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AgWater Solutions Project
Case Study
Agricultural Water Management Technology
Adoption in Zambia: Findings of a Household
Survey
Willem Colenbrander
Independent Consultant
Andrew Kabwe
Indpendent Consultant
Barbara van Koppen
IWMI, South Africa
in collaboration with
Farming Systems Association of Zambia (FASAZ)
July 2011
i
Acknowledgment
The authors and project partners wish to thank the Bill & Melinda Gates Foundation for the
generous grant that made this project possible.
The AWM Project
The AgWater Solutions project was implemented in five countries in Africa and two states in India
between 2008 and 2012. The objective of the project was to identify investment options and
opportunities in agricultural water management with the greatest potential to improve incomes and
food security for poor farmers, and to develop tools and recommendations for stakeholders in the
sector including policymakers, investors, NGOs and small-scale farmers.
The leading implementing institutions were the International Water Management Institute (IWMI),
the Stockholm Environment Institute (SEI), the Food and Agriculture Organization of the United
Nations (FAO), the International Food Policy Research Institute (IFPRI), International Development
Enterprises (iDE) and CH2MHill.
For more information on the project or detailed reports please visit the project website http://awm-
solutions.iwmi.org/home-page.aspx.
Disclaimers
This report is based on research funded by the Bill & Melinda Gates Foundation. The findings
and conclusions contained within are those of the authors and do not necessarily reflect
positions or policies of the project, its partners or the Bill & Melinda Gates Foundation.
Copyright © 2012, by IWMI. All rights reserved. IWMI encourages the use of its material provided
that the organization is acknowledged and kept informed in all such instances.
ii
Contents List of Tables .......................................................................................................................................... iii
List of Figures ......................................................................................................................................... iii
1. Introduction ........................................................................................................................................ 1
2. Household Wealth by Gender of Household Head and Adoption Status ........................................... 7
3. Time spent on farm work by gender of household head and by adoption status ........................... 10
4. Water Management .......................................................................................................................... 12
5. Differences between Owners of Irrigated and Rainfed Plots ........................................................... 13
6. Irrigated and Rainfed Plot Size and Yield .......................................................................................... 17
7. Net Yield from Irrigated and Rainfed Plots ....................................................................................... 20
8. Characteristics of owners of irrigated plots (adopters) only ............................................................ 21
9. Comparison of Adopter and Non- and Dis-adopter Plot Owners ..................................................... 23
10. Financing issues for irrigated and rainfed plots .............................................................................. 36
11. Marketing issues with irrigated and rainfed plots .......................................................................... 38
12. Changes in the households due to AWM technology adoption ..................................................... 40
13. Changes after AWM technology adoption in the households of married adopters ...................... 43
14. Changes related to years after adoption ........................................................................................ 44
15. Obstacles for future irrigation expansion ....................................................................................... 45
ANNEX 1: Additional Figures on AWM Technology and Farm Operations ........................................... 47
iii
List of Tables
Table 1.1: Sample data.
Table 1.2: Adopters, non- and dis-adoptors by gender of household head.
Table 2.1: Month food crop harvested last season ran out this season.
Table 2.2: Education level for adopters and non- and dis-adopters.
Table 3.1: Survey sample data.
Table 3.2: Percentage of household members working hours per day.
Table 3.3: Survey data.
Table 3.4: Hours worked by household members of adopter and non- and dis-adopter households.
Table 4.1: Natural water sources.
Table 4.2: Reliability and quality of water sources.
Table 5.1: Overview of adopters and non- and dis-adopters for all plots.
Table 5.2: Plot ownership frequencies by gender of household head.
Table 5.3: Plot ownership frequencies by district.
List of Figures
Figure 1.1: Household distribution by gender of household head and district.
Figure 1.2: AWM technology adoption status by district.
Figure 1.3: AWM technology adoption status by gender of household head.
Figure 1.4: AWM adoption by district.
Figure 1.5: Type of AWM technology adoption by gender of household head and district.
Figure 2.1: Asset ownership by gender of household head and spouse.
Figure 2.2: Frequency of fish or meat meals during the last week.
Figure 2.3: Asset ownership by household head, spouse and AWM adoption status.
Figure 3.1: Comparison of average times spent working on the farm by each household member of
male and female headed households.
Figure 3.2: Comparison of average times spent working on the farm by household members of
adopters and non- and dis-adopters.
Figure 5.1: Total average annual income from harvests sold by owners of irrigated and rainfed plots.
Figure 5.2: Total average annual income from harvest sold from all sampled irrigated and rainfed
plots.
Figure 5.3: Total average annual income from harvests sold by owners of irrigated and rainfed plots
in each district.
Figure 5.4: Average annual income from harvests sold by owners of each of the irrigated and rainfed
plots.
Figure 6.1: Average plot size for owners of irrigated and rainfed plots in the survey area.
Figure 6.2: Total average annual yields from harvests sold by owners of irrigated and rainfed plots.
Figure 6.3: Average plot size for all sampled irrigated and rainfed plots.
Figure 6.4: Total average annual yields from irrigated and rainfed plots in each district.
Figure 6.5: Average plot size for owners of irrigated and rainfed plots.
Figure 6.6: Total average annual yields from harvests sold by owners of irrigated and rainfed plots.
Figure 6.7: Average irrigated and rainfed plot size.
Figure 6.8: Average annual yield from harvests sold by owners of irrigated and rainfed plots.
iv
Figure 7.1: Comparison of net yields from harvest sold from irrigated plot 1 and rainfed plot 4.
Figure 8.1: Ownership of irrigated plot 1 and control over money from sales for produce.
Figure 8.2: Nature of acquisition of irrigated plots and encouragement in long-term investment.
Figure 8.3: Nature of acquisition of irrigated plot and encouragement in long-term investment and
gender of plot owner.
Figure 9.1: Irrigated plot 1 or rainfed plot 4 ownership and gendered decision making over produce
consumption or sale.
Figure 9.2.1: Hoeing (water source/AWM technology).
Figure 9.2.2: Hoeing (gender).
Figure 9.3.1: Ploughing (water source/AWM technology).
Figure 9.3.2: Ploughing (gender).
Figure 9.4.1: Irrigation (water source/AWM technology).
Figure 9.4.2: Irrigation (gender).
Figure 9.5.1: Sowing (water source/AWM technology).
Figure 9.5.2: Sowing (gender).
Figure 9.6.1: Weeding (water source/AWM technology).
Figure 9.6.2: Weeding (gender).
Figure 9.7.1: Disease and pest control (water source/AWM technology).
Figure 9.7.2: Disease and pest control (gender).
Figure 9.8.1: Supervising paid labour.
Figure 9.8.2: Supervising paid labour.
Figure 9.9.1: Harvesting (water source/AWM technology).
Figure 9.9.2: Havesting (gender).
Figure 9.10: Average plot size in ha for adopters and non- and dis-adopters.
Figure 9.11: Average gross yield in kw/ha from harvests sold on plots of adopters and non- and
disadopters.
Figure 10.1: Men’s plots: source of financing for all inputs.
Figure 10.2: Women’s plots: source of financing on all inputs.
Figure 10.3: Percentage of plot owners encountering problems with financing inputs.
Figure 10.4: Specific problems encountered by plot owners in financing inputs.
Figure 11.1: Irrigated plot 1 owners: percentage of encountering marketing problems.
Figure 11.2: Rainfed plot 4 owner: percentage of encountering marketing problems.
Figure 11.3: Irrigated plot 1 owners: percentage of encountering marketing problem.
Figure 11.4: Rainfed plot 4 owners: percentage of encountering marketing problems.
Figure 11.5: Marketing problems experience by plot owners.
Figure 11.6: Specific marketing problems experienced by gendered plot owners.
Figure 12.1: How household food security changed after AWM technology adoption.
Figure 12.2: How household income changed after AWM technology adoption.
Figure 12.3: How household food security, income and food production changed in FHHs and MHHs
after AWM technology adoption.
Figure 12.4: How household income changed in the opinion of FHHs and MHHs after AWM
technology adoption.
Figure 12.5: Changes due to adoption: How household food security changed in 4 districts after
AWM technology adoption.
v
Figure 12.6: Changes in household income: How household income changed after AWM technology
adoption.
Figure 13.1: Collaboration between spouses after AWM technology adoption.
Figure 13.2: Decision making on outputs and income between spouses after AWM technology
adoption.
Figure 14.1: Change in food security in the years after AWM technology adoption.
Figure 14.2: Change in household income in the years after AWM technology adoption.
Figure 15.1: Problems in getting suitable land for irritation with sufficient tenure for expansion by
gender of household head.
Figure 15.2: Problems in getting suitable land for irrigation with sufficient tenure security for
expansion by district and gender of household head.
Figure 15.3: Availability of inputs for irrigation by gender of household head.
Figure 15.4: Availability of inputs for irritation by district and gender of household head.
Annex 1
Figure A.1: Tree cutting.
Figure A.2: Hiring draught power.
Figure A.3: Using improved seeds.
Figure A.4: Fertilizer application.
Figure A.5: Transplanting.
Figure A.6: Use of herbicides.
Figure A.7: Hiring paid labour.
Figure A.8: Transporting harvest.
