Awulachew et al. (2005) the total irrigated land in the Amhara region was
347,725 hectares. There are 310 modern irrigation schemes developed in this region.
The irrigation schemes developed have covered an irrigated area of 8,469.2 hectares
with 17,443 beneficiaries. Out of these total irrigated areas 5,718.68 hectares is from
small-scale and 2,750.58 hectares from medium-scale irrigation schemes.
The study area, Fogera District, is one of the eight Districts bordering Lake Tana,
source of Blue Nile. This District has an estimated 23,354 hectares of water bodies.
The District is endowed with beautiful and diverse natural resources, with capacity to
grow diverse annual crops. The altitude ranges from 1774 to 2410 masl. The mean
annual rainfall is 1215 mm and ranges from 1100 to 1340 mm (MOA 2005).
Therefore, the district has a great potential for small-scale irrigation. The objective of
this study is to evaluate the impact of selected small-scale irrigation schemes on
household gross income and on poverty reduction in Fogera district.
1.2 Statement of the problem
Agricultural production in Ethiopia is primarily rainfed, so it depends on
erratic and often insufficient rainfall. As a result, there are frequent failures of
agricultural production. Irrigation has the potential to stabilize agricultural production
and mitigate the negative impacts of variable or insufficient rainfall.
Irrigation development also can help offset some of the negative effects of
rapid population growth (2.6% per year in Ethiopia; CSA 2007). Population growth
6
causes agricultural activities expands into marginal land, which leads to forest, land
and water degradation. This environmental degradation can reduce agricultural
productivity, which in turn worsens food insecurity and poverty. In order to respond to
growing food demand, food production should increase. The three methods to increase
food production are: increasing agricultural yield, increasing the area of arable land,
and increasing cropping intensity (number of crops per year). Irrigation has the
potential to increase both yields and cropping intensity in Ethiopia (Awulachew et al.
2010).
Irrigation increases agricultural productivity and farm income per ha,
according to previous studies (Nhundu et al., 2010; Gebremedhin and Peden 2002;
Hussain 2006). It insulates the national agricultural economic sector against weather-
related shocks and provides a more stable basis for economic growth and poverty
reduction. It supports the process of transforming traditional subsistence agriculture in
to market-oriented production of high value crops (Asfaw 2007).
The development of water resources for agricultural purposes (irrigation) is
rising rapidly. According to BCEOM (1998) and Tilahun & Paulos (2004) as cited in
Awulachew et al. (2010), in 1990 Ethiopia had an estimated a total of 161,000
hectares of irrigated agriculture, of which 64,000 ha were in small-scale schemes,
97,000 ha were in medium-and large-scale schemes and approximately 38,000 ha were
under implementation. This had grown to more than 247,000 ha by 2004, with
traditional irrigation schemes alone covering more than 138,000 ha. Currently, the
Ethiopian government gives more emphasis to small-scale irrigation as a means of
achieving food self-sufficiency (MOFED 2010).
Fogera District is an irrigation potential area, with an estimated 23,483
hectares of water bodies (MOA 2005). However, the living standard of the community
7
is subsistence2. Sustainable economic development will be supported by effective
agricultural technology intervention. Equal and fair technology distribution within the
community is valuable for balanced economic growth (Kobets 2004). This study will
assess the impact of small-scale irrigation on the household gross income and poverty
reduction at the household level.
1.3 The Goal of the research
The goal of this research is to evaluate the economic impact of selected small-
scale irrigation on income and poverty reduction at household level. It compares
households with and without access to small-scale irrigation systems. It also compares
households who use four different small-scale irrigation schemes in the five villages of
the district.
1.4 The specific objectives
The specific objectives of this project are as follows:
1. To identify the major field crops and vegetables grown using small-scale
irrigation in the study area;
2. To compare the relative advantages of the various types of small-scale
irrigation system;
3. To examine the major constraints encountered in the use of the small-scale
irrigation systems;
2 Subsistence means the production of goods and services is not beyond maximum level of income
requisite to maintain the basic needs of household consumption. People need aid if one agricultural
season fails due to lack of rain or other adverse events.
8
4. To examine the effects of small-scale irrigation on the gross income at
household level;
5. To determine the difference in prevalence of poverty between small-scale
irrigating and non-irrigating households;
6. To apply the study findings to make recommendation and policy
implementation of small-scale irrigation systems.
1.5 Hypotheses
The hypotheses of this research are:
1. Small-scale irrigation has a positive impact on household gross income,
cropping income and livestock income but has a negative impact on non-farm
incomes
2. Small-scale irrigation has a negative impact on poverty. The probability of
being poor is lower among users of small-scale irrigation compared to non-
users in the agricultural sector.
3. Irrigation users have more agricultural productive assets and non-agricultural
asset holdings.
9
CHAPTER TWO
2 REVIEW OF RELATED LITRATURE
2.1 Poverty
Poverty definitions and measurement have important implications for targeting
and policy. The concept of poverty goes back to the 16th
and 17th
centuries. Before
1750, there were four approaches to poverty: acceptance (resignation), charity,
precarious rescue and theft depending on which side of the fence the observer stood.
Since the era of mercantilism, the fight against poverty has been marked and
consequently, it was with the advent of the mercantile economy and the urbanization
and monetarization of society that the poor had been defined in terms of lacking what
the rich had, David (1994) cited by Abraham (2006).
Poverty is a highly complex problem. It has multiple causes and
manifestations. According to Townsend (1993) poverty is defined as absence or
inadequacy of diets, amenities, standards and services that allow people to follow the
customary behaviors expected of them by virtue of their membership of society.
Poverty exists for people whose resources are seriously lacking when compared to the
resources available by the average individual or family (Haile 2008). Poor people are
those who are excluded from ordinary living patterns, customs and activities. Some
defined poverty in general terms as inability to maintain a minimal standard of living.
Others also have defined the poor as those who do not have adequate resources to
meet their basic needs. The United Nations (UN 1995) defined absolute poverty as “a
condition characterized by severe deprivation of basic human needs, including food,
safe drinking water, sanitation facilities, health, shelter, education and information. It
depends not only on income but also on access to services”.
10
McClelland (2000) indicated that “Poverty is where people have unreasonably
low living standards compared with others; cannot afford to buy necessities, such as a
refrigerator for example; and experience real deprivation and hardship in everyday
life”. Empirical evidence shows that poverty rates vary when different concepts and
measures are used. There are two types of poverty, absolute and relative poverty:
absolute poverty is defined as the minimum amounts of essential goods and services a
household needed to survive. It is estimated based on the income needed to purchase
these subsistence amounts. Relative poverty is the households‟ standard of living falls
seriously below what is believed normal for the society in which they live (Ravallion
1998) cited by Haile (2008).
2.2 Water and agriculture
Water, soil, air and sunshine are the four main determinants for plant growth.
Therefore, water is essential to plant-growth and crop-production (Widtose 2001). All
sectors depend on water. Water is important for agriculture, household consumption,
industry, hydropower, navigation, fisheries, recreation, and ecosystems. Without water
there is no food production. When there is adequate supply of water, crops grow best
and produce most.
Water is a basic need for human beings and animals. It is essential for their
metabolic processes. Livestock water requirements are mainly provided by direct
water intake and partly by the moisture content of their forage. Livestock production
requires large quantities of forage. The production of forage requires substantial
amounts of water. Therefore, water is vital for all agriculture types.
According to Dupriez and De Leener (2002), the sources of water for crop
production are rainfall and irrigation water. The two types of agriculture seen from the
perspective of water management are:
11
Rainfed cultivation is agricultural production of crop depending entirely on the rain. It
relies on the rainfall timing and distribution. Rainfed farming is characterized by
plateau cultivation and dry land cropping. Rainfed farming is mostly practiced during
one growing season, unimodal, but in some areas two growing seasons (bimodal
production) are possible.
Irrigated cultivation is agricultural production using irrigation water in addition to
rainfall. Irrigated crops benefit from man-made watering with the help of water pipes,
canals, reservoirs and pumps. The source of irrigation water is surface water or
groundwater. Surface water is obtained in ponds, lakes, rivers and seas whereas
groundwater is obtained underground in liquid or vapor state (Dupriez and De Leener
2002).
2.3 Irrigation development
Irrigation is generally defined as the application of water to the land for the
purpose of supplying moisture essential to plant growth. It is an age-old art. Irrigation
was practiced for thousands of years in the Nile Valley. Egypt claims to have the
world's oldest dam built about 5000 years ago to supply drinking water and for
irrigation. At that time basin irrigation was introduced and still plays a significant role
in Egyptian agriculture. According to Zewdie et al. (2007) irrigation has been
practiced in Egypt, China, India and other parts of Asia for a long period of time. India
and Far East have grown rice using irrigation nearly for 5000 years. The Nile valley in
Egypt, the plain of Euphrates and Tigris in Iraq were under irrigation for 4000 years.
Irrigation is the foundation of civilization in numerous regions. Egyptians have
depended on Nile‟s flooding for irrigation continuously for a long period of time on a
large scale. The land between Euphrates and Tigris, Mesopotamia, was the
12
breadbasket for the Sumerian Empire. The civilization developed from centrally
controlled irrigation system (Schilfgaard 1994).
Evidence also shows that irrigation in China was begun about 4000 years ago.
There were reservoirs in Sri Lanka more than 2000 years old. As far back as 2300 BC,
the Babylonian Code of Khammurabi provided that 'If anyone opens his irrigation
canals to let in water, but is careless and the water floods the fields of his neighbor, he
shall measure out grain to the latter in proportion to the yield of the neighboring field.'
Other indicator for irrigation development is found in the stony-gravel limestone
desert of the Negev area in Israel. Remnants of these ancient irrigation systems date
back from the Israelite period (about 1000 BC) and from the Nabattean- Roman-
Byzantine era (300 BC to 600 AD). In the absence of permanent water sources, the
ancient farmers developed 'runoff' farm systems that used sporadic flash floods for
irrigating (Shanan 1987).
Ethiopia has a long history of traditional irrigation systems. Simple river
diversion still is the dominant irrigation system in Ethiopia. According to
Gebremedhin and Peden (2002), the country‟s irrigation potential ranges from 1.0 to
3.5 million hectares but the recent studies indicate that the irrigation potential of the
country is higher. According to Tilahun and Paulos (2004) as cited by Awulachew et
al. (2010), estimates of the irrigation potential of Ethiopia may be as large as 4.3
million hectares. Traditional irrigation schemes cover more than 138,000 hectares
whereas modern small-scale irrigation covers about 48,000 hectares. The total current
irrigation covers only about 6% of the estimated potential land area.
According to the MOA (2005) and Awulachew et al. (2007), Amhara region
has 770,000 hectares of irrigation potential. Different development activities have
been underway to utilize these resources. Currently, there are 310 irrigation schemes
operating in the Amhara region. The irrigation schemes developed cover an irrigated
13
area of 8,469 hectares with 17,443 beneficiaries. Of these total irrigated areas, 5,719
hectares are from small-scale and 2,751 are from medium-scale irrigation schemes.
2.4 Irrigation methods
Irrigation methods are the systems how to obtain water for irrigation purposes
from its sources. According to Dupriez and De Leener (2002), irrigation methods
depend on several factors such as topography, water resources, the plants cultivated,
the land tenure systems, the growing seasons and the rain and water regimes.
2.4.1 Surface irrigation
There are only two general methods of applying irrigation water. The first is
surface irrigation. Surface, irrigation means above the ground, and is the method
generally adopted in all countries. There is a great variety of methods of surface
irrigation, most of which do not merit serious consideration, because they either fail to
recognize the natural laws underlying irrigation, or their cost of installation is
unaffordable in the current context. The second is sub-surface irrigation, the
application of irrigation water from below. Sub-surface irrigation has the advantage
that water so applied is not subject to such direct evaporation from the surface as of
necessity accompanies surface irrigation.
According to Widtose (2001), surface irrigation methods are furrow irrigation,
flood irrigation basin irrigation and boarder irrigation. The choice and adoption of
these irrigation methods are depending on the nature of the soil, the contour of the
land, the head of the water stream, the quantity of water available and the nature of the
crop.
14
2.4.1.1 Basin irrigation
A basin is a piece of land, small or large, surrounded by earth bunds in which water is
ponded. The water can be impounded within it to irrigate trees, vegetables or crops
grown in patches. The field is divided in to compartments or checks wholly
surrounded by levees. The water is contained at the upper end and completely fills the
compartments until it over flows at the lowest point of the levees.
2.4.1.2 Furrow irrigation
In this method, the water is guided in the furrow or channels that pass through the
whole field, but the water covers only part of the soil surface, so it results in less
evaporation. The furrows are separated with ridges. At each ridge, water is conveyed
into furrows that can be perceived as narrow basins or borders. Furrowing is applied
on steep slopes.
2.4.2 Flood irrigation
In flood irrigation, all of the soil is covered by the water applied. It is the least
controlled of all surface irrigation techniques. Water is conveyed in a ditch at the
upper part of plot and allowed to spread over the land in a manner directed by the
natural landscape. Flooding is best applied when the slope is limited.
2.4.3 Border irrigation
The border method of irrigation is an open-field method. Here the land is divided in to
elongated plots confined between low earth banks and configured to slope uniformly
from the point of supply. The land surface should slope gently in the direction of flow
15
and it is generally leveled laterally, along all cross sections perpendicular to that
direction. Water is guided over the land by field ditches.
2.5 Sprinkler irrigation
According to Dupriez and De Leener (2002), Sprinkler irrigation imitates
rainfall. It is also called overhead irrigation. The water is broken up in to fine droplets
and falls on the ground or the vegetation. It is the application and distribution of water
over the field in the form of a spray, or a jet which breaks in to drops or droplets,
created by expelling water under pressure from an orifice.
In contrast to surface irrigation, sprinkler systems are designed to deliver water
to the field without depending on the soil surface for water conveyance or distribution.
To prevent pondings and surface runoff, sprinklers are designed and arranged to apply
water at a rate that does not exceed the soil‟s infiltration. Water application efficiency
under sprinkling irrigation is strongly affected by wind, especially during daytime
when the air is warm and dry, and if the droplets are small and the application rate is
low.
2.6 Drip irrigation
The principle of drip irrigation is to wet dry ground with small amounts of
water just where the plants can absorb it. Drip irrigation is practiced in dry, arid
regions where water is scarce and must be used sparingly. Water is delivered to the
points via a set of plastic lateral tubes laid along the ground or buried at a depth of 15-
30 cm and supplied from a field main. These tubes are left in place throughout the
irrigation season. Drip irrigation can save water by reducing the portion of the soil
surface that is wetted thus, decreasing the amount of direct evaporation.
16
2.7 Irrigation-poverty linkages
Some literature argues that irrigation agriculture causes water logging that
create favorable condition for the multiplication of disease causing agents such as
malaria, Schistosomiasis and the like. The other environmental problems with
irrigation are land degradation and salinity. On the other hand, there is much
literatures that shows irrigation is a major driving factor of the increase in rural
household income through agricultural growth. These studies strongly argue that
irrigation expansion the main policy intervention to alleviate rural poverty. According
to Lipton et al. (2004) as cited by Haile (2008) the four main inter-related mechanisms
to reduce poverty are:
1. Irrigation increase agricultural production and income, for households with
access. These outcomes are observed despite the price decrease that can occur
as supply increases (other factors held constant). The rice decrease can allow
poorer households to more easily meet their basic needs. Household level
economic welfare is improved for the poor.
2. Irrigation protects from the risk of crop loss due to erratic, unreliable or
insufficient rainwater supplies.
3. Irrigation enhances the use yield-enhancing farm inputs. The uses of such farm
inputs improve the agricultural production and income.
4. Irrigation creates additional employment. Household and/or laborers are
engaged in the irrigation farming that helps to increase the labor productivity
during the dry periods, farm off-season.
Water is a valuable input for agriculture. Irrigation water appears to provide
many pathways for poverty alleviation. The access to consistent irrigation water can
enable farmers to adopt irrigation technologies. Irrigation facilitates the intensity of
cultivation that leads to an increase in agricultural productivity and greater returns
17
from farming. The expansion of irrigation opens up new employment opportunities in
the household that increase the efficiency of labor and land. This improves farm
income, livelihood, and the quality of life in rural areas (Hussain and Hanjra 2004).
18
CHAPTER THREE
3 THE STUDY AREA AND SMALL-SCALE IRRIGATION
TYPES
3.1 Description of the study area
Ethiopia is situated in the East Africa and lies between 3°30´ and 14°50´ North
latitudes and 32°42´ and 48°12´ East longitudes. It has a surface area of about 1.127
Million km2, of which 1,119,683 km
2 is and 7,444 km
2 is water. The country has a
land boundary length of 5,311km. Ethiopia has special features because of its
topography, geology and climate (Awulachew et al. 2001).
Ethiopia is a landlocked country consisting of nine independent regions and
two city councils divided along ethnic lines. It occupies an area of 1.14 million square
kilometers. The country shares its international borders with five African countries:
Eritrea in the North, Djibouti and Somalia in the East, Kenya in the South and Sudan
in the west. Ethiopia is one of the poorest countries in the world with a population of
83 million in 2008 being the second most populous in Africa next to Nigeria. The
nation‟s economy is mainly dependent on rainfed agriculture, which accounts for half
the GDP, 60% of exports and 80% of employment (WAE 2008). Ethiopia has nine
National Regional States and two Special City Administrations: Addis Ababa and Dire
Dawa.