1
1. Introduction
This report presents the results of a household survey on Agricultural Water Management
Technology Adoption in Zambia. The household survey is one of the case studies conducted as part
of the Zambian component of the Agricultural Water Management Solutions project, carried out by
the International Water Management Institute in collaboration with the Food and Agricultural
Organization, International Development Enterprise, International Food Policy Research Institute,
Stockholm Environmental Institute, and CH2MHill (www.awm-solutions.iwmi.org).
The survey examined rainy season cropping and dry season irrigation in 2009/2010. The site and
sample selection were based on an Inventory of Agricultural Water Management Technologies for
the same project. This inventory captured the range of important Agricultural Water Management
(AWM) Technologies throughout Zambia, including buckets, dambos, river diversions, treadle pumps
and motor pumps, conservation agriculture, and public irrigation schemes.
To ensure sufficient frequencies of river diversions, treadle and motor pumps, conservation
agriculture, and public irrigation schemes, districts were selected where experts expected the
highest concentrations. Accordingly, the selection included Mpika (river diversions), Chibombo
(treadle and motor pumps), Monze (conservation agriculture) and Sinazongwe (public irrigation
scheme). In these districts all households in adjacent area were interviewed, so adopters and non- or
dis-adopters were interviewed (Table 1.1, Figure 1.2).
Out of the total 1,935 households interviewed, surveyors randomly selected 60 households in each
of the 4 districts for a total of 240 households1. In the 191 Male Headed Households, 182
respondents were Male Household Heads (MHHs), while in 9 cases the respondent was the wife. For
the 49 Female Headed Households (FHHs), all 49 respondents were household heads (Figure 1.1).
The field work for this analysis was conducted by the Farming Systems Association of Zambia
(FASAZ).
Figure 1.1: Household distribution by gender of household head and district.
1 See Annex 2: Sample Data.
84%
77%
76%
82%
16%
23%
24%
18%
Sinazongwe
Monze
Chibombo
Mpika
n=
62
n=
60
n=
58
n=
60
Valid n = 240
Missing n = 0
Total n = 240
HH Distribution by Gender HH Head
and by District
MHH FHH
2
There were 240 households in the sample, of which 191 (80%) were MHHs and 49 (20%) FHHs (Table
1.1). Among the FHHs, 43 (18%) are de jure (i.e. not married) and 6 (2%) de facto married, but the
husband is not in the household head.
Table 1.1: Sample data.
Districts Adopters Dis-adopters Non-adopters Total
No. % No. % No. % No. %
Mpika 42 70 9 15 9 15 60 100
Chibombo 41 71 9 16 8 14 58 100
Monze 40 67 16 27 4 7 60 100
Sinazongwe 39 63 18 29 5 8 62 100
Total 162 52 26 240
Between 60% and 70% of the sample were households currently using one or more forms of AWM
technology (adopters), while the remainder are not currently using any form of AWM technology
(Figure 1.2). Among the latter are those who have never used an AWM technology (8-15% non-
adopters) and those that have used AWM technology before (15-29% dis-adopters).
Figure 1.2: AWM technology adoption status by district.
Between the 4 districts the adoption rates are not much different (Table 1.2 and Figure1.3), but
there are relatively more dis-adopters in Monze and Sinazongwe (27-29%) than in the other two
districts (15-16%).
Table 1.2: Adopters, non- and dis-adoptors by gender of household head.
Districts Adopters Dis-adopters Non-adopters Total
No. % No. % No. % No. %
MHH 135 71 41 21 15 8 191 100
FHH 27 55 11 22 11 22 49 100
Total 162 52 26 240
63%
67%
71%
70%
29%
27%
16%
15%
8%
7%
14%
15%
Sinazongwe
Monze
Chibombo
Mpika
n=
62
n=
60
n=
58
n=
60
valid n = 240
missing n = 0…
AWM Technology Adoption Status
by District
Adopters Dis-adopters
Non-adopters
3
Figure 1.3: AWM technology adoption status by gender of household head.
FHHs have a lower adoption rate (55%) than MHHs (71%). More FHHs are non-adopters (22%) than
MHHs (8%). There is not much difference between the MHHs and FHHs as far as dis-adoption is
concerned. In the 4 districts the farmers are using different technologies (Figure 1.4). Where the
bucket is the predominant technology in most districts, the next most important technology is
different for each of the districts2. The more advanced AWM technologies are most commonly used
in Mpika (50% of the adopters use river diversions) and Chibombo (29% of adopters use motor
pumps), followed by Sinazongwe (18% of adopters use
the irrigation scheme) and Monze (13% of adopters use conservation agriculture).
Figure 1.4: AWM adoption by district.
Buckets are used by all small-scale farmers in the survey area (and in fact all over Zambia). In this
report, ‘bucket’ refers to any type of container that can be used for carrying water (Photo 1). In this
2 Note: Neither electric pumps or rope and washer pumps were not found in any of the 4 districts and are
therefore not included in this report.
71%
55%
21%
22%
8%
22%
MHH
FHH
n=
19
1n
=4
9
Valid n = 240
Missing n = 0…
AWM Technology Adoption Status by
Gender of HH head
adopters dis-adopters non-adopters
67%
78%
66%
38%
0%
3%
29%
0%
18%
0%
0%
50%
15%
0%
0%
12%
0%
0%
5%
0%
0%
13%
0%
0%
0%
8%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Sinazongwe
Monze
Chibombo
Mpika
n=
39
n=
40
n=
41
n=
42
Valid n = 162
Missing n = 78
Total n = 240
AWM Adoption by District
bucket/watering can diesel/petrol pump
canal/river diversion dambos/wetlands
treadle pump conservation agriculture
hand pump rope and washer pump
electric pump
4
case the water is collected from a perennial stretch of the Maramba River. Farmers like buckets
because they are cheap, they have low or no maintenance costs, they are easy to handle and always
readily available for irrigation. Buckets are also commonly used for various household chores like
collecting water from a pump or well for drinking and other uses. Livestock can be watered with a
bucket. They can be easily lent and borrowed. There are no disadvantages in using a bucket. Other
water lifting devices farmers know and would like to use are motor pumps and treadle pumps.
Photo 1: Left: A woman using buckets to irrigate her rape field in Kasiya village near Livingstone,
Southern Province, Zambia. Credit: AWS. Right: A perennial part of the river which is used for
domestic chores like laundry and bucket irrigation by women
Dambos and wetlands are mainly found in Mpika and Sinazongwe and were analysed together with
the more dominant technologies in those districts. Dambos and wetland fields are individually
owned and managed and no payments are made for water.
Mpika: River diversions (Photo 2) are the most important AWM Technology, even more important
than buckets.
Photo 2. A typical river diversion in Mpika District.
The majority of river diversions are owned by groups of water users, of which the head of the
household is a member. The HH head pays for water and for maintenance and he/she also provides
labour for maintenance. The wife in a MHH also provides some labour. Some river diversions are
5
privately owned. Farmers like this technology because they can irrigate more land and more plots.
The technology is also easy to use.
Most households said that water from a river diversion is used for irrigation and for domestic uses
including drinking water.
Chibombo: This district was chosen because of the predominance of motorised pumps, mainly small
5hp portable petrol pumps. Chibombo is approximately 20 km north of Lusaka. The Great North
Road to Kabwe runs through Chibombo.
Photo 3 shows a motor pump being tested on a farm in the Katuba area. Water is pumped from an
unprotected shallow well, which provides water throughout the dry season. These wells may need
some deepening as the water table drops in the dry season.
Photo 3: Testing a small motor pump to draw water from a nearby well. Photo: AWS.
Pumps are generally owned by individuals. Pumps were provided to some groups by a Danida-
supported WWF project. Since then, some group members have bought their own pumps. Farmers
say that individual ownership means the pump is available when they want it for the household.
Pump owners find it easy to acquire this technology and the majority say that they have no reason
to prefer a different technology. They find the pump easy to operate, they have enough household
labour for irrigation with a pump, and they can irrigate more land than before. Only a few farmers
said that high fuel cost is a disadvantage. Half the farmers use the pumped water for drinking,
cooking and other domestic uses. None of the farmers have rented out their pumps.
Only two treadle pumps were found in the survey area (5%). In the remainder of this report, treadle
pumps are grouped under ‘other technologies’.
Monze: This district was chosen because of the predominance of conservation agriculture which has
been introduced over the past ten years. The most common conservation farming practices
observed were: crop rotation, mulching with organic residues, zero tillage and water harvesting (e.g.
potholes and bunds; (Photo 4). Hand-pumps are also quite common because they were installed
some 25 years ago when farm plots where allocated to farmers in Kayuni Settlement on an ex-
Kayuni State Farm.
6
Photo 4: Potholing is a common conservation
agriculture technique. Photo: AWS.
Sinazongwe: This district was chosen because there is a public irrigation scheme on the shores of
Lake Kariba. The scheme comprises a constructed lake established when the Kariba Dam was built in
the 1950s. The Valley Tongas used to have gardens on the banks of the Zambezi before the valley
was flooded.
Photo 5: Doing the luandry. Irrigation schemes like this
one in Sinazongwe are often used for muliple purposes.