Amhara Region is one of the regional states of the Federal Republic of
Ethiopia. Amhara region has a geographical area of about 153,000 Km2. Ethiopia‟s
largest inland body of water, Lake Tana, as well as the Semien Mountains National
Park, which includes the highest point in Ethiopia; Ras Dashan is located in Amhara
region.
19
According to the CSA (2007), Amhara National Regional State has a total
population of 17,214,056, with 8,636,875 men and 8,577,181 women. Only 12.2
percent of the population lives in urban areas. The region covers a total land area of
159,173.66 square kilometers and the population density is 108.15 people per square
kilometer. The region has 3,953,115 households. The average family size in urban
and rural areas is 3.3 and 4.5 persons, respectively.
The study was conducted in Fogera District, which is one of the 106 Districts
of the Amhara Regional State and found in South Gondar Zone. Fogera is one of the
eight districts bordering Lake Tana, source of Blue Nile. It is situated at 110 58 N
latitude and 370 41 E longitude. Woreta is the capital of the District. It is found 625
km from Addis Ababa and 55 km from the Regional capital, Bahir Dar.
Figure 1: Location of Fogera District
Fogera district is bordered by Libo Kemkem district in the North, Dera district
in the South, Lake Tana in the West and Farta district in the East. The district is
20
divided into 28 rural and 5 Urban PAs. The district has a total land area of 117,414
hectares. The land use pattern of the district includes 51,662 hectares of cultivated
land, 25,831 hectares of pasture land, and 16,434 ha for other purposes, and the water
bodies‟ account for 23,483 hectares (MOA 2005). IPMS (2005) indicate that flat land
accounts for 76%, mountain and hills 11% and valley bottom 13%. The high
proportion of plain topography creates the opportunity for irrigation. However, water
logging is a common phenomenon in the plain areas of the district. The average land
holding per household is about 1.4 hectare with a minimum and maximum hectare of
0.5 and 3.0 hectares, respectively. The altitude ranges from 1774 to 2410 masl. The
mean annual rainfall is 1215 mm and ranges from 1100 to 1340 mm (MOA 2005).
The 28 rural PAs have a total population of 212,204. Werota, the capital of the
district, has one rural PA known as Werota Zuria. The town has 40,404 inhabitants.
The number of agricultural households in the district is 44,168 (MOA 2010).
3.1.1 The characteristics of the sample PAs
Five PAs in Fogera district were chosen for the purposes of this study, and it is
appropriate to discuss some of their basic characteristics in this section. The sample
PAs has some common characteristics. The agro-climatic ecology of the five PAs is
similar. In each PA, the belg and meher are two cropping seasons. The belg cropping
season is a very short rainy period whereas meher season is the long rainy period.
Farmers depend on meher season for rainfed crop production. The onset, duration and
quantity of the rainfall are variable. Agriculture is the major occupation of the people
in the PAs. The agriculture in all PAs is a mixed crop–livestock farming system. Crop
production is rainfed during the rainy season, supplemented for some households by
small-scale irrigation in the dry season. The dominant crops grown in the study area
are rice, teff (Eragrostis), wheat, barley, maize, beans, peas, chickpeas, lentils,
21
fenugreek and noug. Commonly produced vegetables are onion, tomato, potato,
pepper and cabbage.
3.1.1.1 Kuhir Michael
The PA is located 17 Kilometer south-east of Werota town and 39 Kilometer
North of Bahir Dar. The main Asphalt road pass from Addis Ababa to Gonder passes
through this PA. Gumara town, which is known as an onion and tomato market, is
found in this PA. According to Fogera district office of Agriculture 2010 report, the
number population and households in the PA were estimated 6,068 and 1,411,
respectively.
The landscape of the PA is characterized with both plain and upland. Vertisol
is the main soil type in the area. Kuhir Michael is endowed with perennial rivers and
streams. Gumara River, one of the largest tributaries of Lake Tana, passes through this
PA. Farmers use the Gumara River for all of their water need. Gumara River is used
for drinking purpose. Both people and livestock use it for drinking, washing and other
activities. Irrigation is the other important use of the Gumara River. Motorized pumps
are widely used to draw the water from the river for irrigation. Farmers who cannot
afford to buy pumps sometimes use those of other farmers by renting in daily and (or)
hourly basis. The other river that is widely used for irrigation by the farmers in this PA
is the Guanta River. The Guanta is diverted by a cement concrete channel for
irrigation purposes. Traditional river diversion from rivers and well water using pedal
pumps are also practiced in this PA.
3.1.1.2 Shina
Shina is located 13 km south-west of Werota town. It is found towards Lake
Tana. According to Fogera district office of Agriculture 2010, the number of
22
population and households in the PA were estimated 10,052 and 2011, respectively.
The average farm size is estimated to be 1.3 hectare per household. The landscape of
the PA is plain. The soil type is black at around 7 meters depth but the upper layer is
silt. The total surface area of the PA is 3,400 hectares. About 2,071 hectares are used
for cultivation, 664 hectares are used for communal grazing, 244 for private grazing
land, 83 hectares are covered by eucalyptus tree and 334 hectares are used for
residential and governmental institutions. Motor and treadle water pumps are the
common irrigation systems. Traditional river diversion and shallow wells are also used
for irrigation, drinking, washing and other household consumption in the PA. The two
major rivers, Gumara and Reb that have great economic importance to the district
traverse this PA. These rivers are mainly used in the PA for irrigation during the dry
season using water pumps. The small-scale irrigation methods used in the PA are
motorized pumps, treadle pumps, traditional river diversion, and wells.
3.1.1.3 Abana Kokit
Abana Kokit is situated thirteen kilometers north of Werota Town. The main
asphalt road from Addis Ababa to Gonder crosses the PA. The topography of the PA
is characterized as both plain and upland type. The Fogera district office of agriculture
(2010) indicates that the total household and population of the PA are 921 and 3,496.
The Reb river passes through the PA. The river is used for irrigation purpose using
motorized pumps. There are other small rivers that are used for traditional river
diversion.
3.1.1.4 Bebekis
Bebeks is one of the rural PAs in the Fogera district. It is located 19 kilometers
southeast of Werota town. According to Fogera district office of agriculture (2010) the
23
number population and households in the PA were estimated 8,595 and 1,465,
respectively. In the PA, there is a concrete diversion from three perennial springs used
for small-scale irrigation. This is locally known as “Timeket Bahir” which means lake
used for Epiphany. The spring diversion is geographically located at 11047
′32″ N
latitude and 37039
′40
″ E longitude. The scheme is used to irrigate 120 hectares of land,
with 496 beneficiary households. The irrigation water is used for cropping, drinking,
washing and other household consumption activities. Gumara River passes through
this PA. Traditional river diversion and water pumps are the other commonly used
irrigation practices in this PA.
3.1.1.5 Werota Zuria
Werota Zuria is the rural part of Werota town. According to the Werota town
administrative agricultural office (2010) Werota Zuria has a total population of 6081.
There are 1,415 household involved in crop and livestock farming in Werota Zuria
PA. In this PA, there is a river diversion dam on the Eriza river. The dam was
constructed in 2003 by IFAD with 104 beneficiary households. The irrigation potential
of the dam is 26 hectares.
3.2 Small-scale irrigation types
3.2.1 Concrete canal river diversion
River diversion irrigation systems are practiced in the four Sample PAs such as
Quahir Michael, Shina, Bebeks and Werota Zuria. Guanta River is the main source of
water for the modern irrigation3 system in Quahir Michael and Shina PAs.
3 Modern irrigation locally means type of irrigation in which water is diverted from river or spring
development through concrete canal.
24
Figure 2: Guanta river dam
The river is diverted by cement concrete canal for irrigation purposes.
According to BOWR (2005), it was constructed in 2003 by the Amhara Regional state
water works. The diversion site is located at 11045
′22″ N latitude 37
047
′ 17
″ E
longitude. The canal river diversion water is used for irrigation, for drinking livestock
and other household consumption. The command area of the scheme is 46 hectares of
land and serves 91 households of which 85 are male and 6 female. Irrigation farming
has an advantage over livestock farming. According to Fogera district office of
agriculture (2010), 94% households have both crop and livestock. The borders around
the irrigation canal provide good grazing for livestock (picture 4).
25
Figure 3: Irrigation and livestock
The Guanta river diversion and Tanqua Gabriel spring development together
are used for irrigation by both Kuhir Michael PA and Shina PA. Kuhir Michael is
upstream of Shina. Both PAs have the same water use association. Irrigation occurs by
both gravity for lands at lower elevation and by a motor pump for land above the
canal. The amount of water in the irrigation canal is sufficient for both gravity and
motor pump irrigation and usually there is excess of water flowing back to the Gumara
River.
26
Figure 4: Motor pump irrigation from river diversion canal
In addition, the river diversion water is used for household consumption such
as drinking, washing and the like. The picture below shows the woman and the two
children fetching water for household consumption.
The other modern irrigation scheme is Eriza river diversion in Werota Zuria
(Figure 6). The river diversion dam was constructed by Co-SIRARE in 2003.The
irrigation potential of the scheme is 26 ha.
27
Figure 5: A women and Children fetch water from river diversion for household
consumption.
Figure 6: The river diversion dam on Eriza River in Werota Zuria
The amount of water is poor compared with Guanta and other spring water
sources. The amounts of land irrigated are comparatively low. The area is upland and
dry.
28
3.2.2 Spring development small-scale irrigation scheme
The two main spring development irrigation areas are Tanqua Gabriel and Timeket
Bahir in Quhir Michael and Bebekis PAs, respectively (Figure 7). The Tanqua Gabriel
spring development is constructed by ORDA and EMATLFA in 2001.The irrigation
potential of the spring is 70 hectares of land for 351 beneficiary households
Figure 7: Tanqua Gabriel spring development
The second spring development irrigation scheme is the “Timeket Bahir”
which means water used for Epiphany. The spring is used for religious purpose with
Ethiopian Orthodox Church. The scheme is developed from three perennial springs.
29
3.2.3 Motorized pump
Motorized pumps are widely used irrigation systems in the five PAs (Figure 8).
In Shina, for instance, there are 54 total pumps. Most of the farmers bought them as
part of a group. Other households gain access to the pumps through renting from the
owners. The Gumara, Rib and Eriza rivers are used for irrigation by using motor
pumps.
Figure 8: Motor pump irrigation using Eriza River near Werota town
3.2.4 Pedal pump
In the five PA, 295 households received pedal pumps from office of agriculture
and rural development on credit basis in 2006, 2007 and 2008. The amount of credit
required for each treadle pump was 350 ETB. Although the treadle pumps are highly
demanded by the farmers, there is an insufficient supply. These pedal pumps were
imported from India (Figure 9). They are lightweight and easy to operate. One key
problem is limited access to spare parts for repairs in the case of malfunction. In
30
addition, the suction and delivery hoses are easily damaged. Loss of integrity of the
joints around the foot press is another problem. At present, most of these treadle
pumps are non-functional.
Figure 9: Pedal pump
The Indian pedal pumps are regarded as superior to those made in Ethiopia due
to better pumping power. With Indian pumps, the water can be pumped long distances
through its long delivery hose.
The major water source for pedal pump is shallow wells. Shallow wells are
widely used water sources for irrigation and other household consumption (Figure 10).
There are 2378 shallow wells in Shina PA alone. There are households who have up to
eight wells. Most of the household‟s water consumption such as drinking, washing and
irrigation are obtained from shallow well. The depth of the wells is estimated in the
range of one to seven meters.
31
Figure 10: Sample wells constructed for only one cropping season
Very shallow wells that are one to three meters depth are dry during very dry
periods such as February, March and April. Wells that have a depth from four to seven
meters are perennial water sources. These shallow wells are extensively used by
farmers to irrigate small plots of land, by fetching water using buckets and jars. The
shallow wells are used for only one cropping season because during rainy season the
wells are damaged because the area is flood prone and dominated by Vertisols.
Figure 11: Sample of Vertisol
32
As a result, a common practice is for farmers to construct new wells each
cropping season. There are traditionally used mechanisms to avoid shallow well
failure. Some farmers use car tires or cylinders made from cement to construct the
well.
Figure 12: Well constructed from tire materials
This saves the wells from frequent failures. These shallow wells are
constructed by farmers themselves. The well water is used through jar and bucket
irrigation (Figure 12) in addition to the treadle pumps.
In general, all family members of the household are involved in jar and bucket
fetching irrigation from well water, but females are the main actors. Some households
use two or more shallow wells in one irrigated farm plot. The wells were constructed
in the boarders of the irrigable lands for ease of watering the irrigated crops (Figure
13).
33
Figure 13: Irrigation by fetching water from wells
Figure 14: Sample well constructed by cement cylinder
The commonly grown crops by fetching water from shallow well are tomato,
onion, cabbage, and lettuce.
34
3.2.5 Traditional river diversion
Traditional river diversion is the dominant method used by farmers in all five
PAs. This irrigation system is simple for farmers to practice by inheriting the
knowledge from grandparents but the amount of water and seasonality of rivers are
major problems. Many farmers use traditional irrigation to complement other
irrigation systems like modern river diversion and motor pump irrigations.
35
CHAPTER FOUR
4 MATERIALS AND METHODS
4.1 Research methods
4.1.1 Approach for data collection, entry and checking
Household data collection was undertaken in five villages that have irrigation
and non-irrigation water users. Data collection methods included a survey, semi-
structured interviews and focus group discussions. Data were collected at household
and community level with the assistance of development agents. Each PA has three
developmental agents who live and work with the farmers. Using development agents
as assistance for data collection is important for the reliability of the data because
farmers are more likely to report accurate information to development agents,
especially on income, land size and other taxable assets.
The sample households were selected by utilizing the following three-stage
stratified sampling procedure. The first stage involved consultation with Fogera
District Agricultural and Rural Development offices, and five PAs were selected
purposively on the basis of their similarity in agricultural practices, surface water
resource potential for irrigation, and the type of small-scale irrigation they used. In
the second stage, household lists in the selected PAs were obtained from village
administration and Development agents‟ office. The different types of small-scale
irrigating and non-irrigating households were selected from this list. In one of the five
PAs, Shina, all households are irrigation users in one way or another. No sample was
taken for non-irrigation user households in this PA. Proportional sampling method was
used to develop the sample.
36
In the final stage, households were listed by each small-scale irrigation
category then the random sampling technique was used to select sample households
from each household type using a random number table. The objective was to
carefully examine and compare the income and poverty level of small-scale irrigation
users and non-users.
Based on this multi-stage sampling process, the total sample households were
selected on a random sampling basis from five villages in Fogera District. Pervious
literature showed that an appropriate sample size is determined by number of factors.
As the number of factors increase, the sample size should also increase to avoid biased
results. According to Marks (1966), as cited in Green (1991) a minimum of 200
subjects should be used for any regression analysis, whereas Schmidt (1971)
suggested a minimum subject-to-predictor ratio ranging in value from 15-to-1 to 25-
to-1. According to Cohen (1988) if the research uses 15 predictors, the minimum
sample size is 138 and if the research uses 20 predictors, the minimum sample size is
156. Rao and Richard (2006) suggest that an appropriate sample size depends on the
type of problem investigated, required precision and to a certain extent, the resources
available. Following these guidelines, a total sample size of 180 households was
selected from the five villages with proportional samples size was taken from
irrigating and non-irrigating households (Table 1).
In addition to the structured survey, information was collected through focus
group discussions with the Fogera district agricultural office socio-economic and
irrigation experts, development agents and irrigating and non-irrigating farmers. Focus
group discussions were first held with model4 farmers who use small-scale irrigation.
4 Model farmer, in the context of this study, means a farmer who adopts modern irrigation technology
and earns a higher income from it.
37
A second discussion was with development agents. After thoroughly discussing the
problems and opportunities of irrigation development with farmers and development
agents, a focus group with Fogera district office of agriculture socio-economic experts
and irrigation experts was undertaken.
Table 1: Summary of sample size by PA and irrigation types
PA
Irrigating Non-
irrigating
Sample
per
PA
Concrete
canal river
diversion
Traditional
river
diversion
Motor
pump
Pedal
pump
Kuhir Mikael 6 4 4 4 22 40
Shina 8 0 8 8 0 24
Kokit 0 4 4 8 22 38
Bebekis 6 8 4 0 24 42
Werota Zuria 4 6 4 0 22 36
Sample
/irrigation 24 22 24 20 90 180
Another source of information for this study was key informants. The key
informants were selected by asking farmers randomly “who is your model farmer in
the PA with irrigation farming?” then the more frequently proposed farmers were
selected for key informants. In addition to this, local leaders and extension workers are
used in the selection of key informants. The same procedure was used in all PAs for
key informant selection.
The survey data were recorded and organized in a Microsoft Excel
spreadsheet. SPSS 16 software was utilized for data entry and editing. A print-and-
verify method of data entry checking was performed to avoid errors in the recording
process. The missing values, zeros and not applicable values were identified for
verification. Each variable was examined not only for outliers but also for the general
acceptability of the figures compared to national and regional information from other
sources. The inconsistent values were also checked with the questionnaire to identify
38
data entry errors. The database in SPSS then was converted to the STATA
econometric software format and further data editing was undertaken.