Most users see the scheme as owned and managed by groups of water users comprised of
heads of households. They pay for water and contribute labour for maintenance, comparable to
the river diversion schemes in Mpika. Farmers like this scheme because it is easy to use and gives
more access to land for irrigation and wives and relatives can use the scheme. Water is also used for
non-irrigation purposes such as laundry (Photo 5), although there are no specific facilities like a
washing slab. The irrigation scheme in Sinazongwe is a de facto multiple use system.3 AWM
technologies used by gender of household head are displayed in Figure 1.5.
3 van Koppen, B. et al., (2009). Climbing the water ladder, multiple use water services for poverty reduction.
IRC and International Water Management Institute, Colombo, Sri Lanka.
7
Figure 1.5: Type of AWM technology adoption by gender of household head and district.
• Farmers in all districts use buckets as the main AWM technology except for Mpika, where river
diversions are used by 51% of the adopting MHHs. Only 39% of MHHs use buckets. For FHHs in
Mpika, buckets and river diversions are of equal importance. FHHs use dambos more frequently
and river diversions less frequently than MHHs.
• In Chibombo, motorised pumps are the most important after buckets, equally used by MHHs
and FHHs4.
• In Monze, conservation agriculture is the dominant technology after buckets and are equally
used by FHHs and MHHs.
• In Sinazongwe, the irrigation scheme is used by 21% of the MHHs and by none of the FHHs.
Dambos are used by FHHs (20%) and MHHs (15%).
2. Household Wealth by Gender of Household Head and Adoption
Status
Asset ownership by gender of household head (Figure 2.1)
All MHHs (n=191) and FHHs (n=49) were asked about the ownership of the following assets:
1. Housing: 1. improved dwelling, 2. improved toilet, 3. electricity
2. Farming equipment: 4. oxcart, 5. plough, 6. hoe, 7. axe
3. Livestock: 8. bulls, 9. cows, 10. oxen, 11. poultry
4. Other equipment: 12. mobile phone, 13. bicycle, 14. sewing machine, 15. TV, 16. satellite
dish
Male household heads own more assets than female household heads. Female household heads
own more assets than spouses. The most common assets are hoes and axes, while the least common
asset is improved housing.
4 In the Inventory, motor pump adoption rates are lower for FHHs (15%) than MHHs (31%). The difference
between the Inventory and household survey is explained by a slight divergence from fully proportionate
sampling.
65%
80%
79%
71%
65%
70%
38%
40%
0%
0%
3%
0%
29%
30%
0%
0%
21%
0%
0%
0%
0%
0%
51%
40%
15%
20%
0%
0%
0%
0%
11%
20%
0%
0%
12%
14%
0%
0%
0%
0%
0%
0%
6%
14%
6%
0%
0%
0%
n=34
n=5
n=33
n=7
n=31
n=10
n=37
n=5
MH
HF
HH
MH
HF
HH
MH
HF
HH
MH
HF
HH
Sin
azo
ngw
eM
on
zeC
hib
om
bo
Mp
ika
Valid n = 162
Missing n = 78
Valid n = 240
Type of AWM Technology Adoption by Gender
of HH head and by District
bucket/watering can diesel/petrol pump
canal/river diversion dambos/wetlands
conservation agriculture other
8
Figure 2.1: Asset ownership by gender of household head and spouse.
Seasonal food availability
The respondents were asked to name the month when the food crop they harvested last season ran
out during the current season (Table 2.1).
Table 2.1: Month food crop harvested last season ran out this season.
All figures are % MHH FHH De jure
FHH
De facto
FHH
N=191 N=49 N=43 N=6
Did not run out 20 16 16 17
January 8 6 7 0
February 8 0 0 0
March 7 6 7 0
April 6 8 9 0
May 4 4 2 17
June 7 10 12 0
July 6 6 5 17
August 9 8 7 17
September 6 12 14 0
October 5 8 9 0
November 4 8 7 17
December 7 4 5 0
Destroyed 2 2 0 17
There is no clear pattern that differentiates the 4 household categories. One would expect food
shortages the few months before the harvest (January, February, March) but the results do not bear
this out. The sample households did not belong to the poorest families because most have two or
three meals per day. In Zambia it is generally considered that the poorest households have only one
meal per day. Food stress would show a clear seasonal shortage pattern the few months before
harvesting, which is not the case here.
Frequency of nutritious (protein-rich) meals by household head
The respondents were asked how many times they had eaten fish or meat in the last week (Figure
2.2). Almost half the FHHs had not eaten a nutritious meal in the last week, while this only applied to
one quarter of the MHHs.
0% 20% 40% 60% 80% 100%
improved housing
other equipment
oxcart/plough
hoe
axe
cattle
poultryn
=4
5n
=3
32
n=
83
n=
33
4n
=2
67
n=
10
0n
=2
52
Valid n = 1,423
Missing n = 4,408
Total n = 5,831
Asset ownership (wealth) by Gender of
HH head and Spouse
Male HH Head Female HH Head Spouse
9
Figure 2.2: Frequency of fish or meat meals during the last week.
Asset ownership by adopters and non- and dis-adopters
All adopters (n=162) and non- and dis-adopters (n=78) were asked about the ownership of the
following assets (Figure 2.3):
1. Housing: improved dwelling, improved toilet, electricity
2. Farming equipment: oxcart, plough, hoe, axe
3. Livestock: bulls, cows, oxen, poultry
4. Other equipment: mobile phone, bicycle, sewing machine, TV, satellite dish
Household heads and spouses of adopter households have a slightly higher asset ownership status
than household heads and spouses of non- and dis-adopter households.
Figure 2.3: Asset ownership by household head, spouse and AWM adoption status.
2.5: Highest education level for adopters and non- and dis-adopters
There is little difference between adopters and non- and dis-adopters in terms of education level
(Table 2.2).
24%
43%
28%
18%20%
25%
13%
8%9%
2%2% 2%0%
2%3%0%1% 0%
MHH (n=191) FHH (n=49)Valid n = 240
Missing n = 0
Total n = 240
Frequency of fish or meat meals
during the last week
none 1 meal 2 meals 3 meals 4 meals
5 meals 6 meals 7 meals 8 meals
0% 20% 40% 60% 80% 100%
HH head
Spouse
HH head
Spouse
HH head
Spouse
HH head
Spouse
HH head
Spouse
HH head
Spouse
HH head
Spouse
imp
rov
ed
ho
usi
ng
oth
er
eq
uip
me
nt
oxc
art
/
plo
ug
hh
oe
axe
catl
lep
ou
ltry
n=
45
n=
33
2n
=8
3n
=3
44
n=
26
7n
=1
00
n=
25
2
Valid n = 1,423
Missing n = 4,408
Total n = 5,831
Asset ownership (wealth) by HH head, Spouse and AWM
Adoption Status
adopters dis-/non-adopters
10
Table 2.2: Education level for adopters and non- and dis-adopters.
Highest education level Non- and dis-adopters
N=418
Adopters
N=1018
% %
None 33 31
Primary 49 44
Junior 13 17
Senior 3 6
College/university 1 0
3. Time spent on farm work by gender of household head and by
adoption status
The total number of respondents for this analysis was 240 households with an average household
size of 6.04 = 1,450 household members (Table 3.1). More MHH members do not work on the farm
(42%) compared to FHH members (33%). FHHs have a smaller household size from which to draw
labour (Table 3.2).
Table 3.1: Survey sample data.
Mean
MHH 6.37
FHH 4.73
All HHs 6.04
Table 3.2: Percentage of household members working hours per day.
Hours MHH FHH
Total N N % N %
Zero 507 42 75 33 582
1-4 438 36 106 46 544
4-6 179 15 33 14 212
>6 87 7 16 0 103
Total 1211 230 1441
In Figures 3.1 and 3.2, household members are numbered from 1 to 14, where 1 is always the
household head (male or female) and 14 is the youngest, often a grandchild. Number 2 is the wife in
a MHH, if applicable. Then follow other members of the family (children and father, mother, brother
and sister of head, etc.).
The following trends can be seen:
• Only a few household heads do not work at all. Work is done most frequently by the household
head and the person immediately following the household head (e.g. wife in MHH).
• For longer working hours, the responsibility shifts from the household as a whole to the
household head and the wife in a MHH, where more household heads take up the heavier
workloads.
• In MHHs, wives do an equal amount of work as their husbands, up to workloads of 6 hours.
When the workload goes beyond 6 hours, more often household heads do the work.
11
• In FHHs, the household head is assisted by the second person in that household but for longer
working hours the responsibility shifts to the household head with less help from the second
person.
Comparison of average times spent working on the farm by each household member of male and
female headed households
Figure 3.1: Comparison of average times spent working on the farm by each household member of
male and female headed households.
The total number of survey respondents for this analysis was 240 households with an average
household size of 6.04 (Table 3.3) or 1,450 household members.
Table 3.3: Survey data.
Mean
Non- and dis-adopters 5.40
Adopters 6.35
All HHs 6.04
Slightly more non- and dis-adopter household members do not work on the farm at all (45%)
compared to adopter household members (39%). More adopter household members (41%) work 1-4
hours more than members of the non- and dis-adopter households (30%). The following trends can
be seen from Table 3.4 and Figure 3.2. Overall, more adopter household members are involved in
farm work than non- and dis-adopter household members, and more household heads work longer
hours than the second adult in the household (e.g. the wife in a MHH).