The household was used as the basic survey unit for the analysis. A household
was defined as a number of people living and eating together in the same dwelling and
share the same income. From November 2010 to February 2011, observation surveys
and interview of households were conducted. The interview was conducted over 54
days. Household heads were involved in responding the interview because household
heads are often make decisions concerning their households issue in the study area.
Twenty-eight rural and five urban PAs exist in Fogera District. Five PAs were
purposively selected on the basis of their similarity in agricultural practices, surface
water potential for irrigation, and the type of small-scale irrigation they used. The
different types of small-scale irrigating and non-irrigating households were collected
from the respective PAs at development agents‟ office. Irrigating and non-irrigating
households were proportional, 90 households from each category then total sample
size was 180 households. The respondents were selected randomly using a random
number table.
To collect the data, the survey questions were carefully translated in to the
local language (Amharic). This helped to convey the questions effectively to the rural
interviewees. The data collection assistants were selected and trained for one and half
days on administering and completing the questionnaire, and a pre-testing fieldwork
was also organized for half a day. On the basis of the pre-test feedback, some
adjustment was made on the questionnaire and the final questionnaire was organized.
The questionnaires (see Appendix B) have six main parts. These are:
1. Household demographic characteristics;
2. Resource endowments of a household;
3. The crop production from rainfed agriculture;
39
4. Crop production with irrigation;
5. Livestock production;
6. Credit, input and extension service supports in production;
7. Non-farm and off-farm income;
In order to characterize the selected small-scale irrigation systems, the major
problems encountered in relation with irrigation systems, the reasons why non-
irrigating households do not irrigate were developed using structured checklists. The
survey data initially were recorded and organized in a Microsoft Excel spreadsheet.
The data were then transformed to a database in SPSS (Version) for data entry and
editing. A print-and-verify method of data entry checking was performed to avoid
errors in the recording process.
The missing values, zeros and not applicable values were identified for
verification. Each variable was examined not only for outliers but also for the general
acceptability of the figures compared to national and regional values. The inconsistent
values were also checked with the questionnaire to identify data entry errors. The
database in SPSS then was converted to STATA format for analysis.
4.1.2 Data analysis
4.1.2.1 Socio-economic and demographic characteristics of the sample households
To estimate the impact of small-scale irrigation on income improvement and
poverty reduction, an assessment of selected socioeconomic and demographic
characteristics of the sample household is vital. Impact assessment of any
development intervention is methodologically difficult and complex task to undertake.
Ravallion (2005) and Baker (2000) argued that no single method should dominate the
impact evaluation of any development intervention but instead rigorous impact
40
evaluations should be open-minded in the choice of methodology. The most important
thing to do in impact evaluations is to derive robust and meaningful close proxies or
indicative estimates that are comparable between and within individuals or groups
based on the aims of a particular development intervention.
The effect of the irrigation on irrigation participating and non-participating
households will be evaluated using descriptive statistics and econometric modeling
that controls for other contributing factors. Households that did not use irrigation or
those who were living adjacent to the irrigation users and the different small-scale
irrigation scheme users will be used as the comparison group. To examine the impact
of irrigation on the household poverty status, gross income was used as the main
outcome of interest. In addition, various other socio-economic indicators were
examined.
The sample households‟ demographic characteristics indicate the various
characteristics of, and differences among, the study groups. For the socio-economic
analysis particular importance is given to age, sex, and education of household head,
family size, land holding, access and sources of credit, extension and market services.
These variables were analyzed using descriptive statistics such as average, percentage,
minimum, maximum and frequency distributions.
4.1.2.2 Income evaluation
To evaluate impact of small-scale irrigation on annual gross income of the
household, all sources of income such as agricultural (cropping and livestock) incomes
and non-agricultural (off-farm and other) incomes should be considered. The
examination of off-farm income in household gross income evaluation is valuable
because of the working hypothesis that non-irrigating households have larger off-farm
income than irrigating households. Non-irrigating households may use off-farm and
41
non-farm activities as compensation of irrigation. Therefore, considering of off-farm
and non-farm income avoided the overstated income share from irrigation activities.
To compare the annual mean income of the four different irrigation schemes, a
single factor analysis of variance (one way ANOVA) was used. When the four
irrigation schemes annual mean income comparison was computed, the ANOVA F
(sometimes called the overall F or omnibus F) were statistically significant, that
means there is a difference of variance (the assumption of equal variances has been
violated). Thus, post hoc Multiple Comparison tests, commonly known as follow-up
tests, were applied (Morgan et al. 2004).
To control for other factors that influence household incomes this study uses
an econometric modeling approach. As stated Nicholson et al. (2004) and Zhou et al.
(2009), household gross income is a function of many determinants including
household characteristics, asset holding, village location characteristics, and the prices
of goods and services.
Mathematically, this can be written as:
Y = f (X, D, Z, A, P) (1)
Where Y is an endogenous variable (household gross income), X is household
characteristics (education of household head, household family size, age of household
head and gender of household head), D is Irrigation access, Z is village characteristics,
A is the Value of household production assets, and P is the prices of agricultural
products and inputs.
In this study, the principal dependent variable is annual household income
(INCOMEHH), which includes agricultural income (cropping and livestock incomes)
and off-farm income. The values of agricultural incomes are computed by multiplying
the amount of each agricultural product (sold and consumed) with their annual average
price. A principal objective of this research is to examine the impact of irrigation on
42
annual gross income of household. The income data were collected during November
2010 to February 2011.
The independent variables were identified from previous studies and the nature
of the study area. These variables are expected to result in (and therefore, explain)
income variation across households in the study area (Table 2). The independent
variables are as follows:
• Access to irrigation (IRR): Irrigation supplements moisture, which enables
farmers to maximize agricultural production. It is assumed to have a direct
relation with the total income of a household. Nhundu et al. (2010), Hussain
and Biltonen, (2001) and Haile (2008) identified a strong positive relationship
between access to irrigation and household income. Access to irrigation for
household is a dummy variable, 1 if a household has access to irrigation and 0
otherwise.
• Cultivated land size (LANDSZ): total cultivated land is the total sum of the
household‟s own and/or rented in/out from/to other households and measured
in hectares. This does not include the grazing land and fallowing land.
Farmland is the major input for agricultural production in rural households.
Total cultivated land should have a positive relationship with income of a
household (Kamara et al. 2001).
• Family size of a household in adult equivalent (FAMSZADUL): family size in
adult equivalent of a household is calculated by using the conversion factor in
(Appendix-Table A2). A household family size in adult equivalent is
calculated by multiplying each household member with respective conversion
factor and then summing. Its size depends on the age of each family members
of a household. In rural households, family labor is the major input used in
agricultural production. Households with large family size in adult equivalent
43
have more labor for agricultural production. Family size in adult equivalent is
correlated positively is expected to positively affect total income and
negatively affect the probability of poverty for a household.
• Education (literacy) level of a household head (EDUHHL): Education has
paramount impact on income improvement and poverty alleviation. It is likely
that educated farmers would more readily adopt irrigation technologies and
may be easier to train through extension support. The variable entered in the
model as dummy variable with 1 if a household head can read and write, and
otherwise 0.
• The number of livestock owned in TLU (LIVESTO): This is a continuous
variable measured in terms of Tropical livestock unit (250 kg live weight) .The
number of livestock owned by a household in TLU is calculated by conversion
factor for Tropical Livestock Unit (TLU) (Appendix-Table A3). A household
livestock size in TLU is calculated by multiplying the number of each type of
animal by an appropriate conversion factor and then summing. Households
with higher livestock holding will lead to higher probability of getting excess
livestock for selling and hence generating additional income, particularly the
owner of more oxen lead to an ability of ploughing more land on time, thereby
achieving crop yields and earning higher income.
• Use of credit (CREDIT): This is a dummy variable with 1 for user and 0
otherwise. Access to credit is hypothesized as having a positive relationship
with income and negative relation with poverty. According to Norton et al.
(1970), credit helps farmers purchase inputs such as seeds, fertilizers and
chemicals.
• Productive asset holding (ASSETHH): This variable includes all assets that are
categorized under agricultural activities but different from land and livestock
44
resources. It is the continuous variable measured in ETB. The value of
productive assets is estimated by the household head considering the current
price and the salvage value of the asset. As indicated by Maddison A (1970),
as people accumulate physical capital, this allows the people to expand
production by changing the marginal productivity of inputs such as land and
labor. Therefore, households with more productive assets can produce more
and increase their total income. Household productive assets should influence
household total income positively and poverty level negatively.
• Gender of the household head (GENDEHH): This is a dummy variable with 1
for male and 0 otherwise. Male household heads are expected to have higher
income compared to female household heads because of better labor inputs
used in male-headed households.
• Age of a household head (AGEHH): Age is a continuous variable and
measured in years. In Ethiopia, household head is the decision maker for farm
activities. Age is one of the factors that determine decision making of a person.
Advanced aged household heads are more reluctant to accept new technology
and agricultural production styles than younger household heads. Thus, age of
household head is hypothesized to have negative contribution to household
income.
The relationship between household head age and total income of a household
is assumed to be a linear function, based in part on estimated equations.
• Dependency ratio of the household (DEPRATIO): The dependency ratio is
equal to the number of individuals aged below 15 and/or above 64 divided by
the number of individuals aged 15 to 64, expressed as a percentage (John
2002). Dependency ratio is important because it shows the ratio of
economically inactive compared to economically active. The dependency ratio
45
of agricultural households provides planners and policy makers with an
indication of agricultural labor availability in male and female managed
holdings and their abilities to actively participate in agricultural programs and
projects. Members of holdings with high dependency ratios might not be able
to participate in programs and projects due to time, labor and/or financial
constraints (FAO 2010), that is dependency ratio is thought to be negatively
related to income of households.
• Use of input (INPUT): the use of inputs influences household income from
crop production. The main inputs used in the study area are chemical
fertilizers, improved seeds and agricultural chemicals. Households who use
one or more of these farm production inputs will usually have higher crop
yields and hence higher income. Thus, a binary variable was specified with a
value of 1 for households that had used one or more of these inputs during the
previous cropping season, and 0 for households that had not used any of these
inputs during that time.
• Prices of inputs and outputs are among the exogenous variables that determine
the gross income of a household. However, the price of goods and services are
almost identical for all households in the study area. Therefore, price effects
cannot be determined and price information is not directly incorporated in the
model.
Following previous studies, the determinants of household gross income were
analyzed by multiple regression models. The model is of this form:
Y = α + D + δX+ σZ+ φA + ԑ (2)
Where α is an intercept, and δ, σ and φ are parameters to be estimated.
46
Table 2: Summary of dependent and independent variables codes, definitions and
expected sign of effect on household income
Variable Variables definition and measurements Expected
sign
INCOMEHH Annual household gross income in ETB Dependent
IRR Dummy variable for irrigation (1 = access to
irrigation, 0 = No access) +
LANDSZ Total cultivated land, hectares +
FAMSIZE Family size of a household in adult equivalent +
EDUHH Education of the household head (1 = read and
write, 0 = Does not read and write) +
AGEHH Age of a household head, years -
INPUT Use of production inputs
5(1 = use of inputs, 0
= No use of inputs) +
LIVESTO The number of livestock owned, in TLU +
DEPRATIO Dependency ratio of the household -
CREDIT Use of credit (1 = use of credit, and 0 = No use
of credit) +
ASSETHH Asset owned by household in ETB +
GENDEHH Sex of the household head (1 = male, and 0 =
female) +
Some households may not derive income from livestock, off-farm and other
activities; therefore in this study, the impacts of irrigation on income were estimated
using a Tobit model. This approach was developed by Nobel laureate economist James
Tobin in 1958 for analyzing situations whenever dependent variable can take zero
values. There are many previous studies with similar works (Nicholson et al. 2004;
Zhou et al. 2009; Aschalew 2009; Barket et al. 2002).
The specific form of the Tobit model is described as follows:
Yi* = βX‟i + ԑi (3)
We define a new random variable Y transformed from the original one, Y*, by
Y* = 0, if Y (3a)
5 Use of input means the application of one or more agricultural inputs such as chemical fertilizer,
improved seed, chemicals (pesticide, herbicide) in the last one cropping season.
47
Y* = Y, if Y (3b)
And where Yi is the observed dependent variable measuring combined livestock
income, off-farm income, cropping income and household total income, Y* is a latent
variable, X is a vector of explanatory variables that influence incomes , β is a vector
of parameters to be estimated, and ԑ is a random disturbance term with mean 0 and
variance σ2.
On the basis of the Tobit model specification, the unknown parameters of the
explanatory variables can be estimated by maximizing the corresponding likelihood
function.
Where Yi is the income of a household, Xi „ is an explanatory variables create
influence on household income, � is a coefficient of the independent variables, � is
the normal density function, � is the normal distribution function, σ2 is the variance of
the error term epsilon in the third equation.
The coefficients of dependent variables in Tobit model are not directly
proportional with change of the independent variable. Therefore, to understand the
change of household income as a result of a unit change of the coefficient of
independent variables, the estimators of the variables should be transformed in to the
vector of first derivatives.
The marginal effect in Tobit model illustrate that the change of the dependent
variables as a result of the changes of respective independent variable (Xi) by a unit.
On the basis of the above Tobit model specification. The marginal effects of the
independent variables on household income are represented as:
48
The marginal value identifies the direct impact of irrigation on household income. The
hypothesis of that irrigating household have higher income than non-irrigating
household is tested by the sign of the marginal effect of the irrigation access variable
(D, if significant) and the magnitude indicates the size of the impact. That is, it fulfills
a main aim of this study to analyze the marginal effect of irrigation on irrigating
households income compared with non-irrigating households income being other
things constant. This helps policy makers to understand the value of future irrigation.
4.1.2.3 Poverty level evaluation
Poverty is a multidimensional concept and its definition and measurement has
been the subject of much debate. The household poverty line often is represented as a
very basic living standard. Poverty indicators are often constructed by comparing
household income with the mean income or median income (midpoint). Poverty
usually is analyzed on the basis of income or consumption indicators. The World Bank
uses poverty line of one dollar (PPP6-adjusted) per day, but this has been criticized for
being too narrow. According to Nilsson et al. (2010), there is no obvious best way to
calculate measures of absolute purchasing power that are comparable both across time
and space when relative prices vary both over time and between countries. The World
Bank estimates rely heavily on household surveys, resulting in questionable
6 PPP (purchasing power parity) means the application of one price across countries for all goods and
services, or representative groups (baskets) of goods and services.
PUS = ( EUS$/ETB$) x (PETB)
PUS = Price of goods in USA
PETB = Price of goods in Ethiopia
EUS$/ETB$ = US dollar/Ethiopian birr exchange rate.
49
comparability and low coverage for certain regions such as Sub-Saharan Africa. Thus,
one approach to poverty definition is to use a relative poverty approach, based on the
characteristics of households in the sample
Following pervious literature, combined sample households (both irrigating
and non-irrigating) are ranked according to their current income. This ranking is then
used to determine which quartile a household is in based on current income. The
households in the lower quartiles are relatively poor whereas those in the upper
quartiles are relatively well off.
On the basis of previous studies (e.g., Simtowe et al. 2010), a working
hypothesis is that more of non-irrigating households will be in the lowest-income
quartile. In addition, it is expected that the low-income quartile households have a
lower mean share of income from crop production than households in the higher
income quartiles, but a larger mean income share coming from livestock compared to
households in larger income quartile. The low-income quartiles are also expected to
have a larger income share from non-farm activities compared to households in the
upper quartile.
4.1.2.4 Poverty Line
Although the relative poverty approach has some advantages, it is also possible
to develop more specific absolute poverty, typically defining a somewhat arbitrary
“poverty line” on the basis of income or consumption indicators. Previous authors
have used different definitions. Ethiopia has not established any official poverty lines,
so Schreiner and Chen (2009) used the international poverty lines in dollars at 2005
purchase-power parity, with the lowest of their thresholds at $ 1.00 per person per day.
According to Dercon (1997), the threshold for absolute poverty is $ 0.45 per day per
50
adult (or access to 2200 calories per adult per day) and the moderate poverty level is
$0.60 per day per adult (2750 calories per adult per day).
In this study, the poverty line is determined on the basis of current income
because detailed consumption data were not available. Using the dollar amounts and
the recent dollar to ETB exchange rate, the absolute and moderate poverty lines are
ETB 3,073 and ETB 3,687 per person in adult equivalent per year, respectively. For
the purposes of this study, the absolute poverty line is the value of current income at
the twenty-fifth percentile for sample households (3,225 ETB per person in adult
equivalent per year) and the moderate poverty line is defined as the value of the
thirtieth percentile of current incomes (ETB 3,457 per person in adult equivalent per
year). These values are reasonable close to those described by Dercon, and are
consistent with income and food poverty prevalence of 29.2 and 28.2 %, respectively,
in recent years (MOFED, 2010). However, both the absolute and moderate poverty
lines defined are below the World Bank‟s poverty line set at one dollar per day per
adult, which would be ETB 6,231 per year per adult at current exchange rate ($1 =
ETB 17.07). Using the official exchange rate in the National Bank of Ethiopia, the
absolute poverty line ETB 3,225 per year per adult is approximately $189/adult/year.
The estimated moderate poverty line for the study area is ETB 3,457 per year per adult
is approximately $202/adult/year.
4.1.2.5 Poverty level comparison
The poverty level comparison between irrigating and non-irrigating households
is valuable to estimate the impact of irrigation on poverty reduction. Poverty level
comparison helps to estimate the extent of irrigation‟s impact on rural poverty
alleviation. Poverty level comparisons between irrigating and non-irrigating
households use the following poverty measures developed by Foster et al. (1984):
51
Where Pα is the poverty level indicator for a sample of households, m is the number of
households below the poverty line, n is the number of households, z is poverty line
yi is income per adult equivalent of ith
household, α is the poverty sensitivity parameter
that can take on a variety of values. When α = 0, the result is the prevalence of
poverty or the head count ratio, that is the proportion of people falling below the
poverty line. When α = 1, the equation gives the depth of poverty. It is also called
poverty gap index. This shows the amount of income necessary to bring everyone in
poverty up to the poverty line, divided by total population. This can be thought of as
the amount of income that an average person in the economy would have to contribute
for poverty to be eliminated.
4.1.2.6 Econometric model specification
Assessing the impact of irrigation on the likelihood that a household is in
poverty is one of the objectives of this study. Thus, poverty is the dependent variable,
and is determined by independent variables such as irrigation, household
characteristics, asset holdings and access to services (Table 3). In this analysis, the
independent variable is binary (1 if the household is classified as poor when its annual
income is in the lowest quartile, and 0 if the household is classified as non poor).
Under this limited dependent variable model, the probability that the i th
household is
poor is given by:
Prob (y = 1│X) = F (Xi, β) (7)
Where Zi is a function of explanatory variables (Xki), and expressed as:
Zi = β0 + β1X1i + β2X2i+ β3X3i + β4X4i +… βkXni + μi (7a)
Where μi = error term.
52
If Pi is the probability of the ith
household is being poor, then (1-Pi) is the
probability of not being poor. Since the dependent variable, poverty, is unobserved
and the resulting model is nonlinear, it cannot be estimated by using OLS so
maximum likelihood can be used. Green (2002) indicates that either Probit or Logit
models are mainly used for the dependent variable that takes dichotomous values (e.g.,
yes or no) or a choice between two alternatives. Both the Logit and Probit models
guarantee that the estimated probabilities lies in the range 0 to 1 and that they are non-
linearly related to the explanatory variables. Following Habitamu (2009) and Haile
(2008), the dichotomous dependent variable poor/non poor is estimated by Logit
model, for the sake of its mathematical convince.
The probability of being poor can be expressed in binary choice models or a
logistic distribution function as:
(8)
Where: exp (the value of e), the base of natural logarithm.
Table 3: Summary of the dependent and independent variables, codes, definitions and
expected signs.
Variable
code Variables definition and measurements
Expected
sign
Poverty Probability to being poor (1 = poor, and 0 = non-
poor) Dependent
IRR Dummy variable for irrigation (1 = access to
irrigation, 0 = No access) -
LANDSZ Total cultivated land, hectares per capita. -
FAMSIZE Family size of a household in adult equivalent -
EDUHHL Education of the household head (1 = read and
write, 0 = Does not read and write) -
AGEHH Age of a household head, years +
INPUT Use of production inputs (1= use inputs, 0 = No
use of inputs) -
OXEN The number of oxen owned, in TLU per capita -
DEPRATIO Dependency ratio of the household -
53
CREDIT Use of credit (1= Use credit, 0= Does not use
credit) -
ASSETHH Asset owned by household in ETB per capita -
GENDEHH Sex of the household head (1 = male, and 0 =
female) -
For the nonlinear dependent variable, the marginal effect of each independent
variable is not straight forward to interpret. In the Logit model the marginal effect of
each independent variable on poverty should be transformed to Log odds ratio
coefficients. Therefore, the regression equation of the odds ratio is:
The Log odds ratio shows change of the probability that a household is being
poor/non-poor if the independent variable (Xi) changes by one unit. The statistical t-
tests, chi square, minimum, maximum and percentages were done by Statistical
Package for Social Science (SPSS) for Windows Release (SPSS, Inc., Chicago,
Illinois). The income and poverty analyses were done by STATA/SE 10.0 for
Windows (Stata Corp LP, College Station, Texas USA) software was used for data
processing.
54
CHAPTER FIVE
5 RESULTS AND DISCUSSION
5.1 Household Socio-economic characteristics
This section describes the analysis of survey data and its interpretation. In the
first section, the sample households‟ demographic characteristics are discussed.
Particular reference is given to the factors hypothesized to influence income, such as
family size, education level, land holding, asset holding, labor availability, access and
source of credit for irrigating and non-irrigating households. These descriptive
analyses help to frame the econometric results obtained in the study.
5.1.1 Family size
Family size is useful for formulating various development plans and for
monitoring and evaluating their implementation. Average family size at the national
level in Ethiopia was 4.7 (CSA 2007). In the study area, the average family size was
5.93 with a minimum 2 and maximum of 11. The t-test shows that there is significant
difference in family size between the irrigating and non-irrigating households at a 5%
level of significance (Table 4).
Table 4: Family size, family labor and dependency ratio for irrigating and non-
irrigating households
Characteristics
Irrigating
households
(N=90)
Non-Irrigating
households
(N=90)
Total
Households
(N=180)
t-value for
difference
Family size,
persons 6.3 5.6 5.9 2.5
**
Family size in AE
(family labor) 4.9 4.3 4.6 3.1
***
Dependency ratio 1.5 1.4 1.4 0.6
***, ** indicate significant at the 1% and 5% significance levels, respectively
55
5.1.2 Family labor
In rural Ethiopia, household family is the main source of labor for all income
sources. Family size in adult equivalents indicates the sample households‟ average
family labor force for agricultural production and other income-generating activities.
The average family size in adult equivalents in the study area was 4.62 with a
minimum 1.74 and maximum of 8.24. The t-test shows that there is significant
difference between irrigating and non-irrigating households at 1 % level of significant
(Table 4). Thus, irrigating households have owned better labor input than non-
irrigating households.
5.1.3 Dependency ratio
The dependency ratio shows the ratio of economically inactive compared to
economically active. Economically active members of a household, whose age is from
15 to 64, are assumed to be the principal sources of income for the household.
Household members under 15 and over 65 are assumed to be economically inactive
and dependent on economically active members of a household for education, clothing
and health care (John 2002). The dependency ratio of agricultural households provides
planners and policy makers with an indication of agricultural labor availability in
male- and female-managed holdings and their abilities to actively participate in
agricultural programs and projects. Members of holdings with high dependency ratios
might not be able to participate in programs and projects due to time, labor and/or
financial constraints, that is, dependency ratio is thought to be negatively related to
income of households (FAO 2010). In the study area, the average dependency ratio
was 140 %, which means every 100 economically active persons had 140 extra
persons to feed, cloth, educate and medicate. Economically active members (45
56
percent) were less than non-active household members (55 %). This can have
important implications for poverty alleviation efforts. No statistically significant
difference was observed between irrigating and non-irrigating households for the
dependency ratio (Table 4).
5.1.4 Sex and education of the household head
In the study area, the head of the household generally is responsible for the co-
ordination of the household activities. As such it is pertinent to examine attributes
such as sex and education of the head as one component of irrigation participation
decisions. Of the 180 sampled households, about 88% were male-headed. The
percentage of non-irrigating female household heads was more than irrigating (Table
5). There is a significant difference in the sex of the sampled household heads for
irrigating and non-irrigating households at a 5 % significance level (Table 5).
Economic growth is driven by change in people‟s capabilities or their human
capital, as affected particularly by their education. Educated people can more easily
contribute to the generation of new technologies and more readily utilize those
technologies. It is one of the main factors affecting adoption of irrigation technologies
to improve agricultural productivity (Maddison et al. 1970). The education level of
household heads is higher for irrigating households than non-irrigating households
(Table 5).
57
Table 5: Household member, gender, and education and age characterization
Characteristics
Irrigating
households
(N=90)
Non-
Irrigating
households
(N=90)
Total
households
(N=180)
Chi-
square test
for
difference
Percent Percent Percent χ2
Household head gender
Male 93 83 88
Female 7 17 12
Total 100 100 100 4.4**
Household head education
Illiterate 21 65 43
Read and write 48 23 35
Elementary complete 27 11 19
Junior complete 3 1 2
High school and above 1 0 1
Total 100 100 100 24.7***
Age of household head
15-30 years 17 14 16
31-45years 53 47 50
46-64 years 28 34 31
65 and above 2 5 3
Total 100 100 100 1.9
***, ** indicate significant at the 1% and 5% significance levels, respectively.
5.1.5 Age of household head
The average age of the household heads in the study area was 42 years with a
minimum of 24 and maximum of 78 years. The age of the household head influences
whether the household benefits from the experience of an older person, or has to base
its decisions on the risk-taking attitude of a younger farmer. There is no significant
difference in the distribution of household head age of the sampled households
between irrigating and non-irrigating household heads (Table 5).
5.2 Productive resource
Agricultural production requires resources such as labor, natural resources,
agricultural tools and other capital assets. In the foregoing sections, it has been
58
discussed that household income has a critical link with access to productive resources
such as labor, land, oxen and agricultural assets. Therefore, the study looks the access
of these resources between irrigating and non-irrigating households. Knowing this
helps to judge irrigation‟s impact on household‟s income difference.
5.2.1 Land holding
Land is the major productive asset in agrarian countries like Ethiopia.
Cultivated land appears to be the most important scarce factor of production. In the
study area, own land, rented and shared lands were used for cultivation. The average
land holding size of the sample households in the study area is 1.1 ha, which is
comparable to the national land holding of 1.0 hectares. There is no significant
difference between irrigating and non-irrigating households in average land holding
size (Table 6). Thus, the overall land holding per household among the study group is
similar. However, there is a significant difference in their cultivated land size.
Irrigating households have larger cultivated land area than non-irrigating households.
Irrigation may generate income and allow accumulation of other productive assets by
irrigating households, which facilitate cultivation of additional land through share in
and rent in (Table 6) from non-irrigating households.
The average grazing land for irrigating and non-irrigating households was 0.21
and 0.16 hectares, respectively. Irrigating households also use more grazing land than
non-irrigating, and the difference between them is statistically significant at the 1 %
significance level.
Sharing of farmland from any other households is commonly practiced in the
study area. Share in of farmland is practiced by 70 % and 40 % of irrigating and non-
irrigating households; respectively. Irrigating households share in more farmland
compared with non-irrigating households, whereas sharing out of farmland was done
59
by only 12 % and 21% for irrigating and non- irrigating households, respectively.
Non-irrigating households share out more their own farmland compared with
irrigating households (Table 6). Irrigating household participation was higher for land
share in but less for land share out. The converse is true for non-irrigating households,
which may be due to the fact that irrigating households have better potential to
cultivate additional land than non-irrigating households. The proportions of
households, who share in, share out and rent in were 62 %, 16% and 15%,
respectively. The share in, share out and rent in land size were 0.28, 0.09 and 0.07 ha,
respectively.
Table 6: Average landing size (ha) at household‟s level
Characteristics
Irrigating
households
(N=90)
Non-
Irrigating
households
(N=90)
Total
households
(N=180)
t-value
for
difference
Land holding 1.10 1.00 1.10 1.5
Cultivated land 1.10 0 .80 1.00 4.4***
Grazing land 0.21 0.16 0.19 2.1**
Land share in 0.36 0.21 0.28 2.8***
Land share out 0.05 0.14 0.09 -2.4**
Land rent in 0.09 0.04 0.07 0.8
Land rent out 0.00 0.001 0.001 -
Fallow and woodlot
land 0.19 0.14 0.16 1.8
***, ** indicate significant at the 1% and 5% significance levels, respectively.
Rent in of farmland is practiced by 21% and 11 % of irrigating and non-
irrigating households, respectively. The mean rented in farmland from any other
household for both irrigating and non-irrigating households were 0.09 and 0.04 ha,
respectively. Non-irrigating household (7%) participates in rent out of their farmland
whereas irrigating households did not rent out any farmland. Irrigating household
participation was higher for land share in but less for land share out. The other type of
land tenure is fallow and woodlot (Eucalyptus tree and other perennial crops) land.
60
The average fallow and woodlot land size of the sample households 0.16 ha, which is
0.19 and 0.14 ha for irrigating and non-irrigating, there is no significant difference
between them.
5.2.2 Effect of irrigation on land rent value
In Ethiopia land is a public property. Sale of land is not allowed, but land
rental and sharing through agreement between users for one or two cropping seasons is
common in the study area. The rental value of the land depends on the quality of the
land and the access to irrigation.
The average rental values of land accessed with irrigation and land without
access to irrigation were ETB 5,816 and ETB 2,867 per ha per one crop season,
respectively. This is consistent with the hypothesis that irrigation increases the value
of net returns to land. Households who have farm plots with access to irrigation water
thus will have higher incomes per ha from land rent (Table 7).
Table 7: Average land rental rate
Characteristics Land accessed
for irrigation
Land not
accessed for
irrigation
t-test for
difference
Land rental rate,
ETB/ha 5,816 2,867 3.9***
*** indicates significant at the 1% significance level.
5.2.3 Production assets
Agricultural production assets include motor pumps, treadle pumps, plough sets and
equipments necessary for agricultural activities. The production assets for irrigating
and non-irrigating households are valued by considering the salvage value of each
asset. As mentioned in the literatures review section of this paper, irrigation
61
development has several benefits and roles, one of these benefits are increasing wealth
of households. Irrigating households have, on average, more agricultural production
assets than non-irrigating households (Table 8). This difference is statistically
significant at the 1 % significance level.
Table 8: Mean value of agriculture production assets at household‟s level
Characteristics
Irrigating
households
(N=90)
Non-
irrigating
households
(N=90)
Total
households
(N=180)
t-value for
difference
Production assets,
ETB 2,362.6 771.8 1,567.2 5.1***
*** indicates significant at the 1% significance level.
5.2.4 Type of houses
Types of housing are an indicator of improving the well-being of rural
households. In rural Ethiopia most of the houses are grass-roofed, but wealthier
households will have a corrugated iron roof. A higher percentage of irrigating
households in the sample had corrugated iron roofed houses than non-irrigating
households, but statistically there is no significant difference (Table 9).
Table 9 : Housing types in samples households
Housing types Irrigating
Non-
irrigating Total
Chi-square
for difference
Percent Percent Percent χ2 test
Grass roof 23 30 27 Corrugated roof 77 70 73 Total 100 100 100 0.46
5.3 Major crops grown using small-scale irrigation
The crops grown without irrigation (rainfed) in the study region are teff,
barely, wheat, maize, finger millet, rice, oat, vetch, check pea, onion, tomato, potato
62
and pepper. In addition to their rainfed cultivation, irrigating households produced
cash crops for the second round within a year in dry periods using irrigation water.
The main field crops grown using small-scale irrigation schemes in the study region
are maize, oat, rice and vetch and the dominant vegetables are onion, tomato, potato
and pepper. The first main crop season is from June to November. In this period both
irrigating and non-irrigating households produced rainfed crops. The second crop
season is practiced in dry seasons from December to April. In this cropping season,
only irrigating households can cultivate using water from irrigation. Access to
irrigation has been regarded as a powerful factor that provides a greater opportunity
for multiple cropping, cropping intensity, and crop diversification (Saleth et al. 2003).
Households who have access to small-scale irrigation can cultivate twice a year. Thus,
irrigation increases the intensity of cropping. The most common field crops (cereals)
produced by small-scale irrigation are maize, oats, and vetch whereas the most
commonly produced irrigated vegetables are onion, tomato and potato (Table 10).
Table 10: The major field crops and vegetables grown using small-scale irrigation
Crop types Obs. Percent of irrigating
households growing Field crops (Cereals)
Maize 19 21 Oats 15 17 Vetch 4 4 Maize and Oat 7 8 Three or more crops 6 7
Vegetables Onion 46 51 Tomato 6 7 Potato 2 2 Onion and Tomato 18 20 Three or more 9 10
In field crop (cereal) cultivation using small-scale irrigation, maize was the
dominant. It is grown by 21 percent of irrigating sample households. Oats and vetch
are the second and third major field crops, grown by 17 % and 4 % respondents,
63
respectively (Table 10). Vegetables were the more commonly produced crops with
small-scale irrigation systems. The most frequently grown crop was onion, grown by
51 % of irrigating sample households. Onion is better than other vegetables in terms of
amount of yields produced and demand in the market, but requires frequent watering.
Therefore, onion irrigation with scarce surface water access areas like Werota Zuria
has lower yields compared with areas with more water resources, such as Quhir
Michael and Shina. Tomato and potato were less commonly produced than onions.
Twenty percent of respondents grew both onion and tomato, whereas 10% of
households produced three or more vegetable crops.
Crops grown using small-scale irrigation were few in number (Table 10), but
there are different reasons why they are grown by irrigating households. The major
factors for production decision were good production (50 %), better price (24%) and
easier to cultivate (24%). There are other reasons such as disease resistant, seed
availability; water scarcity and others accounted 16 % of the respondents (Table 11).