1. For workloads of 1-4 hours, the adopters spread the load out over more family members than
the non- and dis-adopters. Adopter households have a larger average household size (6.35) to
depend on for work than the non- and dis-adopter households (5.40).
2. For heavier workloads the responsibility shifts from the household as a whole to the household
head and wife in a MHH, where more household heads take on a heavier workload.
3. There is a slight trend that more adults in adopter households take on the heavier workloads
than in the non- and dis-adopter households.
0% 10% 20% 30% 40% 50% 60%
Zero hrs
Zero hrs
1 - 4 hrs
1 - 4 hrs
4 - 6 hrs
4 - 6 hrs
>6 hrs
>6 hrs
MH
HF
HH
MH
HF
HH
MH
HF
HH
MH
HF
HH
n=
50
7n
=7
5n
=4
38
n=
10
6n
=1
79
n=
33
n=
87
n=
16
Valid n = 1448
Missing n = 2
Total n = 1450
Comparison of average time spent working on the farm
by each HH member of FHHs and MHHs
HH HEAD
Wife (in MHH)
3
4
5
6
7
8
9
10
11
12
13
youngest
12
Table 3.4: Hours worked by household members of adopter and non- and dis-adopter households.
Hours Adopters Non-/Dis-adopters
Total N % N % N
Zero 39 394 45 188 582
1-4 41 418 30 126 544
4-6 14 146 16 66 212
>6 6 64 9 39 103
Total 1022 419 1441
Comparison of average times spent working on the farm by household members of adopters and
non- and dis-adopters.
Figure 3.2: Comparison of average times spent working on the farm by household members of
adopters and non- and dis-adopters.
4. Water Management
Natural water sources for buckets and motorised pumps
Ground water is the most common natural water source. Shallow ground water can be reached by
digging an unprotected shallow well. This is common in Chibombo (Katuba area). Motor pumps have
an average maximum suction head of 8 meters (Table 4.1).
Table 4.1: Natural water sources.
Perennial
river/stream
Seasonal
river/stream Pond/lake Groundwater Dambo
Bucket takes
water from
11 5 4 68 12
11% 5% 4% 68% 12%
Motor pump
takes water
from
3 0 2 10 0
20% 0 13% 67% 0
Water reliablity and availability
Lake and spring water seem to be the most reliable sources, followed by perennial streams and
groundwater. Less reliable groundwater sources are dambos and seasonal streams (Table 4.2).
0% 10% 20% 30% 40% 50%
non-/dis-adopters
adopters
non-/dis-adopters
adopters
non-/dis-adopters
adopters
non-/dis-adopters
adopters
zero
hrs
zero
hrs
1-4
hrs
1-4
hrs
4-6
hrs
4-6
hrs
>6
hrs
>6
hrs
n=
18
8n
=3
94
n=
12
6n
=4
18
n=
66
n=
14
6n
=3
9n
=6
4
Valid n = 1441
Missing n = 9
Total n = 1450
Comparison of average time spent working on the farm by each
HH member of adopters and non-/dis-adopters
HH HEAD
wife (in MHH)
3
4
5
6
7
8
9
10
11
12
13
youngest
13
Table 4.2: Reliability and quality of water sources.
Question about reliability Water source
Lake/spring Perennial
stream
Ground
water Dambo
Seasonal
stream
Water is available in October 93% 89% 86% 79% 67%
Number of yes
answers/number of
respondents
13/14 31/35 72/84 15/19 4/6
Water quality is no problem 100% 91% 96% 95% 100%
Number of yes
answers/number of
respondents
14/14 32/35 80/83 19/20 6/6
5. Differences between Owners of Irrigated and Rainfed Plots
This section deals with the owners, by gender, of irrigated and rainfed plots. General characteristics
are displayed in Table 5.1.
Table 5.1: Overview of adopters and non- and dis-adopters for all plots.
Adopters Non- and dis-adopters Total
Irrigated Plot Owners
Husband 158 158
Wife 21 21
Male HH Head 3 3
Female HH Head 22 22
Irrigated sub-total 204 204
Rain-fed Plot Owners
Husband 193 67 260
Wife 27 21 48
Male HH Head 4 5 9
Female HH Head 25 18 43
Rainfed sub-total 249 111 360
Total 453 111 564
Data were collected for the three main irrigated plots (numbered 1, 2, 3) and the three main rainfed
plots (4, 5, 6). The frequencies in Table 5.2 were used as the n values in Figure 5.1. Table 5.2 shows
that adopters as well as non- and dis-adopters are owners of rainfed plots.
14
Table 5.2: Plot ownership frequencies by gender of household head.
Plot Description Husband Wife
Single
Male HH
head
Single
Female
HH head
Total
1 Irrigated 109 15 2 20 146
2 Irrigated 38 5 1 2 46
3 Irrigated 11 1 0 0 12
Sub-total irrigated plots 158 21 3 22 204
4 Rainfed 144 13 6 37 200
5 Rainfed 74 30 2 0 106
6 Rainfed 42 5 1 6 54
Sub-total rainfed plots 260 48 9 43 360
Total 418 69 12 65 564
Income from harvest sold per gendered plot owner category
Figure 5.1 shows the main differences in average annual income from harvests (not the value of total
harvest) between owners of irrigated and rainfed plots:
• Husbands have a higher income than wives from both irrigated and rainfed plots.
• Wives earn more income from irrigated plots than single women (FHH heads).
• Single women earn more income from rainfed plots than wives.
Figure 5.1: Total average annual income from harvests sold by owners of irrigated and rainfed plots.
The frequencies in Table 5.3 were used as the n values in Figures 5.2, 5.3 and 5.4).
Table 5.3: Plot ownership frequencies by district.
Plot Description Mpika Chibombo Monze Sinazongwe Total
1 Irrigated 36 41 35 34 146
2 Irrigated 20 16 3 7 46
3 Irrigated 2 6 1 3 12
Sub-total irrigated plots 58 63 39 44 204
4 Rainfed 56 54 52 38 200
5 Rainfed 44 24 29 9 106
6 Rainfed 25 10 16 3 54
Sub-total rainfed plots 125 88 97 50 360
Total 183 151 136 94 564
0 5,000,000 10,000,000 15,000,000
Husband
Wife
Single Male HH Head
Single Female HH Head
n=
41
8n
=6
9n
=1
2n
=6
5
US $ 1000 2000 3000
Total Average Annual Income from Harvest Sold by
Owners of Irrigated and Rainfed Plots in the whole
survey area
Total Average Annual Income in Kwacha from Irrigated Plots 1, 2 & 3
Total Average Annual Income in Kwacha from Rainfed Plots 4, 5 & 6
15
Income from harvest sold per district
Figure 5.2 shows the main similarities and differences in average annual income between the
districts.
• Chibombo, where motor pumps are the most common AWM technology after buckets, has a
higher income from irrigated than from rainfed plots.
• Chibombo has by far the highest income from irrigated as well as rainfed plots compared to the
other three districts, possibly because of its proximity to the Lusaka market (about 20 km).
• In Chibombo (motor pumps) and Sinazongwe (irrigation scheme and dambos near Lake Kariba)
the income from irrigated plots is higher than the income from rainfed plots. Sinazongwe has
hardly any income from rainfed plots.
• In Mpika (river diversions) the income from rainfed crops is higher than from irrigated plots.
• In Monze (conservation agriculture), the income from rainfed plots is higher than from irrigated
plots, which are 78% irrigated by buckets and 13% cultivated under conservation agriculture.
Figure 5.2: Total average annual income from harvest sold from all sampled irrigated and rainfed
plots.
Figures 5.3 shows average annual incomes from harvests sold in more detail.
• In Chibombo, FHH heads earn far more income from rainfed plots than wives, while in the other
three districts wives earn more from rainfed plots than female household heads.
• Husbands earn more than wives from irrigated plots, while wives earn more from irrigated plots
than female household heads.
0 2 4 6 8 10 12
Sinazongwe
Monze
Chibombo
Mpika
n=
94
n=
13
6n
=1
51
n=
18
3
US$ 400 1,200 2,400
Kwacha Millions
Total Average Annual Income from Harvest Sold from all
sampled Irrigated and Rainfed Plots in each District
Total Average Annual Income from Irrigated Plots 1, 2 & 3
Total Average Annual Income from Rainfed Plots 4, 5 & 6
16
Figure 5.3: Total average annual income from harvests sold by owners of irrigated and rainfed plots
in each district.
Figure 5.4 shows distinct patterns for average annual income by gendered plot ownership5. For the
three districts with a good number of owners of irrigated and rainfed plots (Mpika, Chibombo and
Monze):
• Husbands have, on average, a minimum of 3 irrigated plots and 3 rainfed plots.
• Compared to husbands, wives have fewer plots, on average only 1 or 2 irrigated plots and 1 to 3
rainfed plots. Wives in Mpika have up to 5 plots, while in Chibombo and Monze up to 3 plots.
• Compared to husbands and wives, female household heads have fewer plots (1 or 2 irrigated
plots and 1 to 2 rainfed plots).
• In Sinazongwe, the husband has up to 2 irrigated plots while the others have only 1 irrigated
plot.