Table 11: Reason for selecting the major field crops and vegetables for irrigation
Reasons Obs. Percent of irrigating
households responding
Good production 45 50
Better price 22 24
Easier to cultivate 9 10
Two or more reasons 15 16
5.4 Household income evaluation
Household gross income is derived from agricultural (crop and livestock) sales
and value of crops and livestock products retained for household consumption7. The
value of retained crop and livestock products was calculated using annual average
nominal prices. In the case of irrigating households, individual household cropping
7 Thus, this is a “full (gross) income” value rather than a “cash (gross) income” value.
64
income was computed from both rainfed and irrigated crops but for non-irrigating
households, cropping income was derived from only rainfed crops. The off-farm and
non-farm incomes were also computed as part of gross household income. The main
reason is to examine the hypotheses that irrigating households‟ income was greater
than non-irrigating. Non-irrigating households may use off-farm activities to
compensate for their lack of irrigation. Therefore, to evaluate the income difference
between irrigating and non-irrigating households due to irrigation, the study considers
the off-farm and non-farm incomes. In the hypothesis, irrigating households have
higher income than non-irrigating households due to access of irrigation. Non-
irrigating households may have better income in off-farm and non-farm activities as a
compensation of irrigation then considering all income sources are important to
evaluate impact of irrigation on household gross income.
5.4.1 Cropping incomes
The most common crops grown in the study area are onion, rice, maize, vetch,
teff, finger millet, barley, oat, chickpea, onion, tomato, potato and pepper (Table 12).
These crops are grown as staple and cash crops in the study area. The estimation of
crop income uses taking the mean annual average price for both the sold and home-
consumed crops.
The major income source crops for irrigating households were onion (35%),
rice (17%) and oats (12%) whereas for non-irrigating households were rice (25%),
wheat (13%) and finger millet (12%). Onion and rice were the two main sources of
income from crops in the study area. The mean income difference shows that
irrigating households were better off in all cropping income than non-irrigating
households except wheat and pepper. The largest income was from onion produced
using small-scale irrigation. This suggests that small-scale irrigation development
65
increases the incomes of rural household because it directly influences the highest
income source, cropping.
Table 12: Major crop types and their mean annual production values
Major
crop
types
Ave.
annual
price,
(ETB
/100kg)
Irrigating households Non-irrigating
households t-value
for
difference
in
produc-
tion value
Produc-
tion value,
000 ETB
Percent
of total
crop
income
Produc-
tion value,
000 ETB
Percent of
total crop
income
Teff 626 1.5 5 1.5 11 0.7 Barley 317 0.4 1 0.3 2 0.6 Wheat 463 0.5 1 1.7 13 0.5 Maize 340 1.6 5 1.2 9 1.1 Finger
millet 289 1.6 5 1.6 12 1.0
Rice 629 5.5 17 3.3 25 2.5** Oat 573 4 12 1.4 11 2.3**
Vetch 330 1.2 4 0.8 6 2.4* Check
pea 385 0.6 2 0.6 5 1.5
Onion 473 11.4 35 0 0 6.1*** Tomato 237 3.2 10 0 0 2.1*** Potato 222 0.3 1 0.4 3 0.6 Pepper 1663 0.4 2 0.4 3 0.9 Total - 32.3 100 13.4 100 6.6***
***, **,* indicate significant at the 1%, 5% and 10% significance levels, respectively.
5.4.1.1 Rainfed cropping income
Rainfed crops were cultivated by both irrigating and non-irrigating households.
But, unlike irrigating households, non-irrigating households depend only on rainfed
cultivation. The major reasons for non-irrigating households not irrigating were lack
66
of surface water access8 in their farm plot (85%), lack of financial capital (8%) and
labor (7%) (Table13).
Table 13: The reasons for non-irrigating households for not irrigating
Reasons Obs. Percent of non-
irrigating households
No surface water access 77 85
Shortage of money 7 8
Shortage of labor 6 7
Total 90 100
Lack of surface water access was the most important limiting factor; however
the literature indicates that the groundwater table is high in the study area (Johnston et
al. 2010 and Girum 2010). Thus, in addition to surface water, groundwater based
irrigation development might be given additional consideration as a means of
irrigation development in the study area.
The mean annual income from rainfed cropping was ETB 14,189 (Table 14).
Statistically, there is no significance difference between irrigating and non-irrigating
households in their mean annual rainfed income.
Table 14: Rainfed income for irrigating and non-irrigating households in ETB
Characteristics
Irrigating
households
(N=90)
Non-
irrigating
households
(N=90)
Total
households
(N=180)
t-value for
difference
Rainfed income 15,011 13,366 14,189 1.15
5.4.1.2 Irrigated crop income in PAs
The average irrigated land size 0.65 ha per household with a minimum of 0.12
ha and a maximum of 2.75 ha. The major irrigated crops in the study area are onion,
8 Lack of surface water access means the farm plots of a household were topographically inaccessible
with irrigation water from river, pond, lake or any surface water.
67
tomato, maize, oats and vetch. The mean annual cropping income from sample
irrigating households was ETB 17,271 (Table 15).
Table 15: Income from irrigated crop production in ETB
PA Obs. Mean Std.
dev. Minimum
Maximu
m F-test
Werota Zuria 14 9,730 9,072.2 649 34,967
Bebekis 19 17,213 12,074.7 920 41,037
Kokit 14 9,609 9,168.3 1,060 29,240
Kuhir Michael 19 30,704 26,198.0 1,531 80,380
Shina 24 15,550 12329.9 2,114 48,086
Total 90 17,271 17011.5 6,49 80,380 5.3***
*** indicates significant at the 1% significance level.
The PAs with higher mean income from irrigated crop production were Kuhir
Michael, Bebekis and Shina, respectively. These PAs use concrete river/spring
diversion for irrigation water. Kuhir Michael and Shina were upstream and
downstream of Guanta river diversion and Tanqua Gabriel spring development. The
amount of water for irrigation was high in these PAs. In addition to Guanta and
Tanqua Gabriel diversion water, Kuhir Michael used Gumara river and Shina used
both Gumara and Rib river. In addition to this, Kuhir Michael and Shina have water
use associations. The association has multiple purposes; some of them were avoid
conflicts and irrigation water theft, used as a source of market information, supply
farm inputs for member households, protect and amend river diversion canal when
damaged. Thus, these PAs have better irrigation water use system and can earn better
income from irrigation farming.
Werota Zuria has the lowest income from irrigated crop production. The only
water source for the PA is Eriza River; the amount of water was low during flowering
period of irrigated crops during January and February. Water scarcity was the main
problem in the PA. On the upper part of this river, there is concrete canal river
diversion but the amount of water became declined at peak irrigation season, which
68
caused a conflict between the upper and lower stream user of the river. Therefore,
water scarcity was the main cause for low income from irrigated crop production.
5.4.1.3 Total cropping income
Total cropping income is the amount of mean annual income of a household
obtained from both types of cropping systems, rainfed and irrigation. The mean annual
income of a household from cropping income in the sample PAs was ETB 22,824
(Table 16).
Table 16: Total mean annual cropping income at household level in ETB
Characteristics
Irrigating
households
(N=90
Non-
irrigating
households
(N=90)
Total
(N=180)
t-value for
difference
Mean annual
cropping
income
32,282 13,366 22,824 7.7***
*** indicates significant at the 1% significance level
The total mean annual cropping income of irrigating households was
substantially higher than that for non-irrigating households. The t-test shows that there
is a significant difference between irrigating and non-irrigating households at 1% level
of significance (Table 16). This suggests that irrigation markedly increases income,
but this will be more appropriately tested using econometric analysis.
5.4.2 Livestock income
The type of agriculture in the study area is settled agriculture with a mixed
farming system (i.e., integrated crop and livestock production). Livestock are the most
important productive assets in the household. In the study area, livestock are important
source of power for ploughing, transportation, and riding. Livestock also consolidate
the social organization as they serve in payment for blood compensation and gifts for
69
relatives. They play role in religious and cultural ceremonies and serve as source of
prestige. It also considered as a saved asset used during periods of food shortage. The
average livestock holding for sample households was 4.02 TLU. Irrigating households
possess a larger average number of livestock (4.89) than non-irrigating households
(3.15). There is a significant difference between irrigating and non-irrigating
households at the 1% significance level (Table 17).
Table 17: Number of livestock (TLU)
Characteristics
Irrigating
households
(N=90)
Non-irrigating
households
(N=90)
Total
(N=180)
t-value for
difference
Average number of
livestock (TLU) 4.89 3.15 4.02 5.4
***
*** is significant at the 1% significance level.
Livestock play a significant role as income sources in rural poor Ethiopia. Sale
of live animals and their products are main livestock-related income sources in the
study area. The livestock income category includes income from the sale of livestock,
livestock products (i.e. milk, eggs, honey etc.) and other by-products like hide and
skin. The values of sale and own consumption livestock and livestock products were
estimated based on the average annual nominal prices. The livestock products were
collected on a weekly basis, and converted to estimate annual income (Table 18).
The highest mean livestock income among the study PAs are reported in Shina.
Livestock farming system in the study areas is free grazing on communal grazing
lands. The high livestock income in this PA was due to better communal grazing land.
The PA has high water potential. The two major rivers in Tana basin, Gumara and Rib
pass on the PA. The borders of these rivers are rich in livestock feed resources. On the
other hand, the PA also contains more irrigated areas than other PAs. In addition to
high surface water access, the groundwater table is high so all sample households are
irrigation users. From focus group discussions and key informant interviews because
70
the people have enough food from irrigated and rainfed cropping, animals are not
being sold to get food. Therefore, each household has high livestock numbers and
livestock income.
Table 18: Average annual livestock income
PA Obs. Mean Std.
deviation Minimum Maximum F-test
Werota Zuria 36 3,822 3463.9 0.0 12,388
Bebekis 42 1,105 1277.3 0.0 5,622.4
Kokit 38 2,472 3343.4 0.0 18,992
Shina 24 5,377 4894.1 580.6 20,462.8
Total 180 2,783 3348.5 0.0 20,462.8 8.6***
*** is significant at the 1% significance level.
The second highest mean livestock income is reported in Werota Zuria. The
average livestock income was ETB 3,822 with a minimum of 0 and a maximum of
12,388. Werota is the capital town of the district. Because there are hotels and
restaurants in the town, demand for livestock products like milk and egg was high,
which encourages households to produce more. In addition to this, crosses of the
Fogera dairy cow breed with exotic dairy breeds, especially Holstein, were common in
the PA. There are households who practice intensive dairy and fattening farming in the
area.
The lowest mean income from livestock is reported in Bebekis. On average,
the livestock income was ETB 1105 with a minimum of 0 and a maximum of 5,622.
The PA is an upland area with poor livestock feed resources. The community is also
relatively poor. Most of the household members in this PA are employed in other PAs
as daily laborers. They sell their livestock frequently to purchase grain, so their
livestock holdings and livestock income was low.
The mean livestock income for irrigating and non-irrigating household was
ETB 3,232 and ETB 2,440, respectively. Irrigating households had larger livestock
income than non-irrigating households, but statistically there is no significant
71
difference. The overall mean income of livestock in all sample households is ETB
2,783 with a minimum of 0 and a maximum of 20,463. This indicates that livestock
farming is another of the major income sources of the study area. There is a significant
difference among sample PAs at the 1% significance level (Table 18).
5.4.3 Off-farm and other incomes
Off- farm and other incomes are important parts of total income in rural
households of Ethiopia. They are significant for purchasing power and food security.
Petty trading was one source of off-farm income in the study area, for instance, onion
and tomato trading in Gumara town. The sale of onions and tomatoes transported to
Bahir Dar and Gonder towns was another income source. Werota, the capital town of
the district provides off-farm income for the surrounding households, especially in
petty trading. Some households have houses in town and rents are another source of
income. Thus, average off-farm and non-farm income share were highest in Werota
Zuria compared to other PAs. The other sources of off-farm income in the area were
employment on other farms during weeding and harvesting seasons, sale of wood, sale
of local drinks (tela), renting of irrigable lands, artisan (blacksmith, weaving and
pottery), brokering, sale of wood (charcoal), house rent and remittance.
Table 19: The mean off-farm and other incomes
Characteristics
Irrigating
households
(N=90)
Non-irrigating
households
(N=90)
Total
(N=180)
t-value for
difference
Off-farm incomes 622 667 645 - 0.3
The average off-farm income for sample households was ETB 645 (table 19).
Irrigating households also get off-farm income from the rent of water pump and
houses rent in the town. Water pumps were rented on average for ETB 12.50/hour.
72
The difference in off-farm income between irrigating and non-irrigating households is
not statistically significant.
5.4.4 Summary of income sources at household level
The total mean annual household income in the study area was ETB 26,251
(Table 20), which is roughly equal to the average per capita income for Ethiopia as a
whole. From the total mean annual income of a household, cropping contributes the
highest income share (86%) followed by livestock (11%) and off-farm (3%),
respectively.
Irrigating households earn higher income from cropping than non-irrigating
households. However, there is no significant difference between irrigating and non-
irrigating households in their livestock and off-farm incomes. The total income
significant difference arises from the cropping income difference, which is suggestive
of the both the mechanism and the degree to which irrigation access increases
household incomes. The next section discusses the results of econometric analysis that
assesses the impact of irrigation controlling for other factors that influence income.
Table 20: Summary of annual household income sources:
Characteristics
Irrigating
households
(N=90)
Non-
irrigating
households
(N=90)
Total
(N=180) Percent
t-value
for
difference
Crop income 32,282 13,366 22,824 86 7.7***
Livestock
income 3,132 2,433 2,783 11 1.4
Off-farm
income 622 667 645 3 - 0.3
Total income 36,036 16,466 26,251 100 7.6***
*** indicates significant at the 1% significance level.
73
5.4.5 Econometric model for income analysis
This section provides additional analysis of the impact of irrigation on the
performance of gross incomes of the irrigating households. This study uses an
econometric model for the analysis of impacts of irrigation on household income. In
this analysis, the dependent variable is the household annual total income derived from
rainfed and irrigation crops, livestock and their products, off-farm and other incomes
reported over the past 12 months (from November 2009-October 2010).
The income analysis was estimated using a Tobit (censored regression) model.
The analysis was carried out using Stata software. Multicollinearity was examined
using Variance inflation factor (VIF) and correlation coefficients. The values of the
VIF for explanatory variables were found to be less than 10 and total of eleven
explanatory variables were entered in to the regression analysis.
The dependent variable, total income of a household, has non-zero value.
According to Holloway et al. (2004), use of a Tobit model at a non-zero dependent
variable may increase the magnitude of bias, and to avoid this problem they develop
alternative approaches. In the censored regression model, the minimum of the
observed values defines the maximum for the censoring value. That is an upper bound
on n is the minimum of the set (yi , i c) by the same reasoning, because the observed
total income is non-negative. A logical lower bound on total income (п) on n is zero.
In other words, logic constrains the feasible choice for п to the closed interval
(10)
This equation provides the censoring points to can be vary within the range of values
that lies below the minimum of the observed, positive quantities.
74
On the basis of this alternative, the observed total minimum income at
household level is ETB 1,256, that is, a non-zero value. By considering the above
revised approaches Tobit regression model was used with 1255 as lower limit. The
estimates of coefficients by the Tobit regression model as tool of parameter estimation
are depicted below (Table 21).
The Tobit analysis suggests that several variables have a statistically
significant impact on the total income of the household, many of which are consistent
with the hypothesized relationships. The analysis indicates which determinants are
more important for the improvement of total household income. Some variables
appear to be insignificant; this may be due to the relatively small sample size involved.
Education of household head (EDUHH) has statistically significant positive
impact on the total income of a household. This seems rational; educated human
capital can more easily adopt technologies like irrigation and make more informed
production decision. Education can increase the marginal productivity of labor. The
increase in productivity of labor is one of the important factors to increase income of a
household.
Household family size in adult equivalent (FAMSZADUL) and livestock
holding in TLU (LIVESTO) are positively associated with household total income,
and both of them are statistically significant. Household family size in adult equivalent
means a larger amount of labor available to the household. Labor increases
productivity per ha of land, and in turn, household total income increases for a given
land base. The positive association between labor and household total income seems
reasonable. Livestock holding in TLU (LIVESTO) contributes to total household
income directly through the sale of livestock and their products, and indirectly through
use as a source of draught power for crop production activities.
75
Table 21: Tobit estimates of the determinants for household total income
Variable Coef. Std. Err. t P>|t|
AGEHH -16.54 50.73 -0.33 0.74
EDUHH 4915.29 1487.37 3.30 0.00
GENDERHH 98.65 1755.29 0.06 0.96
DEPRATIO -1031.12 692.57 -1.49 0.14
FAMSZADUL 1554.59 505.83 3.07 0.00
LIVESTO 2285.07 374.29 6.11 0.00
IRR 3359.46 1222.01 2.75 0.01
ASSETHH 2.81 .34 8.26 0.00
LANDSZ 10291.91 1607.31 6.40 0.00
INPUT 4688.55 1738.96 2.70 0.01
CREDIT -894.16 1052.57 -0.85 0.39
Constant -10696.22 3561.15 -3.00 0.00
Sigma 6778.27 358.72
Number of obs. 180
LR chi2(11) 386.63
Prob > chi2
0.00
Pseudo R2
0.09
Log likelihood -1834.24
Access to irrigation (IRR) influences the household total income significantly
with a positive sign as expected. As Maddison (1970) suggest, access of technology
(irrigation) shifts the production function and offsets the diminishing marginal return
by doing so increases income and used as a source of economic growth. According to
Makombe (2007), the production function analysis of irrigated and non-irrigated farm
plots, the result shows that irrigation shifts the agricultural production frontier to a
higher level. The marginal productivities of land and labor for the irrigated farms are
almost four, and five times more, respectively. Thus, access to irrigation is one among
many factors that increase household incomes.
Household production asset value (ASSETHH) influences the household total
income significantly with a positive sign. This tells us households with high
production assets can produce more and increase their total income. This is consistent
with the economics of transformation and growth principles (Maddison et al. 1970) as
76
people accumulate physical capital allows the people to expand production by
changing the marginal productivity of inputs like land and labor.
Land size (LANDSZ) is positively associated with household total income as
expected. Land holding is highly significant to the household total income. Land is
important fixed input to increase production and income.
Use of input (INPUT) influences household income significantly, and as
hypothesized has a positive impact. Households who use input have higher household
income. As Maddison et al. (1970) suggest, one of the main strategies for agricultural
development depends on the availability and financing of new inputs like chemical
fertilizers, new seeds, pesticides and the like.
Age of household head age (AGEHH), Gender of household head
(GENDERHH), Household dependency ratio (DEPRATIO) and Household access to
credit (CREDIT) have no statistically significant effect on the total income of a
household.
The previous discussion indicated the sign and statistical significance of the
coefficients from the Tobit model. However, in that model the coefficients do not
directly represent the marginal effect, that is, the impact on household income from a
one-unit change in the independent variables. The marginal effects are calculated
using equation (5) using the mean values of the independent variables. The marginal
effect estimates reveal that the land size (LANDSZ) has the largest impact. That is, a
one ha land change has an impact on income for 10,275 ETB per year (Table 22).
Thus, land holding size is very important input in rural poor households to increase
their annual income (although it will typically be difficult for a household to markedly
increase the size of its landholding). Because agriculture is the main source of income
and livelihood for more than 85% of the country‟s population, land access is a critical
and sensitive political issue in contemporary history of Ethiopia (Helland 1999). In the
77
study area, land is a scarce resource. Land share in/out and rent in/out is common.
Even thought the cost in cash of land is not far from the estimated marginal impact of
land, the additional costs such as transaction cost and monitoring cost are high.
Therefore, it is not easy to increase a land access for the individual household.
Education of household head (EDUHH) is another important factor that
influences the annual total income of a household. The analysis shows that education
(literacy) significantly increases the household‟s total income by ETB 4,903.3.
Use of inputs (INPUT) influences household income from crop production.
The main inputs used in the study area are chemical fertilizers, improved seeds and
chemicals (pesticide, herbicide). Households who used one or more of these inputs
increase their income significantly. The marginal effect of the Tobit model revealed
that households who have access for inputs can increase their income by ETB 4,670
per annum. Although it was not tested formally in this study through the estimation of
a production function, other agricultural inputs probably are complementary with
irrigation. Thus, consideration should be given not only to irrigation water access but
also to other agricultural inputs.
Access to irrigation (IRR) has a significant impact on the total income of a
household, ETB 3,353 per year (or a 27% increase in the mean income without
irrigation). This supports the initial hypothesis that access to irrigation increases
households‟ income, controlling for other factors. Households who have access to
irrigation can cultivate their irrigated land two or more times a year. Although the
econometric analysis cannot indicate directly why the increase in income occurs,
irrigation allows the farmers to practice crop intensification 9 and diversification
10,
9 Crop intensity means cultivating two or three times per year
7Crop diversification means producing two or more crops per one crop season
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which increases crop yields and revenues from crop sales. Irrigation likely also
increases the marginal land and labor productivity, increases the crop production and
then promotes household income.
Table 22: Marginal effects of determinants on household total income
Determinant dy/dx Std. Err. z P>|z|
AGEHH -16.51 50.65 -0.33 0.74
EDUHH 4903.33 1481.80 3.31 0.00
GENDERHH 98.48 1752.30 0.06 0.95
DEPRATIO -1029.43 691.43 -1.49 0.14
FAMSZADUL 1552.03 504.99 3.07 0.00
LIVESTO 2281.29 373.67 6.11 0.00
IRR 3353.29 1219.40 2.75 0.01
ASSETHH 2.80 0.34 8.26 0.00
LANDSZ 10274.89 1604.70 6.40 0.00
INPUT 4669.84 1725.20 2.71 0.01
CREDIT -892.63 1050.60 -0.85 0.39
Livestock holding (LIVESTO) also affects annual total income of a household.
An increase of household‟s livestock holding by one TLU is estimated to increase the
total income of a household by ETB 2,281 per annum. As expected, the value of
productive assets owned by the household (ASSETHH) also increases total income of
a household. The increase in asset holding of a household by ETB 1,000 is estimated
to increase total household income by ETB 2,800. This suggests that if households
invested in more productive assets, they would pay for themselves in a relatively short
time. (However, it is important to note that the effect is on gross, rather than net
income, so the return on productive assets cannot be directly calculated based on these
results.)
Household size in adult equivalent (FAMSZADUL) also increases the annual
income of a household. A one-unit increase family size in adult equivalent increases
the total income of a household by about ETB 1,600.
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5.4.6 Comparison of sample small-scale irrigation types at household level
In addition to the overall impact that irrigation has on household incomes, it is
relevant to consider the income generated by different types of irrigation systems.
Each small-scale irrigation type has its own advantages and disadvantages. Sample
households use concrete river/spring diversion, motor pump irrigation, treadle pump
irrigation and traditional river diversion.
5.4.6.1 Sample small-scale irrigation types and irrigated crop income.
The concrete canal river/spring diversion generates more income per
household on average than other irrigation types. The mean annual irrigated cropping
income from concrete canal river/spring diversion is ETB 25,610 (Table 23); 40% of
total mean annual income from all irrigated crops). This indicates that concrete canal
river/spring diversion irrigation produces the highest income share compared with the
other sample small-scale irrigation types. The reason is the amount of water supplied
is large, especially in Kuhir Michael and Shina PAs. Moreover, water wastage is
relatively low due to the water user association. The association establishes a water
use timetable for all user households, and then the amount of water supplied to
irrigated farm plots is equal and adequate. This limits water theft and conflict among
irrigation water users. The concrete canal river/spring diversion water user pays for the
water. The payment depends on the amount of irrigated land owned by a household.
The average payment was ETB 40 / ha/year. The users believed that the payment is
low compared to the benefits provided by the service, which is consistent with the
findings of this study with regard to the impact of irrigation water access on household
incomes.
80
The small-scale irrigation type that produced the second-largest amount of
income per household was the motor pump. Motor pump irrigation users can access
water easily from any perennial rivers. Motor pump are widely used in the study area.
Rivers such as Gumara, Rib and Eriza are widely exploited by motor pump irrigation
users. The mean annual irrigated cropping income from motor pump is ETB 22,422
(Table 23). Households who have a motor pump get additional income by renting the
pump for other households. However, an issue is the cost of fuel and durability of the
pump.
Table 23: The sample small-scale irrigation types and irrigated crop income per
irrigating household
Irrigation
types Obs. Mean
Std.
deviation Minimum Maximum Percent
Concrete
canal
river/spring
diversion
24 25,610 21,253.4 4,895 80,380 40
Motor pump 24 22,422 17,886.9 1,176 62,841 34
Pedal pump 20 9,502 7,217.1 1,658 29,240 12
Total 90 17,271 17,011.5 649 80,380 100
Many households use traditional river diversion in the study area. The mean
annual irrigated crop income from this irrigation system is ETB 9,615 per household.
This irrigation system has no direct cash cost; the river diversion is made by user
farmers using their own labor. For this reason, poor rural households are more often
interested in and use this irrigation system. The main problem in traditional river
diversion was the shortage of water due to lack of rivers accessible to traditional
diversion. The more easily traditionally diverted rivers often provide limited water in
the dry months before irrigated crops are harvested.
Pedal pumps have high demand by irrigation user households in the study area
due to their low cost and the easy water access they allow. In the Fogera plain, the
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water table is high, so many households use bucket and jar irrigation from shallow
wells. These households have high demand for treadle pump especially the Indian
treadle pump. The mean annual income from pedal pump irrigation is ETB 9,502 per
household. It is relevant to compare the income from crops under different types of
irrigation systems, even thought this does not control for other factors that may
influence cropping income and therefore cannot be used directly to indicate that one
irrigation type is more profitable than another. As noted in Chapter 4, with four
irrigation types there are six pair wise comparisons, which will be tested for
differences with a combined overall significance level using the Games-Howell test.
The statistical mean comparison revealed that concrete canal river/spring
diversion has a significant difference with traditional river diversion and pedal pump
at the 5 % and 1 % significance levels, respectively (Table 24). Motor pump irrigation
has also a significance difference with traditional river diversion and pedal pump at a
5 % significance level. However, there is no significant difference between concrete
river/spring diversion and motor pump, nor a significant difference between traditional
river diversion and pedal pump.
Table 24: The sample small-scale irrigation types and irrigated crop income
Post Hoc multiple comparisons, Games-Howell
(I) Sample small-
scale irrigation types
(J) Sample small-scale
irrigation types
Mean
Difference
(I-J)
Std.
Error
Concrete canal
river/spring diversion
Traditional river diversion 15994.8**
4.859.8
Motor pump 3187.6 5.670.3
Treadle pump 16107.6***
4.628.8
Traditional river
diversion
Motor pump -1.2807.2**
4.257.6
Pedal pump 112.8 2.720.4
Motor pump Pedal pump 12920.0**
3.991.9
***, ** indicate significant at the 1% and 5% significance levels, respectively.
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5.4.6.2 The small-scale irrigation types and total income of household
Irrigation has significant impact on the total income of a household in addition
to the impact on cropping income. Small-scale irrigating households have higher mean
value income than non-irrigating households. The amount of annual total income of a
household is influenced by the type of small-scale irrigation used.
Table 25: Small scale irrigation types and total income of a household
Irrigation types Obs. Mean Std.
deviation Minimum Maximum
Concrete canal
river/spring diversion 24 46,530 26,736 17,775 106,000
Traditional river
diversion 22 25,544 11,613 10,860 50,797
Motor pump 24 44,840 22,521 6,802 92,741
Treadle pump 20 24,419 10,453 6,948 44,174
Non-irrigating 90 16,466 11,232 1,256 44,907
Total 180 26,251 19,930 1,256 106,000
Canal river diversion users have the highest average total household income,
with a mean of ETB 46,530. The average annual income for motor pump irrigating
households is similar to that of concrete canal river/spring diversion, with ETB
44,840. Traditional river diversion and pedal pump irrigation have mean annual
incomes significantly lower than canal or motor pump users, with ETB 25,544 and
24,419, respectively.
It is pertinent to compare the total mean annual income under four different
types of irrigating and non-irrigating households, even thought this does not control
for other factors that may influence mean annual income of household (Table 26). For
the four types of irrigation and non-irrigation systems, there are nine pair wise
comparisons that were tested for differences with a combined overall significance
level using the Games-Howell test. The statistical mean comparisons revealed that the
four irrigation systems have a significant difference with non-irrigation system.
83
Table 26:Small-scale irrigation types and the mean annual income of a household
(I) Sample small-
scale irrigation types
(J) Sample small-
scale irrigation
types
Mean
difference (I-J) Std. Error
Concrete canal
river/spring diversion
Traditional river
diversion 20986.3
** 5992.9
Motor pump 1689.5 7135.8
Pedal pump 22111.1*** 5937.1
Non-irrigating 30063.6*** 5584.6
Traditional river
diversion
Motor pump -19296.7*** 5221.5
Pedal pump 1124.8 3404.9
Non-irrigating 9077.3**
2744.4
Motor pump Pedal pump 20421.6*** 5157.2
Non-irrigating 28374.0*** 4747.1
Pedal pump Non-irrigating 7952.5** 2620.1
***, ** indicate significant at the 1% and 5% significance levels, respectively.
5.5 Poverty analysis
5.5.1 Poverty level in the study area
As described in chapter 4, the absolute poverty line (i.e., people unable to attain their
minimum nutritional requirements) was defined as the value of current income at the
twenty-fifth percentile of sample households and moderate poverty line is the value of
current income at the thirtieth percentile for sample households. These poverty
threshold values allow computation of the proportion of households in poverty, and
the poverty gap.
The absolute poverty head count ratios of irrigating and non-irrigating
households were 7 % and 43%, respectively (Table 27).The moderate poverty head
count ratios of irrigating and non-irrigating households were 10% and 50 %,
respectively. In the study area, of the sample population who live below the absolute
poverty level, 88% are non-irrigating households and only 12% are irrigating
households. This suggests that irrigation may have a significant impact on rural
poverty alleviation.
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Table 27: Poverty comparison between irrigating and non-irrigating household
Absolute poverty line Moderate poverty line
Head count
ratio (P0)
Poverty gap
index (P1)
Head count
ratio (P0)
Poverty gap
index (P1)
Irrigating
households 0.07 0.29 0.10 0.33
Non-irrigating
household 0.43 0.43 0.50 0.47
The poverty gap index shows the proportionate shortfall of average income
from poverty line. Because the definitions of absolute and moderate poverty were
similar (a difference of only about 200 ETB per person per year), the calculated
poverty gap values for absolute and moderate poverty levels are similar for a given
household type (Table 27). The estimated poverty gap index using the absolute
poverty line for irrigating and non-irrigating household were 29 %and 43%,
respectively, while the poverty gap index using the moderate poverty line for irrigating
and non-irrigating households were found to be 33% and 47%, respectively. The
average income gap of poor people is ETB 943 and 1399 for irrigating and non-
irrigating households, respectively. The estimated average income required to bring
the poor people out of poverty (poverty line) for non-irrigating households was higher
by ETB 546 than irrigating households. The poverty gap index is much larger for non-
irrigating households, which again suggests that irrigation may play a role in poverty
reduction.
The poverty gap concept can also be expressed in terms of monetary values
rather than as a proportion, and this is undertaken for individual PAs (Table 28) and
by irrigation use status (Table 31).
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Table 28: The average income poverty gap of the poor by sample PAs
PAs Mean income per adult
equivalent of the poor, ETB
Mean of income poverty
Gap, ETB
Werota Zuria 2,290 935
Bebekis 1,500 1,725
Kokit 2,210 1,015
Kuhir Michael 1,995 1,230
Shina 2,652 573
Overall 1,887 1,338
The overall income gap of poor people was ETB 1,338. The estimated average
income gap of poor people differs by PA; the gap is lowest in Shina (ETB 573), and
highest in Bebekis (ETB 1,725, nearly three times that in Shina), this is due to that
Shina is high irrigation potential area. The two irrigable rivers Gumara and Rib are
exploited in this PA. In Shina all households are irrigation users. Thus, the poverty gap
is low whereas in Bebekis the main irrigation water source is spring development. The
amount of water is limited. The access of irrigation from rivers is limited. Thus,
households who are accessed to river and spring irrigation have high income whereas
those who cannot get are low in income. Therefore, the poverty gap is high in this PA.
Table 29: The average income poverty gap between irrigating and non-irrigating
households
Mean income per adult
equivalent of the poor, ETB
Mean of income
poverty Gap ETB
Irrigating 2,282 943
Non-irrigating 1,826 1399
Total 1,887 1338
The average income gap of irrigating households was lower than non-irrigating
households. This suggests that access to irrigation reduces the poverty gap (and thus
reduces the average extent of poverty). The numbers of households below the
moderate poverty line are fifty-four (based on the thirtieth percentile of current income
and N=180 total households). Of these 54, 49 (91%) are non-irrigating households.
The five households below the moderate poverty line use different irrigation
86
technologies: two use pedal pump, one uses traditional river diversion, one uses motor
pump, and one uses concrete canal river/spring diversion. The number of irrigating
households below the poverty line is small, which makes it difficult to assess the
impact of irrigation types on the likelihood of a household being in poverty.
5.5.2 Multivariate Logit regression
A Logit regression model is used to assess the impact of various factors
including irrigation access on the probability that a household is in poverty. For this
analysis, the poverty threshold is the absolute poverty line, which is defined as the
current income at the twenty-fifth percentile of the sampled households. The overall
significance of the regression is good (Table 30) based on the probability of getting a
LR test (as indicated by the small p- value from the LR test of < 0.00001). Moreover,
many of the coefficients of independent variables in the model are significant and have
the expected sign.
The estimated coefficient for dummy variable access to irrigation with the odds
of being poor over non-poor was negatively correlated and significant. This suggests
that the probability to being poor decreases if one has access to irrigation, other factors
being constant. This likely is due to the influence that irrigation on crop intensity and
crop diversification. Cropping intensity is higher in irrigated household as compared
to non-irrigating households.
The estimated coefficient for dummy variable access to irrigation with the odd
of being poor over non-poor was negatively correlated and significant. This suggests
that the probability to being poor decreases if one has access to irrigation, other things
factors being constant. This probably is due to the influence that irrigation has on crop
intensity and crop diversification. Cropping intensity is higher in irrigated household
as compared to non-irrigating households. Because the definition of the poverty
87
threshold in this study is based on current income, and previous results suggest that
access to irrigation increases income (especially from cropping), it is not particularly
surprising that the likelihood of poverty is lowered by irrigation use.