5 Where a plot does not show in the Figure it means there is no income from sales from that plot.
0 1 2 3 4 5 6 7 8
Husband
Wife
Single Male HH Head
Single Female HH head
Husband
Wife
Single Male HH Head
Single Female HH head
Husband
Wife
Single Male HH Head
Single Female HH head
Husband
Wife
Single Male HH Head
Single Female HH head
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
n=
94
n=
13
6n
=1
51
n=
18
3
US$ 200 600 1000 1400
Kwacha Millions
Total Average Annual Income from Harvests Sold by
Owners of Irrigated and Rainfed Plots in each District
Total Average Annual Income from Irrigated Plots 1, 2 & 3
Total Average Annual Income from Rainfed Plots 4, 5 & 6
17
Figure 5.4: Average annual income from harvests sold by owners of each of the irrigated and rainfed
plots.
6. Irrigated and Rainfed Plot Size and Yield6
The total hectares of rainfed plots is larger than the total hectares of irrigated plots (Figure 6.1).
Husbands have more hectares for both rainfed and irrigated plots compared to wives and other
owner categories.
Figure 6.1: Average plot size for owners of irrigated and rainfed plots in the survey area.
For all owner categories, the yields per hectare from harvest sales are higher for irrigated plots than
for rainfed plots (Figure 6.2). Irrigation is for cash crops, while harvests from rainfed plots are mostly
consumed as staple foods.
6 See Chapter 9 “Adopter and non- and dis-adopter plot owners”, Figures 9.10. and 9.11 for plot size and yields
specified for adopters and non- and dis-adopters.
0 1 2 3 4
Husband
Wife
Single male HH Head
Single female HH head
Husband
Wife
Single male HH Head
Single female HH head
Husband
Wife
Single male HH Head
Single female HH head
Husband
Wife
Single male HH Head
Single female HH head
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
n=
94
n=
13
6n
=1
51
n=
18
3
US$ 200 400 600
Kwacha Millions
Average Annual Income from Harvests Sold by Owners of
each of the Irrigated and Rainfed Plots in the Districts
Average Annual Income from Irrigated plot 1 Average Annual Income from Irrigated plot 2
Average Annual Income from Irrigated plot 3 Average Annual Income from Rainfed plot 4
Average Annual Income from Rainfed plot 5 Average Annual Income from Rainfed plot 6
0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00
Husband
Wife
Male HH Head
Female HH Head
n=
41
8n
=6
9n
=1
2n
=6
5
Average Plot Size for owners of Irrigated and
Rainfed Plots in the whole survey area
Ha Irrigated Plots 1,2,3 Ha Rain-fed Plots 4,5,6
18
• Husbands have higher yields in both irrigated and rainfed plots than their wives.
• Female household heads have slightly higher yields on their rainfed fields than other owner
categories and their yields on rainfed and irrigated fields are almost the same. For other owner
categories, the yields for irrigated plots are much higher than yields for rainfed plots.
Figure 6.2: Total average annual yields from harvests sold by owners of irrigated and rainfed plots.
In all districts, the average rainfed plot sizes are much larger than irrigated plot sizes (Figure 6.3).
Figure 6.3: Average plot size for all sampled irrigated and rainfed plots.
• Yields from harvests sold are higher in irrigated fields than in rainfed fields (Figure 6.4).
• Chibombo has a much higher yield from irrigated plots than other districts.
• Chibombo also has a higher yield from rainfed farming compared to the other districts.
Figure 6.4: Total average annual yields from irrigated and rainfed plots in each district.
In all districts, husbands’ irrigated plots are larger than their wives’ plots and other owner category
plots. Husbands’ rainfed plots are usually larger than those of other owners, except for Mpika where
the husbands’ and wives’ rainfed plots are approximately the same size (Figure 6.5).
0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000
Husband
Wife
Male HH Head
Female HH Head
n=
41
8n
=6
9n
=1
2n
=6
5
US$ 200 600
Total Average Annual Yield from Harvests Sold by owners of
Irrigated and Rainfed Plots in the whole survey area
Kw/Ha Irrigated Plots 1,2,3 Kw/Ha Rain-fed Plots 4,5,6
0.00 1.00 2.00 3.00 4.00 5.00 6.00
Sinazongwe
Monze
Chibombo
Mpika
n=
94
n=
13
6n
=1
51
n=
18
3
Average Plot Size for all sampled Irrigated and
Rainfed Plots in each District
Ha Irrigated Plot 1,2,3 Ha Rain-fed Plot 4,5,6
0 1 2 3 4 5 6 7 8 9
Sinazongwe
Monze
Chibombo
Mpika
n=
94
n=
13
6n
=1
51
n=
18
3
US$ 200 600 1000 1400
Millions
Total Average Annual Yield from Harvests Sold from all sampled
Irrigated and Rainfed Plots in each District
Kw/Ha Irrigated Plot 1,2,3 Kw/Ha Rain-fed Plot 4,5,6
19
Figure 6.5: Average plot size for owners of irrigated and rainfed plots.
Chibombo has the highest yields from harvests from irrigated plots by all owner categories (except
MHHs which have a low frequency (Figure 6.6). In all districts for all owner categories, the yield from
harvests sold from irrigated plots is considerably higher than from rainfed plots.
Figure 6.6: Total average annual yields from harvests sold by owners of irrigated and rainfed plots.
There is little difference between the plot sizes of the 3 irrigated plots, which are mostly between
0.1 and 0.3 ha. Irrigated plot sizes are limited because of water availability and type of technology
(mostly buckets). Size of rainfed plots differ considerably. Plot 4 is much larger (about 1 ha) than
plots 5 and 6 (around 0.5 ha). Plot 4 could be the main staple food crop or the main cash crop, while
the other smaller rainfed plots could be vegetables and other crops (Figure 6.7).
0.00 0.50 1.00 1.50 2.00 2.50
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
n=
94
n=
13
6n
=1
51
n=
18
3
Average Plot Size for owners of Irrigated and Rainfed
Plots in each District
Ha Irrigated Plot 1,2,3 Ha Rain-fed Plot 4,5,6
0 2 4 6 8 10 12
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
n=
94
n=
13
6n
=1
51
n=
18
3
US$ 400 1,200 2,000
Kwacha Millions
Total Average Annual Yield from Harvests Sold by owners
of Irrigated and Rainfed Plots in each District
Kw/Ha Irrigated Plot 1,2,3 Kw/Ha Rain-fed Plot 4,5,6
20
Figure 6.7: Average irrigated and rainfed plot size.
Yields from smaller rainfed plot 6 are usually higher than from the larger rainfed plot 4. It may be
that the smaller rainfed plots are used for rainy season vegetables grown for sale (Figure 6.8).
Figure 6.8: Average annual yield from harvests sold by owners of irrigated and rainfed plots.
7. Net Yield from Irrigated and Rainfed Plots
Deducting cost of inputs7 from harvest sales income gives net income from sales. The net yield is
calculated as the net income per hectare. The net yield from all the irrigated plots is greater than
zero, while the net yield from rainfed plots is marginally greater than zero or less than zero, in which
case sales from rainfed plots are not sufficient to cover costs. One possible explanation is that
rainfed plots are mainly used to grow food crops for household consumption, although vegetables
for sale are also grown on rainfed plots (Figure 7.1).
7 Cost of Inputs as defined in the Questionnaire was erroneously recorded as Cost of Seeds in the SPSS files.
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
n=
94
n=
13
6n
=1
51
n=
18
3
Average Plot Size for owners of each of the Irrigated
and Rainfed Plots in the Districts
Ha Irrigated Plot 1 Ha Irrigated Plot 2 Ha Irrigated Plot 3
Ha Rain-fed Plot 4 Ha Rain-fed Plot 5 Ha Rain-fed Plot 6
0 4,000,000 8,000,000 12,000,000 16,000,000
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Husband
Wife
Male HH Head
Female HH Head
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
n=
94
n=
13
6n
=1
51
n=
18
3
US$ 800 1,600 2,400
Average Annual Yield from Harvests Sold by owners of each of
the Irrigated and Rainfed Plots in the Districts
Kw/Ha Irrigated Plot1 Kw/Ha Irrigated Plot2 Kw/Ha Irrigated Plot3
Kw/Ha Rain-fed Plot4 Kw/Ha Rain-fed Plot5 Kw/Ha Rain-fed Plot6
21
Figure 7.1: Comparison of net yields from harvest sold from irrigated plot 1 and rainfed plot 4.
8. Characteristics of owners of irrigated plots (adopters) only
The relationship between ownership of irrigated plots and control over money from sales of produce
of the plots shows the following trends. In most cases the owner decides. In a minority of cases the
wife decides (24%) instead of the husband-owner, the husband decides (15%) instead of the wife-
owner, or somebody else (7%) decides instead of the female household head owner.
• When female household heads are owners, in 93% of the cases they control the money.
• When wives are owners, in 69% of the cases they control the money.
• When husbands are owners, in 57% of the cases they control the money.
Figure 8.1 shows that more female household heads have control over money than decision making
power over consumption or sale of produce (93% as compared to 80%) and the same is the case for
wives (69% as compared to 60%). Fewer husbands have control over money than decision making
power over sale or consumption (57% as compared to 68%).