Table 30: Parameter estimates of a logit model for determinants of a household
poverty
Determinants Coef. St. Error Odds ratio Std. Err.
AGEHH 0.02 0.02 1.02 0.02
DEPRATIO 0.08 0.32 1.08 0.34
GENDEHH -1.58**
0.70 0.21 0.14
EDUHH -1.73***
0.56 0.18 0.09
LANDSZ -1.95 **
0.51 0.01 0.01
ASSETHH -0.001 0.001 0.99 0.001
IRR -1.95 ***
0.51 0.14 0.07
NBOX -2.40 *
1.29 0.09 0.12
Constant 3.26 1.56
Number of Obs.
LR chi2(8)
Prob > chi2
Log likelihood
Pseudo R2
180
92.39
0.00
- 63.76
0.42
***, ** and * are significant at 1 percent, 5 percent and 10 percent significance level,
respectively.
However, other factors also influence the likelihood that a household is in
poverty. As expected, the coefficient of household education is negatively correlated
with poverty and significant. The results suggest that household head who is literate
had a lower probability of being poor compared with those who are illiterate.
Education is assumed to increase productivity and thereby lead to higher levels of
welfare for the household.
Poverty also is more likely for female-headed households. This may be due to
the fact that female-headed households are responsible for all household tasks in
addition to farm activity. Most of female-headed households are older and less
educated compared with counterpart male-headed households. Irrigation and other
farm operation need high labor especially for intensive ploughing, but female-headed
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households are disadvantageous with respect to labor endowments. Irrigating female-
headed household (7% of total households) were few compared to non-irrigating
female-headed household head (17% of total household). Female- headed households
also cultivated small size of land (0.89 ha) compared with male- headed household
(1.01 ha).
The coefficient of land holding per capita was negatively correlated with the
probability of a person being poor and statistically significant. The odds ratio
illustrates that a one-ha increase in land holding per capita, the odds of being poor
decrease markedly (although this is not surprising given that it would result in a
doubling of average farm size).
As expected, the number of oxen owned was negatively correlated with the
probability of a person being poor and statistically significant (but only at the 10 %
level). This shows that oxen are an important means of land cultivation and basic
factor of production. Households who own more oxen have better chance to not be in
poverty because the possession of oxen allows effective utilization of the land and
labor resources of the household.
A number of variables had no statistically significant impact on the odds ratio.
Asset holding per capita was negatively correlated with the probability of a person
being poor, but somewhat surprisingly was not statistically significant. Household
head age also had no statistically significant impact on the probability of a person
being poor which contrasts with findings of previous studies such as Bigsten et al.
(2002).
The dependency ratio often is assumed to be positively correlated with the
probability of being poor, because the burden of supporting family members too
young or too old for productive work falls on other members of the household. In this
study, the dependency ratio is computed by taking only old age members above 64
89
years and children with age less than 15 years. The probability being poor may
increase if other sick, disabled, or weak members of the household are considered. In
addition Ethiopia has high population growth rate, 2.6 percent (CSA 2007), which
increases the dependency ratio and increase the probability being poor. Although the
coefficient had a positive value for this sample, it was not statistically significant.
Consistent with the initial hypothesis, the Logit regression analysis indicates
that access to irrigation markedly reduces the odds that a household will be in poverty,
at least based on the poverty definition used in this study. Other variables that reduce
the likelihood of poverty are household head education, per capita land holding,
ownership of oxen and male headed of household head.
5.6 Problems encountered in small-scale irrigation development
Small-scale irrigation has immense potential to improve the incomes of poor
rural households in developing countries like Ethiopia, but it is never free from
problems. A field survey with focus group discussion and key informant interviews
indicates that small-scale irrigation‟s great benefit is accompanied with
multidimensional problems. The problems of small-scale irrigation technology
development range from individual household‟s biased attitudes to institutional
arrangements. The major problems encountered in small-scale irrigation in the study
area are problems related to cost, institutional problems, the policy environment,
design issues, cultural factors and environmental problems.
Loss of water through seepage is the main problem in small-scale irrigation
systems in the study area. The non-durability of the physical structure of irrigation
schemes and the Vertisol nature of the study area causes high water seepage from river
diversion canals. Seepage from irrigation canals is the main causes for water losses in
Kuhir Michael.
90
The area development agent Ato Mekonen says “the water loss through canal
seepage is the main problem for the source of water shortage for the downstream PA,
Shina.” The canals were constructed in 2003, and the canal‟s service length and the
black soil nature of the area may cause the canal to be non-functional in the absence of
a strong water use association. The current association mends the canal when there is
damage, and protects against any misuse or activities that might damage the canal.
Water loss through seepage occurs with motor water pumps also (Figure 16). In
Werota Zuria PA, Ato Amare cultivated oats using a motorized pump drawing water
from the Eriza River. The main problem faced in his irrigation activities is the water
loss through seepage from the delivery hose.
Figure 15: Water loss through seepage from river diversion canal
91
The lack of spare parts in the local market plus the expense of new ones causes
difficulty for his irrigation activities. Therefore, seepage causes water shortage in the
study area in addition to evaporation and transpiration.
Problems with irrigation water distribution also exist in the study area. In the
five PAs studied, water distribution and water use principles are unregulated except in
Kuhir Michael, Shina and Bebekis where there are water use associations. This causes
many conflicts between upstream and downstream irrigating households. For instance,
in Werota Zuria PA there were conflicts on the Eriza River between downstream and
upstream irrigating households. The main cause of the problem is the amount of water
is very small in Eriza River at the end of February; the upstream community always
uses all amount of water through modern concrete canal river diversion. There are
many households who use motor pump irrigation in the downstream but receive no
water during parts of the year. This creates conflict between upstream and downstream
water users. Finally, the district judiciary court and the area political leaders resolved
the issue through a water use program that allowed use from Monday to Friday for the
upstream irrigation users and from Saturday to Sun day for downstream users.
Generally, water distribution is the main issue in any irrigation schemes. The study
revealed that there are no standardized programs and plans to irrigate each cultivated
crops. Irrigation water use depends only on spatial location of the farm plot; it does
not consider the amount of water required for the type of cultivated crop, time interval
of water application and the size of each irrigated land sizes.
92
Figure 16: Water loss from motor pump
Lack of spare parts for water pumps and shortage of fuel is an issue. The lack
of imported spare parts for motor pumps and treadle pumps are main causes for
reduced efficiency in small-scale irrigation in the study area. Since there are many
perennial rivers like Gumara and Rib in the study area, motor pump irrigation is used
by many households. The main problems in motor pump irrigation are the frequent
damage of the pump, lack of awareness of how to operate, cost of fuel and of the
pump, and lack of credit.
In the focus group discussion, farmers prefer the Robin motor pump, which is
made in Japan. Farmers are more interested with this motor pump because of its
durability and ease to operate. But, the office of agriculture supplied the Haowmax
93
motor pump on credit, which is made by Chain. The office of agriculture supplied this
motor pump rather than Robin due to the higher capacity and the lower priced fuel
used (Nafita). In contrast, the Robin used a more costly type of fuel (Benzene). But,
farmers strongly complain about the Haowmax motor pump because it is easily
damaged. The office of agriculture responds to this problem with discussions with the
Chain Company to solve the difficulty.
Pedal pumps are the other small-scale irrigation technology in the study area.
The pedal pumps used in the study area were imported from India. In the key
informant interview and focus group discussion the main problems with pedal pumps
are lack of spare parts and non-functionality due to long service. At present, most of
these Indian-made pumps no longer have suction hose and delivery hose and have lost
tightness at the joints (Figure 17).
Figure 17: Parts of pedal pump demonstrate loss of tightness
94
The pedal pumps are also highly demanded by farmers but supply in the
market is limited. The office of agriculture has substituted an Ethiopian-made pedal
pump, but users complain about its weight (and therefore higher labor requirement to
operate) and its low water pumping capacity. At present, most of these pedal pumps
are non-functional because of lack of spare parts, but farmers still have high demand
for the Indian treadle pumps because of their simplicity to operate.
Lack of market and marketing facility is another issue. Although not directly
related to the functioning of irrigation systems per se, the market is considered one of
the main problems in the study area. Cultivated vegetables using small-scale
irrigations like onion, tomato, potato and the like are highly perishable and bulky
crops, so an efficient marketing channel is necessary.
However, the study area marketing system does not always facilitate outcomes
desired by farmers. One reason is the similarity of products and marketing patterns;
onion and tomato are the dominant crops, often harvested by farmers at the same time,
which leads to a high availability and low prices during the main marketing period.
Compounding this, because there is no efficient storage system in the study area,
products quality deteriorates rapidly, which means that farmers must sell within a very
short time, often at what they consider low prices. In some PAs, such as Kuhir
Michael and Shina, which have water use associations, market risk is relatively low.
The water use association has different teams such as marketing team, input supply
team, conflict resolution team and the like. One of the main duties of marketing team
is following the market for their products, and timing sales to increase returns to
farmers. Farmers also perceive that market intermediaries are not pricing products
fairly, which suggests reduced returns and less incentive to invest in the use of
irrigation.
95
Shortage of surface water is another problem. There are rivers that have water
for only some of the dry months. Their seasonality is unpredictable, varies depending
on the climatic conditions each year. This seasonality nature of rivers in the area
causes water shortage especially at the flowering period of irrigated crops. The
traditional river diversion and treadle pump irrigation users are more seriously affected
by this type of water shortage. Traditional river diversion irrigation practiced on such
simple rivers that can easily dry up. In the study area, treadle pump irrigation users use
shallow well as their water source. However, these shallow wells dry out during dry
months of the area January, February and March. As shown in the picture (Figure 18),
the shallow well dry at around the flowering and fruiting periods of cultivated crops.
The above picture was taken on 29-January-2011.The cultivated crop on the irrigated
farm plot was tomato.
Figure 18: Non-functional shallow well
Crop diseases are another factor of importance. The study area is intensively
cultivated with the same crops for long periods of time. Onion and tomato are
repeatedly grown crops. In addition to the loss of productivity and fertility, this
96
cultivation strategy facilitates crop disease like root rot and cut warm. Imported inputs
to control these problems, such as herbicides and pesticides, are costly for farmers to
purchase. Therefore, diseases and pests can limit the economic benefits of small-scale
irrigation activities in the study area.
The price of imported inputs such as fertilizer, chemical and fuel has increased
over time, in part due to depreciation of the ETB in world currency markets. One
result is that the application of fertilizers on their farm plots is below the
recommended levels. Chemicals like pesticides and herbicides are also costly to apply.
97
CHAPTER SIX
6 CONCLUSIONS AND RECOMMENDATIONS
The objective of this study was to assess the impact of small-scale irrigation on
total income and poverty at the household level. The study was conducted in Fogera
district, Upper Blue Nile basin, focusing on four small-scale irrigation types and five
sample PAs. The selection of irrigation types and sample PAs are purposively on the
basis of the irrigation potential.
6.1 Conclusions
Access to irrigation increases the opportunity for crop intensity and
diversification, which increase cropping income. Irrigation is becoming a practice to
increase total annual income for many households in the study area. In addition to
their normal rainfed cultivation, irrigating households cultivate cash crops using small-
scale irrigation. The main irrigated crops were onion, tomato, potato, maize, oat and
vetch. Irrigated crops were selected due to good production potential, economic
returns and ease of cultivation, respectively. Onion and rice were the major income
source crops for irrigating and non-irrigating households, respectively.
The main income sources of rural household in the study area were cropping,
livestock and off-farm activities. Irrigating households have significantly larger mean
annual income than non-irrigating households, but income also differs based on the
type of irrigation used. The average annual total income of sample small-scale
irrigating households was larger for concrete canal river/spring diversion and motor
pump users compared to traditional river diversion and pedal. The findings of this
study are consistent with previous ones such as Nhundu et al. (2010) and Hussain and
Biltonen (2001).
98
Econometric analyses that control for other factors that influence household
income indicate that accesses to small–scale irrigation increases mean household
income significantly (about ETB 3,353 per year, or a 27 % increase over non-
irrigating households). This is hypothesized to occur primarily through crop
intensification and crop diversification, but this was not examined in this study. It is
important to note that other factors (such as production input use) also had large
effects on household income, and this study did not explore in detail the
complementarities between irrigation access and other input use.
The other objective of this study is to assess the impact of irrigation on the
likelihood that a household was in poverty. The results indicate that irrigation
development has a profound impact in alleviating poverty. The poverty analysis
indicates that a much higher proportion of those who are poor are non-irrigating rather
than irrigating households. Thus, the poverty prevalence in non-irrigating households
is by far greater than in irrigating households. This suggests that irrigation has an
important influence on rural poverty alleviation. Econometric analyses indicate that
use of irrigation reduces the probability of a household being poor, controlling for
other factors.
Because small-scale irrigation increases mean annual household income,
irrigating households have lower probability of being poor than non-irrigating
households. From the extremely poor households, only 12% were irrigating
households and the remaining 88 % did not irrigate. In the Logit model analysis, the
estimated coefficient for dummy variable access to irrigation with odds of being poor
over no-poor was negatively correlated and significant. The probability to being poor
decreases if one has access to irrigation, other factors being constant. This suggests
that irrigation has significant impact on rural poverty alleviation.
99
The study identified many problems in irrigation development through group
discussion and key informant interviews. The main problems are lack of access to
surface water, loss of water through seepage, problem of irrigation water distribution,
lack of spare parts for water pumps, high cost of fuel for water pumps, lack of market
transparency and marketing facilities, crop disease, and the perceived high cost of
inputs.
6.2 Policy implications
This study has found that irrigation development helps to increase household
income and reduces the incidence of poverty at the household level. Based on these
findings as well as the outcomes of focus group discussions and key informant
interviews, further development and refinement of small-scale irrigation systems
appears merited. This, of course, raises the question about this might best be
undertaken. Although a formal analysis of strategies for future irrigation development
is beyond the scope of this research, following actions are suggested to facilitate future
irrigation development.
1. Ensure irrigation water access, especially through groundwater
Access to irrigation has significant impact to promote total income and reduces the
probability of households being poor. The main reason for non-irrigating households
(85 percent) not to irrigate is lack of access to surface water. Moreover, the
availability of surface water for only short periods in some areas causes loss of lower
crop yield in dry periods, even for irrigating households. Therefore, in addition to
surface water, the use of groundwater for small-scale irrigation is likely to be valuable
for future irrigation development. Previous studies indicate that the study area, Lake
Tana basin has high groundwater potential (Johnston et al., 2010). According to
100
Abedin et al. and Girum (2010), the Fogera alluvial deposited flood plains have
considerable potential for shallow groundwater. Therefore it is appropriate to give
attention to exploit both the surface and groundwater potential of area.
2. Renewed and improved the existed concrete canal river/spring diversion
The concrete canal river/spring diversion has great impact on poverty reduction
by increasing household income. All these types of sample small-scale irrigation were
constructed more than eight years ago in the study areas. They are now cracked and
there is a water seepage problem. The irrigated land coverage is also small compared
with the potential of the area. The Bureau of Agriculture and rural development is
responsible for irrigation development cooperated with governmental and non-
governmental organizations. In the interview and focus group discussions, concrete
canal river diversion user households feel that the water use payment is very low.
They want better service with better payment. Therefore, the Bureau of Agriculture
and Rural Development should give more emphasis on the mending of the existing
schemes and scaling up of the irrigation schemes for sustainable income growth and
poverty reduction at household level.
3. Supply water pumps on the basis of users demand
Water pumps like the motor pump and pedal pump are used in the study area
for irrigation. The supply of these irrigation technologies should be more closely
aligned with the pump characteristics that farmers demand. For instance, the India
pedal pump and Robin motor pump have high demand in the study area, but the access
to such water pumps is limited. In particular, farmers do not have access to the India
pedal pump in the market. Water pumps are profitable for user households. For
101
example, the annualized cost 11
of a motor pump is ETB 785 based on an initial cost of
ETB 6,430 a useful life of 8 years, and a salvage value of ETB 2,000 and an interest
rate of 5 %. The marginal return of irrigation access (although not specifically for the
motor pump, which serves as one example of the technologies that could be used) is
ETB 3,353 per year. The net margin return 12
(NMR) of the motor pump is ETB 2,568
per year and it would require two and half years to pay back the cost of the pump.
Pedal pumps were provided on credit for ETB 430 by office of agriculture, to be paid
back within a year. Thus, concerned governmental and non-governmental
organizations should give emphasis on the supply of water pumps in demand driven.
4. Strengthen education and training
Education has paramount impact on income improvement and poverty
alleviation over time. The two econometric model analyses indicate that literacy has a
large positive impact on household income and also reduces the likelihood that a
household will be in poverty. These effects likely occur because illiterate households
have difficulty accessing extension services and adoption recommendation.
11
Annualized cost of the motor pump is the amount of cost incurred in a year for the equipment which
has useful life longer than one year. Monke and Pearson (1989) suggest:
Where
12
Net margin return above pump cost (NMR) = Additional annual revenue from irrigation – annual
cost of the pump.