-2 0 2 4 6 8 10 12 14 16
Husband
Wife
Male HH Head
Female HH head
Husband
Wife
Male HH Head
Female HH head
Husband
Wife
Male HH Head
Female HH head
Husband
Wife
Male HH Head
Female HH headS
ina
zon
gw
eM
on
zeC
hib
om
bo
Mp
ika
US$ 400 1,200 2,400
Kwacha Millions
Comparison of Net Yield from Harvests Sold from
Irrigated Plot 1 and Rain-fed Plot 4
Net Yield from Irrigated Plot 1 Net Yield from Rain-fed Plot 4
22
Figure 8.1: Ownership of irrigated plot 1 and control over money from sales for produce.
Nature of land acquisition and encouragement to invest
In Zambia land can be acquired through:
• Customary procedures through the headman/chief or through a relative.
• Modern legal procedures, such as renting (within customary tenure), getting title deeds or
getting access through being member of a cooperative.
The nature of land acquisition determines the level of confidence farmers have in investing in land in
the long term. Farmers appear to have more confidence in customary than in modern forms of land
ownership. As can be seen in Figure 8.2.
• A majority of farmers acquired land through customary procedures, either recently or in the
past. The frequency for customary procedures is 126 cases, while the frequency for modern
procedures is only 23.
• Approximately 12% of farmers who acquired land through customary procedures are
discouraged to invest in the long term (possibly due to land disputes) while almost half (44%)
who acquired land through various modern procedures where lacking confidence in long-term
investment.
Figure 8.2: Nature of acquisition of irrigated plots and encouragement in long-term investment.
Nature of land acquisition and encouragement to invest and gender of irrigated plot
owner
The general confidence of farmers in customary land ownership shows equally among the gender
categories of irrigated plot owners: husbands, wives, and female household heads. Only a few
owners are discouraged (5% of female household heads and 7% of husbands) (Figure 8.3).
For modern forms of land ownership:
50%
57%
15%
93%
30%
24%
69%
20%
19%
15%
7%
n=11
n=90
n=13
n=14
Oth
ers
Hu
sba
nd
Wif
e
Fe
ma
le
HH
he
ad
valid n = 128 CONTROL OVER MONEY FROM SALES
missing n = 112
total n = 240
OW
NER
SH
IP O
F IR
RIG
ATE
D P
LOT
1
Relation between Ownership of Irrigated Plot 1
and Control over Money from Sales of Produce
Male or Female HH Head
Wife
Others
43%
31%
34%
36%
14%
25%
54%
62%
43%
44%
12%
1%
n=7
n=16
n=59
n=77
Go
v /
Co
op
ren
ted
He
ad
ma
nre
lati
ve
mo
de
rncu
sto
ma
ry
valid n = 159 ENCOURAGEMENT IN LONG TERM INVESTMENT
missing n = 81
total n = 240
NA
TUR
E O
F A
CQ
UIS
ITIO
N O
F IR
RIG
ATE
D P
LOT
1
Relation between nature of acquisition of irrigated plots
and encouragement in long term investment
Encouraged No influence Discouraged
23
• There were no female household heads in the sample who acquired land through modern
procedures.
• There were more wives (67%) than husbands (42%) who were discouraged by modern forms of
land ownership.
Figure 8.3: Nature of acquisition of irrigated plot and encouragement in long-term investment and
gender of plot owner.
9. Comparison of Adopter and Non- and Dis-adopter Plot Owners
Gendered plot ownership and decision making is characterized in terms of decision making over the
choice to consume produce or sell it (Figure 9.1). In general, the owner decides; the female
household head more than the husband, and the husband more than the wife. Wife-owners have a
stronger say in their rainfed plots and wives of husband-owned plots have more say in the irrigated
plots. It seems that irrigation strengthens the decision making power of wives.
• When female household heads are owners, in more than 80% of the cases they decide. They
may be adopter owners of irrigated or rainfed plots, or non- or dis-adopter owners of rainfed
plots. Their control over their rainfed plots is strongest in terms of deciding whether the produce
will be consumed or sold.
• When wives are owners, there is always a proportion whose husbands decide, but when they
are adopter owners, a higher proportion of wives have decision making power (50-60%) than
when they are non- or dis-adopter owners (43%). Wives who are adopter owners of irrigated
plots more often have decision making power (60%) than wives who are adopter owners of
rainfed plots (50%).
• When husbands are owners, their wives decide in at most 13% of the cases, but their decision
making power is much more frequent (70%) than that of wife-owners (40-60%).
50%
29%
33%
37%
0%
25%
0%
35%
13%
71%
25%
56%
33%
75%
0%
60%
38%
0%
42%
7%
67%
0%
0%
5%
n=8
n=7
n=12
n=97
n=3
n=12
n=0
n=20
mo
-
de
rn
cust
o-
ma
ry
mo
-
de
rn
cust
o-
ma
ry
mo
-
de
rn
cust
o-
ma
ry
mo
-
de
rn
cust
o-
ma
ry
Oth
ers
Hu
sba
nd
Wif
e
Fe
ma
le H
H
he
ad
valid n = 159 ENCOURAGEMENT IN LONG TERM INVESTMENT
missing n = 81
total n = 240
NA
TU
RE
OF
AC
QU
ISIT
ION
OF
IR
RIG
AT
ED
PLO
T 1
Relation between nature of acquistion of irrigated
plot and encouragement in long term investment,
by gender of plot owner
Encouraged No influence Discouraged
24
Figure 9.1: Irrigated plot 1 or rainfed plot 4 ownership and gendered decision making over produce
consumption or sale
Technology adoption, gendered plot ownership and farm operations
In this section, the most common farm operations are cross-tabulated with AWM technology
adoption status of the household8 and with the gendered ownership of irrigated plot 1 and rainfed
plot 4. Table 9.1 shows the data for these analyses.
Table 9.1: Survey data.
8 Additional Figures in Annex 1.
17%
14%
2%
0%
0%
0%
94%
100%
80%
17%
0%
15%
2%
6%
13%
43%
50%
60%
0%
0%
42%
14%
39%
71%
71%
69%
43%
33%
20%
0%
0%
25%
71%
39%
7%
12%
13%
0%
17%
20%
0%
0%
10%
0%
0%
8%
17%
12%
6%
14%
0%
6%
0%
10%
Others - non-adopter owner plot 4
Others - adopter owner plot 4
Others - adopter owner plot 1
HUSBAND - NON-ADOPTER owner plot 4
HUSBAND - ADOPTER owner plot 4
HUSBAND - ADOPTER owner plot 1
WIFE - NON-ADOPTER owner plot 4
WIFE - ADOPTER owner plot 4
WIFE - ADOPTER owner plot 1
FEMALE HH HEAD - NON-ADOPTER owner plot 4
FEMALE HH HEAD - ADOPTER owner plot 4
FEMALE HH HEAD - ADOPTER owner plot 1
n=
12
n=
7n
=1
5n
=4
1n
=1
03
n=
10
9n
=7
n=
6n
=1
5n
=1
6n
=2
1n
=2
0
Decision over Consumption or Sale
Relation between Irrigated Plot 1 or Rainfed Plot 4 ownership
and Gendered Decision over Produce Consumption or Sale
Female HH head Wife Husband Others NAP
Adoption status (Total N=240) N
Dambos/wetland 11
Canal/river diversion 28
Diesel/petrol pump 13
Bucket/watering can 101
4 other AWM technologies 9
Non-and dis-adopters 78
Owners of Rainfed Plot 49 N
Husband 144
Wife 13
Female HH head 37
Others 19
Not applicable 27
Total N 240
Owners of Irrigated Plot 1 N
Husband 109
Wife 15
Female HH head 30
Others 15
Not applicable 81
Total N 240
25
In Figures 9.2 to 9.11), the Valid n and Total N values are presented for each of the adopter
categories or each of the plot owner categories as ratios in the form: Valid n:Total N (n:N).
Example: Hoeing by dambos/wetland adopters has an n ratio occurrence of 10:11 which means that
10 of the 11 adopters do hoeing, while ploughing by dambos/wetland adopters has an n:N ratio of
3:11 which means that only 3 of the 11 adopters do ploughing. The n:N ratio is an indication of the
relative importance of a farm operation. The higher the Valid n, the more common the operation. In
this example, it would mean that hoeing is much more common than ploughing and that farm
mechanisation in the sample households is not common.
A broad analysis (Table 9.2) shows the general patterns of labour provision by gender. For most
labour intensive farm operations, labour contributions are equally made by men and women,
although sowing is mostly done by women.
• The more strenuous and skilled jobs, like ploughing, and the more technical jobs like disease and
pest control are mainly done by men. Supervision of paid labour is mostly done by men.
• At times children provide labour, but only in a few cases. When children provide labour they are
mostly helping their mothers in the field.
Table 9.2: Overview of labour provision by gender.
Farm operator category Provision of labor
Male Female
Land preparation
Hoeing + +
Ploughing +
Cultivation
Sowing +
Irrigation + +
Weeding + +
Disease and pest control +
Supervising paid labor +
Harvesting + +
The following questions framed the interpretation of Figures 9.2 to 9.11:
• What is the most characteristic labour profile?
• In the n:N ratio: how important is the operation, i.e. what is the relative number of respondents
who perform that operation?
• Is there any difference between adopters and non- and dis-adopters? Is there any difference
between technologies?
• Is there any difference between irrigated plot 1 and rainfed plot 4?
• Is there any difference between the gendered plot owners of irrigated plot 1?
• Is there any difference between the gendered plot owners of rainfed plot 4?
26
Hoeing (Figure 9.2.1 and 9.2.2)
• Labour for hoeing is mainly shared between men and women, but with a slight bias towards
women.
• n:N ratio: The majority of respondents are involved in hoeing their fields; a common practice.
• There is no difference between adopters and non- and dis-adopters or between technologies
and between the irrigated and rainfed plots.
• There is a difference between the gendered owners of irrigated plot 1. A female household head
said she gets relatively more assistance from men.
• There is no difference between the gendered owners of rainfed plot 4.
Figure 9.2.1: Hoeing (water source/AWM technology).
Figure 9.2.2: Hoeing (gender).
14%
9%
10%
14%
20%
51%
53%
70%
68%
40%
30%
38%
20%
14%
40%
5%
0%
0%
5%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
63
/78
n=
87
/10
1n
=1
0/1
3n
=2
2/2
8n
=1
0/1
1
Hoeing
male male & female female children
20%
7%
11%
12%
9%
43%
0%
12%
47%
50%
67%
67%
55%
29%
67%
55%
33%
36%
22%
20%
36%
29%
33%
31%
0%
7%
0%
1%
0%
0%
0%
2%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
15
/19
n=
28
/37
n=
9/1
31
01
/14
4n
=1
1/1
5n
=7
/20
n=
9/1
5n
=5
8/1
09
OW
NER
S R
AIN
-FE
D P
LOT
4O
WN
ER
S I
RR
IGA
TE
D P
LOT
1
Hoeing
male male & female female children
27
Ploughing (Figure 9.3.1 and 9.3.2)
• Labour for ploughing is mainly provided by men and to a lesser degree by both men and women
together. Ploughing is hardly ever done by women only (3 cases).
• n:N ratio: The minority of respondents are involved in ploughing, but ploughing is much more
common in rainfed fields than in irrigated fields as irrigated fields are often small enough to be
worked by hoe.
• Among non- and dis-adopters, ploughing is done mainly by men, while among adopters there is
more variation, but n:N values are low. There is a strong similarity in the labour pattern of
bucket watering among adopters and the non- and dis-adopters, possibly indicating that the
users of the most common AWM technology work in the same way on their irrigated fields as on
their rainfed fields. Bucket users do not need any specific irrigation skills or large investments.
The pattern is similar for other farm operations below (sowing, disease and pest control,
supervising paid labour and harvesting).
• On his plot, the husband gets help from women in 40% of the cases, while on the wife’s plot all
the ploughing is done by men.
Figure 9.3.1: Ploughing (water source/AWM technology).
Figure 9.3.2: Ploughing (gender).
78%
72%
100%
50%
67%
13%
14%
0%
50%
33%
3%
7%
0%
0%
0%
6%
7%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
32
/78
n=
29
/10
1n
=5
/13
n=
2/2
8n
=3
/11
Ploughingmale male & female female children
71%
63%
100%
33%
100%
71%
100%
71%
14%
25%
0%
40%
0%
29%
0%
14%
0%
13%
0%
13%
0%
0%
0%
0%
14%
0%
0%
13%
0%
0%
0%
14%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
7/1
9n
=8
/37
n=
5/1
31
5/1
44
n=
5/1
5n
=7
/20
n=
5/1
5n
=7
/10
9
OW
NE
RS
RA
IN-F
ED
PLO
T 4
OW
NE
RS
IR
RIG
AT
ED
PLO
T 1
Ploughing
male male & female female children
28
Irrigation (Figure 9.4.1 and 9.4.2)
• Labour for irrigation is mainly provided by men and women together. For motor pump adopters,
labour is mostly provided by men as most pumps are owned by men.
• n:N ratio: The majority of AWM technology adopters provide labour for irrigation. The low
occurrence of irrigation (3 of the 11 dambos adopters) shows that crops benefit from the natural
water table, without further water conservation or drainage measures.
• When irrigation is done by motor pumps, this task is exclusively done by men (who usually own
the pump).
• On irrigated plots owned by wives, most of the irrigation is jointly done by men and women and
the wives are often assisted by children.
• Among the owners of rainfed plots, female household heads are often assisted by children on
their irrigated plots.
Figure 9.4.1: Irrigation (water source/AWM technology).
Figure 9.4.2: Irrigation (gender).
0%
16%
54%
17%
33%
0%
51%
31%
67%
33%
0%
31%
8%
8%
33%
0%
2%
8%
8%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
0/7
8n
=8
1/1
01
n=
13
/13
n=
24
/28
n=
3/1
1
Irrigationmale male & female female children
0%
25%
50%
32%
22%
17%
0%
17%
100%
38%
50%
53%
56%
33%
57%
53%
0%
13%
0%
16%
22%
50%
14%
25%
0%
25%
0%
0%
0%
0%
29%
5%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
2/1
9n
=8
/37
n=
2/1
31
9/1
44
n=
9/1
5n
=6
/20
n7
/15
n=
59
/10
9
OW
NE
RS
RA
IN-F
ED
PLO
T 4
OW
NE
RS
IR
RIG
AT
ED
PLO
T 1
Irrigation
male male & female female children
29
Sowing (Figure 9.5.1 and 9.5.2)
• Labour for sowing is mainly provided by women and secondly by women and men together.
• n:N ratio: The majority of the respondents do sowing, but only 8 of 20 female household heads
do sowing on their irrigated plots. This may be due to the use of particular vegetables such as
sweet potato leaves whereby only cuttings are planted.
• Adopters and non- and dis-adopters: There is a strong similarity in the labour pattern of buckets
and watering can adopters and the non- and dis-adopters.
• Sowing on plots of motor pump adopters is mainly done by men.
• Female household heads do most of the sowing on their irrigated and rainfed plots, seldom
assisted by men (either jointly or separately).
Figure 9.5.1: Sowing (water source/AWM technology).
Figure 9.5.2: Sowing (gender).
14%
8%
50%
9%
25%
26%
27%
17%
50%
38%
58%
65%
33%
36%
38%
2%
0%
0%
5%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
65
/78
n=
86
/10
1n
=1
2/1
3n
=2
2/2
8n
=8
/11
Sowingmale male & female female children
18%
11%
8%
13%
10%
13%
0%
17%
35%
22%
50%
38%
50%
0%
33%
27%
47%
63%
33%
50%
40%
88%
67%
54%
0%
4%
8%
0%
0%
0%
0%
2%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
17
/19
n=
27
/37
n=
12
/13
11
2/1
44
n=
10
/15
n=
8/2
0n
=9
/15
n=
59
/10
9
OW
NE
RS
RA
IN-F
ED
PLO
T 4
OW
NE
RS
IR
RIG
AT
ED
PLO
T 1
Sowing
male male & female female children
30
Weeding (Figure 9.6.1 and 9.6.2)
• Labour for weeding is mainly provided as a joint venture between men and women.
• n:N ratio: Weeding is a common practice both among adopters and non- and dis-adopters.
• Where only a few men do the weeding themselves in rainfed plots, this proportion increases for
irrigated fields. Weeding on fields irrigated by pumps is a quarter of the time done by men only.
There are no clear differences between owners of irrigated plots and owners of rainfed plots.
Figure 9.6.1: Weeding (water source/AWM technology).
Figure 9.6.2: Weeding (gender).
6%
11%
27%
13%
18%
56%
62%
73%
78%
45%
32%
27%
0%
4%
36%
5%
0%
0%
4%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
62
/78
n=
79
/10
1n
=1
1/1
3n
=2
3/2
8n
=1
1/1
1
Weeding
male male & female female children
7%
18%
0%
10%
0%
13%
13%
12%
79%
46%
73%
68%
73%
63%
50%
68%
14%
29%
18%
21%
27%
25%
38%
18%
0%
7%
9%
1%
0%
0%
0%
2%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
14
/19
n=
28
/37
n=
11
/13
10
5/1
44
n=
11
/15
n=
8/2
0n
=8
/15
n=
57
/10
9
OW
NE
RS
RA
IN-F
ED
PLO
T 4
OW
NE
RS
IR
RIG
AT
ED
PLO
T 1
Weeding
male male & female female children
31
Disease and pest control (Figure 9.7.1 and 9.7.2)
• Labour for disease and pest control is mainly provided by men, except for wife-owned rainfed
plots where it is done as a joint venture or by the wife alone (the latter case has a low
frequency).
• n:N ratio: A small number of respondents do disease and pest control. It is not a common
practice.
• Adopters and non- and dis-adopters: Among non- and dis-adopters there is more division of
labour. In about half the cases it is done by men only and half jointly with women or by women
only.
• For adopters of buckets and watering cans, the situation is similar to non- and dis-adopters as
regards sharing responsibilities with women. For the other more specialised technologies the
men do most of the disease and pest control.
Figure 9.7.1: Disease and pest control (water source/AWM technology).
Figure 9.7.2: Disease and pest control (gender).