102
Education and training facilitates the effective communication between farmers and
agricultural information providers like extension workers. Although the specific
approach to be recommended requires further study, attention should be given to
strengthen education and training for sustainable poverty alleviation in the long r
5. Improving the marketing system
Returns to irrigation are affected by the marketing channel, in part because the
main irrigated crops (onion and tomato) are harvested at similar times by farmers and
are perishable. An effective marketing system will facilitate irrigation adoption.
Hence, the concerned bodies like governmental extension services, farmers‟
cooperatives and non-governmental market organizations should support the further
development of the efficient marketing systems in the study area. This may include
provision of marketing facilities, information provision and monitoring of costs and
returns in the supply chain.
6. Ensure access for imported inputs
The important imported inputs are chemical fertilizers, herbicides and
pesticides. In the study area, these inputs are used below the recommended level
because of their high cost and shortage of supply. Access and proper utilization
agricultural inputs are important for sustainable agricultural productivity and
improvement. The government, cooperative organizations and private organizations
should give attention on the supply of these inputs on time and in adequate amount.
Further studies of the marginal returns to these inputs compared to their costs could
facilitate development of approaches to increase input use, when appropriate.
103
7. Strengthening water use association
There are water use association in the three sample PAs, Shina, Quhir Michael
and Bebekis. In focus group discussion and key informant interview, these
associations have multiple purposes, such as equal distribution of water, conflict
resolution, input supply, source of market information. Although not formally
analyzed in this study, it appears that the water management and marketing functions
undertaken by the associations can have a significant impact a on the current and
future returns from irrigation use. That is, it is not simply access to irrigation water per
se that increases household incomes, but an organizational and institutional structure
that maintains adequate water access and provide information for improved
management and marketing decisions. The concerned bodies should further study the
impacts of, and encourage the establishment of additional water use associations to
promote irrigation development.
6.3 Limitations and questions for future studies
This study focuses on the impact of irrigation on gross income and poverty
reduction at household level. However, there are limitations that need further in-depth
analysis, including the net income analysis of irrigation technologies using cost-
benefit analysis. Another issue needing further research is the groundwater potential
and the choice of irrigation technology types (small-scale, medium scale or large
scale) and their impact on income and poverty. The impact of irrigation on actual
livelihood change on the community like nutritional outcomes, and other indicators of
household well-being need further study. Another issue to be addressed is that
irrigated crops were cultivated and harvested by all farmers at the same time, which
causes the perceived problems of marketing and post harvest handling in the study
area.
104
Some of the key limitations relate to the ability to generalize from this thesis
work. These limitations are:
The study looked at one region of Ethiopia (with presumably greater potential for
irrigation development) for a relatively short period of time. This can make it difficult
to generalize about irrigation‟s impacts elsewhere in Ethiopia and in other developing
countries. It is also a challenge to sort out the dynamic impacts of irrigation from a
single-period study. As one example, the study treats livestock as exogenous (given in
a particular year) but higher incomes from irrigation over time may allow additional
livestock accumulation, which could further increase incomes. Another limitation is
that the study considered gross income, rather than net income, and did not assess
whether higher incomes resulted in improved outcomes such as nutritional status,
health status or education.
Future research questions that follow not so much from the study direct finings
but from the study suggested actions are:
• Which types of irrigation are most cost-effective (cost-benefit analysis
comparing net income to costs) under what conditions?
• What strategies can address the shortages of parts?
• What programs might best make pumps and parts available to farmers?
• What educational efforts could improve returns from irrigation?
• What are the complementarities between irrigation, and other inputs, including
education?
• What organization for and activities of water use associations benefit farm
households, and why?
• To what extent would improvements in the marketing system increase farmer
returns and facilitate irrigation adoption?
105
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APPENDIX- A: TABLES OF CROP VALUES AND
CONVERSION FACTORS.
Table A1: The price of crops and vegetables in 2009/2010
Crop type Nov. Dec. Jan. Feb. Mar. Apri. May Jun Ave.
price
Teff 694 620 583 606 568 610 525 798 626
Barely 315 316 285 307.5 302 314 298 399 317
Wheat 400 476 477 491 478 485 467 429 463
Finger m. 300 332 320 340 320 360 345 400 340
Maize 300 295 256 307.5 293 259 267 331 289
Sorghum 338 332 322 308 278 275 263 255 296
Rice 675 503 622 610.5 596 652 659 716 629
Beans 397 458 339 473.5 438 440 434 417 425
Peas 415 432 405 433.5 472 482 480 454 447
Chickpea 385 372 343 402.5 390 409 404 375 385
Vetch 250 220 300 300 380 400 390 400 330
Lentil 680 630 659 682 679 738 737 736 693
Nug 471 589 591 559.5 516 581 577 556 555
Oat 400 400 500 550 540 680 710 800 573
Rapeseed 285 270 239 261 223 298 306 373 282
Fennfrek 560 599 810 635 648 678 705 688 666
Pepper 1365 1555 1585 1636 1770 1749 1769 1471 1613
Tomato 421 301 275 202.5 103 111 122 360 237
Onion 558 503 516 500 428 390 327 558 473
Garlic 610 606 602 616.5 618 610 617 545 603
Potato 244 205 229 305 165 197 214 220 222
Kosta 242 208 178 219 206 230 215 205 213
Cabbage 283 265 241 231.5 225 230 231 236 243
Honey 1840 1866 2000 2173 3200 2240 2184 2202 2213
Skin 10.5 10 10 11 10 11.5 11.5 12 11
Milk 356 356 336 332.5 348 350 349 436 358
Butter 3505 3708 3760 4025 4270 4560 5049 4680 4195
Source: Fogera District Agricultural and Rural Development office (2010)
116
Table A2: Conversion factor for Adult equivalent
Years of age Men Women
0-1 0.33 0.33
1-2 0.46 0.46
2-3 0.54 0.54
3-5 0.62 0.62
5-7 0.74 0.70
7-10 0.84 0.72
10-12 0.88 0.78
12-14 0.96 0.84
16-18 1.14 0.86
18-30 1.04 0.80
30-60 1.00 0.82
60 plus 0.84 0.74
Source: Dercon and Krishnan (1998)
Table A3: Conversion factor for Tropical Livestock Unit (TLU)
Livestock Type TLU
Ox 1.10
Cow 1.0
Heifer 0.50
Bull 0.6
Calves 0.20
Sheep 0.01
Goat 0.09
Donkey 0.5
Horse 0.80
Mule 0.7
Poultry 0.01
Source: Abdinasir, Ibrahim (2000)
117
APPENDIX- B: SURVEY QUESTIONNAIRE CORNELL-BAHIRDAR UNVERSITIES MPS PROGRAME IN INTEGRATED
WATERSHED MANAGEMENT AND WATER SUPPLY
The questionnaire is prepared to undertake a study on the effect of selected small-scale
irrigation on poverty reduction at house hold level. The purpose of the questionnaire
is to gather information on irrigating and non-irrigating household‟s socio-economic,
agricultural and non-agricultural activities, access for services and other important
information. Dear respondents, the result of this study will help different stakeholders
and policy makers to make appropriate measures on irrigation development in the
future. Your responses are confidential. Therefore, you are kindly requested to provide
genuine responses. Thank you for your time and cooperation!
Identification
a. Code _________________
b. Peasant Association name (PA) _____________________
c. Village___________________________________
1. Demographic Characteristics of the Household
1. Household head name: __________________
2. Age of the household head ____________________
2. 1. Age, sex and education of all household members including permanently
employed laborer, husband and wife.
Age Male Female Educatio
n/Grade
Age Male Female Education
/Grade
0-1 12-14
1-2 16-18
2-3 18-30
3-5 30-60
5-7 60-64
7-10 above 64
10-12 Total
1. Sex of the household head _____________
1= Male 2 = Female
2. Education of the household head _________
0 = illiterate
1 = Read and writ 1 = Elementary complete
3 = Junior complete
4 = High school complete & above
118
3. Education of the spouse___________
0 = illiterate
1 = Read and writ
2 = Elementary complete
3 = Junior complete
4 = High school complete & above
4. Religion________
1 = Christian
2 = Muslim
3 = Traditional
4 = other
7. Total family numbers of the household______________________________
8. Do you face labor shortage?
0 = No 2 = Yes
9. Type of your house
0 = Grass roofed 1 = Corrugated iron roofed house
2. Resource endowments 2.1. Farmland and other assets
No
Land Type
Size in
timed
Other assets
Owned?
1. Yes
2. No
How much it
cost now
(Value) in
ETB
1 Currently
farmed
5 Agricultural
assets
a. Own a. Motor pump
b. Rented in b. Pedal pump
c. Shared in c. Well
d. Shared out
Rented Out 6 Business assets
2 Fallow land a. Mill
3 Pasture land b. Shop
4 Woodlots c. Carts
119
3. Crop production 3.1. Crops production in rainfed, from Nov 2009-June2010
N
o
Type of Crops Plot Size
(Timade)
Total
production
(Kg)
Consumed
at home
(Kg)
Sold
Amtt
(kg)
Value
(ETB)
Ave.
price
1 Teff
2 Maize
3 Wheat
4 Barely
5 Sorghum
6 Finger millet
7 Rice
8 Beans
9 Peas
10 Chickpea
11 Vetch
12 Lentil
13 Noug
14 Sesame
15 Rapeseed
16 Linseed
17 Garlic
18 Fennfreek
19 Other crops
3.2. Vegetable, Fruit, and woodlot production in rainfed No Type of Crop
grown
Plot Size
(Timade)
Total
production
(Kg)
Consumed
at home
(Kg)
Sold
Amount
(kg)
Value
(birr)
Ave.
price
Vegetable
1 Tomato
2 Potato
3 Pepper
4 Onion
5 Cabbage
6 Kosta
7 Others
Fruit
1 Avocado
2 Orange
3 Lemon
4 Others
Woodlots
1 Eucalyptus
2 Gesho
120
1. Are you irrigation user?
0 = No
1 = Yes
a. If the answer is No, what was the reasons not using irrigation?
1 = No farmland in surface water access
2 = No awareness about it
3 = Sufficient rain and moisture
4 = others
2. Which small-scale irrigation type do you use?
1 = Modern micro dam
2 = Traditional river diversion
3 = Motor pump
4 = Treadle pump
5 = others specify_____________________
3. How long do you use irrigation farming? ______________years
0 = No irrigation farming before
1 = 0-2 years
2 = 2-4 years
3 = 4-6 years
4 = 6-8 years
5 = 8 and above years
4. What are the major problems you face/observe in your irrigation farming
_______________________ and what actions do you take to solve the problem
_____________________________________________________________________
5. The major problems encountered in small-scale irrigation schemes you use per
crop season.
5.1. a. In the upgraded small-scale irrigation, how much payment /one crop season,
if any, ____________________
b. What do you feel about the payment, if you feel the cost is high how much is the
reasonable price ________________________________________________
c. What are the major problems encountered in the use of upgraded small-scale
irrigation, what is your opinion about the
solution___________________________________________________________
_____________________________________________________________________
5.2. a. What are the major problems in using Motor pump for small-scale
irrigation? What is your opinion about the solution
_____________________________________________________________________
_____________________________________________________________________
5.3. a. What are the major problems in using Pedal pump for small-scale irrigation?
What is your opinion about the solution______________________________
121
5.4. Well:
a. For what purpose the well water used? If the water was used for irrigation how the
water drawn out from the well
_____________________________________________________________________
_____________________________________________________________________
b. What is the depth of the well in meter? ________, for how long do you use the
well once constructed ____________, if there are a frequent failure what was the main
reasons __________________________________________________________
c. On average for how many months the water available in the well within a
year_______?
1. How much of your land is used by irrigation_________________________
2. Have you cultivated the total of your irrigable land during the last dry season
0 = No
1 = Yes
If your answer to question is No, what are the reasons? (Circle the answers)
1 = Shortage of family labor
2 = Lack of seed
3 = Lack of oxen
4 = Enough production rainfed
5 = Lack of credit
6 = Others specify
8. Have you rented in or rented out any cultivable land
0 = No
1 = Yes
If yes, how much is the cost per Timad per crop season for:
a) Irrigable land______________________________
b) Non-irrigable land_______________________________________
9. What is the source of water for your irrigation?
10. What is the distance between the sources of water to your irrigated land?
_____________________________________________________________________
11. What is the system of water sharing with others?
_____________________________________________________________________
_____________________________________________________________________
12. Is the amount of water is enough to irrigate your land?
1 = River
2 = Well
3 = Spring
4 = Pond
5 = Others
0 = No
122
If your answer is no, what mechanisms do you suggest to solve the scarcity of
water____________________________________________________
13. Is there irrigation water use association around your area?
If your answer is yes, what are the benefits obtained from the association and your
role_______________________________________________________________
4. Production in the irrigation agriculture:
4.1 Crop production in irrigation (Nov 2009- June 2010)
No Type of
Crops
Plot Size
(Timad)
Total
production
(Kg)
Consumed
at home
(Kg)
Sold
Amt
(kg)
Value
(birr)
Ave.
price
1 Teff
2 Maize
3 Wheat
4 Barely
5 Sorghum
6 Finger millet
7 Rice
8 Beans
9 Peas
10 Chickpea
11 Vetch
12 Lentil
13 Noug
14 Sesame
15 Rapeseed
16 Linseed
17 Garlic
18 Fennfreek
19 Other crops
1 = Yes
0 = No
1 = Yes
123
4.2. Vegetable, Fruit, and woodlot production in irrigation
No Type of Crop
grown
Plot Size
(Timade)
Total
productio
n (Kg)
Consumed
at home
(Kg)
Sold
Amt
(kg)
Value
(birr)
Av.
Price
Vegetable
1 Tomato
2 Potato
3 Pepper
4 Onion
5 Cabbage
6 Kosta
7 Others
Fruit
1 Avocado
2 Orange
3 Lemon
4 Others
Woodlots
1 Eucalyptus
2 Gesho
3 Others
16. Why do you select the above type of Vegetable /crops for your irrigation farming?
17. Did you get reasonable price for your produce at the place you used to sell to?
18. What help do you need from the government or any organization on your
irrigation farming________________________________________________
1 = Better price
2 = Good production
3 = High disease tolerance
4 = Easiest to cultivate
5 = Seed availability
6 = Other
0 = No 1 = Yes
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5. LIVESTOCK PRODUCTION (Nov. 2009 - June2010) No Type of
animal
No of
animals
If there is any sold
animal
Rema
rk
Total
owned
How much if you
want to Sell (Nov-
June)
Sold
amount
Income
gained
(Birr)
1 Cow
2 Bull
3 Heifer
4 Calf
5 Ox
6 Mules
7 Horse
8 Donkey
9 Camel
10 Goat
11 Sheep
12 Poultry
13 Bee
colony
5.2 Livestock output N
o
Commodity type Amount
produced
(liter, Kg, no )
Consumed
(liter, Kg, no)
Sold
(Birr)
Remark
1. Dairy output (Dec.1-
15, 2010)
1.1 fluid milk
1.2 Butter
1.3 Yoghurt
1.4 Cheese
1.5 Others
2. Poultry (December1-
30, 2010)
2.1 Egg
2.2 Chicken
3. Honey bee (from the
last one harvest
season)
3.1 Honey
3.2 Bees wax
3.3 Bee colony
4. Animal by-products
Hide and skin
Manure/Dung
125
6. Credit, input and extension service supports in production (2009/10)
6.1 Credit support service 1. Did you need credit for the production of your agricultural products?
0 = No 1 = Yes
2. If yes, did you have access to credit for the production of the Commodities?
0 = No 1 = Yes
3. What is the source of your Credit?
4. Is credit timely and adequately available for agricultural commodities
development?
0 = No
1 = Yes
6.2 Extension services 1. Do you receive any sort of extension services available in your locality?
0 = No
1 = Yes
2. If yes, did you gain any knowledge from the extension agents that could help you
to do things differently on the specific commodities?
0 = No
1 = Yes
3 = If no, specify your reason_________________________
6.3 Access to other Services 1. Do you get market information about prices and demand conditions of agricultural
inputs and out puts?
0 = No
1 = Yes, if yes indicate the source of information___________________
1. Do you use input for the last one cropping season?
0 = No
1 = yes
3. How far do you travel to get local market __________________________km?
4. How far do you travel to get to the nearest school in your vicinity? ______ Km
5. How far do you travel to get the services of all weather roads? ______km
1 = Banks
2 = Friends/relatives
3 = Traders
4 = Microfinance
126
7. NON-FARM AND OFF – FARM INCOME
7.1. Do any member of your family has involved last year on non/off farm activities?
0 = No 1 = Yes, if the answer is yes, in which one from the next table.
No Off-Farm/Non-farm activities Amount
(birr)
Remark
1 Working on other‟ farm
2 Rent from motor Pump, Pedal pump, Rent from draft
power, and others
3 Daily laborer on construction or other non- farm
activities
4 Self employment in manufacturing e.g. Artisan
(blacksmith, weaving, pottery, )
5 Sales of wood (Charcoal)
6 Sales of local drink
7 Transporting using Carts
8 Hair dressing
9 Sales of stone/sand
10 Salary from temporary or permanent employment
Remittance
Trade
Aid
Any comments:
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
_____________________________________________________________________
________________________________________