55%
67%
100%
80%
100%
9%
14%
0%
20%
0%
27%
16%
0%
0%
0%
9%
4%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
11
/78
n=
57
/10
1n
=9
/13
n=
5/2
8n
=4
/11
Disease & Pest Controlmale male & female female children
100%
80%
0%
74%
86%
60%
75%
82%
0%
20%
50%
21%
14%
0%
0%
12%
0%
0%
50%
5%
0%
40%
25%
3%
0%
0%
0%
0%
0%
0%
0%
3%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
2/1
9n
=5
/37
n=
2/1
31
9/1
44
n=
7/1
5n
=5
/20
n=
4/1
5n
=3
4/1
09
OW
NE
RS
RA
IN-F
ED
PLO
T 4
OW
NE
RS
IR
RIG
AT
ED
PLO
T 1
Disease & Pest Control
male male & female female children
32
Supervising paid labour (Figure 9.8.1 and 9.8.2)
• Supervision of paid labour is mainly done by men, but among non- and dis-adopters and
among owners of rainfed plots it is done by women in up to 40% of the cases, or
responsibilities are shared. Although numbers are small, it seems that men take more
responsibility for labour supervision on irrigated fields.
• n:N ratio: Supervision of paid labour is done by only a few of the respondents. There is not
much paid labour on small farms.
Figure 9.8.1: Supervising paid labour.
Figure 9.8.2: Supervising paid labour.
54%
59%
75%
67%
100%
0%
12%
25%
33%
0%
38%
29%
0%
0%
0%
8%
0%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
13
/78
n=
17
/10
1n
=4
/13
n=
3/2
8n
=1
/11
Supervising Paid Labourmale male & female female children
100%
20%
33%
64%
100%
0%
100%
64%
0%
20%
33%
14%
0%
0%
0%
18%
0%
40%
33%
21%
0%
0%
0%
18%
0%
20%
0%
0%
0%
0%
0%
0%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
4/1
9n
=5
/37
n=
3/1
32
8/1
44
n=
3/1
5n
=0
/20
n=
2/1
5n
=1
1/1
09
OW
NE
RS
RA
IN-F
ED
PLO
T 4
OW
NE
RS
IR
RIG
AT
ED
PLO
T 1
Supervising Paid Labour
male male & female female children
33
Harvesting (Figure 9.9.1, 9.9.2)
• Labour for harvesting is mainly a joint venture between men and women. If harvesting is done
by men and women on their own, it is more often done by women than by men.
• There are no major differences in labour patterns between adopters and non- and dis-adopters,
between technologies and between owners of irrigated and rainfed plots.
Figure 9.9.1: Harvesting (water source/AWM technology).
Figure 9.9.2: Havesting (gender).
8%
8%
17%
12%
18%
62%
64%
75%
77%
36%
29%
28%
0%
8%
45%
1%
0%
8%
4%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
73
/78
n=
96
/10
1n
=1
2/1
3n
=2
6/2
8n
=1
1/1
1
Harvesting
male male & female female children
7%
7%
8%
7%
0%
11%
0%
10%
79%
57%
67%
74%
73%
78%
44%
68%
14%
30%
17%
19%
27%
11%
44%
21%
0%
7%
8%
0%
0%
0%
11%
1%
Others
Female HH Head
Wife
Husband
Others
Female HH Head
Wife
Husband
n=
14
/19
n=
30
/37
n=
12
/13
12
1/1
44
n=
11
/15
n=
9/2
0n
=9
/15
n=
68
/10
9
OW
NER
S R
AIN
-FED
PLO
T 4
OW
NE
RS
IR
RIG
ATE
D P
LOT
1
Harvesting
male male & female female children
34
Plot size in relation to adoption status
Irrigated fields are 3 to 4 times smaller than rainfed plots (Figure 9.10). The rainfed plots of adopters
are larger than the rainfed plots of non- and dis-adopters. The average plot size of an adopter is 1.47
ha (0.3 ha irrigated plus 1.17 ha rainfed) and 0.87 ha for a non- and dis-adopter.
Figure 9.10: Average plot size in ha for adopters and non- and dis-adopters.
Gross yield from sales in relation to adoption status
The money earned from irrigated plots is much higher than from rainfed plots. Small-scale farmers
grow mainly cash crops (mostly vegetables) on irrigated fields and food crops as well as cash crops
(vegetables and crops like cotton and sunflower) on rainfed fields. The yields of adopters on rainfed
plots are generally higher than the yields of non- and dis-adopters on rainfed plots, except for plot 4
(Figure 9.11 and Table 9.2).
Figure 9.11: Average gross yield in kw/ha from harvests sold on plots of adopters and non- and dis-
adopters.
0.06
0.15
0.66
0.07
0.25
0.85
0.02
0.07
0.21
Plot 6
Plot 5
Plot 4
Plot 3
Plot 2
Plot 1
RA
IN-F
ED
IRR
IGA
TE
D
Average Plot Size in Hectares for Adopters
and Non-/Dis-adopters
Adopters Non-/Dis-adopters
702,783
87,433
589,336
1,692,943
787,556
496,006
2,441,350
4,148,157
4,728,205
Plot 6
Plot 5
Plot 4
Plot 3
Plot 2
Plot 1
RA
IN-F
ED
IRR
IGA
TE
D
US$ 200 400 600 800
Average Gross Yield in Kw/Ha from Harvests Sold
on plots of Adopters and Non-/Dis-adopters
Adopters Non-/Dis-adopters
35
Table 9.3: Gross yields from sales from irrigated and rainfed plots.
Gross yield from harvest sold in Kwacha/Hectare
Irrigated Plots Rainfed Plots Ranked
1 2 3 4 5 6 Total
Irrigated only
1 Cabbage 4,325,000 1,140,000 - - - 5,465,000
2 Onion 875,000 576,923 851,863 - - - 2,303,786
3 Green maize 300,369 694,444 328,947 - - 1,323,761
4 Sugar cane 230,769 - - - 230,769
Others 5,977,273 - - - - - 5,977,273
Rainfed only
1 Rainfed maize - - - 512,796 1,493,478 2,006,274
2 Cotton - - - 223,750 1,451,613 1,675.363
3 Millet - - - - 156,410 204,211 360,621
4 Sunflower - - - - 62,500 119,355 181,855
5 Cassava - - - 41,128 138,889 180,017
Both irrigated
and rainfed
1 Tomatoes 8,239,768 9,440,226 2,693,966 2,211,538 9,097,221 31,682,720
2 Okra 3,969,644 7,056,000 486,842 - 1,644,899 8,000,000 21,157,384
3 Sweet potatoes 5,000,000 10,000,000 - - 122,530 1,938.922 17,061,452
4 Mixed beans 10,000,000 644,372 - 1,141,813 1,459,597 13,246,147
5 Leafy vegetables 2,372,780 2,967,612 - - - 2,650,000 7,990,392
6 Groundnuts - 633,333 372,414 83,065 124,545 1,213,358
36
10. Financing issues for irrigated and rainfed plots
Inputs for men’s irrigated and rainfed plots are almost exclusively financed by men. The inputs for
women’s irrigated and rainfed plots are shared between husband and wife, or financed by the
female household head. The husband is still the largest financier on all these women’s plots (Figure
10.1 and 10.2).
Figure 10.1: Men’s plots: source of financing for all inputs.
Figure 10.2: Women’s plots: source of financing on all inputs.
The majority of irrigated and rainfed plot owners said they encountered problems with financing
inputs for their plots. Wife-owners and female household head owners had fewer problems in their
rainfed plots than in their irrigated plots. This could be due to more expensive inputs for irrigation
(Figure 10.3).
83%
83%
4%
3%
9%
8%
4%
6%
Rain-fed Plot 4
Irrigated Plot 1
n=
16
1n
=1
16
ME
N'S
P
LOT
S
Source of Financing for all Inputs on Men's Plots
Husband Wife Female HH head other
50%
62%
16%
18%
29%
14%
5%
6%
Rain-fed Plot 4
Irrigated Plot 1
n=
92
n=
50
WO
ME
N'S
P
LOT
S
Source of Financing for all Inputs on Women's Plots
husband wife Female HH head other
37
Figure 10.3: Percentage of plot owners encountering problems with financing inputs.
By far the most common problem (more than 60% of all respondents), is the cost of inputs. Few see
availability and quality as a problem. There is no clear difference between irrigated and rainfed plots
in terms of financing problem (Figure 10.4).
igure 10.4: Specific problems encountered by plot owners in financing inputs.
0% 10% 20% 30% 40% 50% 60% 70% 80%
Rain-fed Plot 4
Irrigated Plot 1
Percentage of Plot Owners that encountered
Problems with Financing of Inputs
Husband owner Wife owner
Female HH head owner other owner
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
other
female HH head
wife
husband
other
female HH head
wife
husband
n=
13
n=
19
n=
5n
=8
7n
=7
n=
6n
=7
n=
58
OW
NE
RS
RA
IN-F
ED
PLO
T 4
OW
NE
RS
IR
RIG
AT
ED
PLO
T 1
Specific Problems encountered by Plot
Owners in Financing Inputs
expensive not available poor quality others
38
11. Marketing issues with irrigated and rainfed plots
In Chibombo, marketing crops grown on irrigated plots is more often seen as a problem than in
other districts, despite the fact that the survey area in Chibombo District (Katuba) is only 20 km from
Lusaka. The problem may be the cumbersome and highly competitive procedures at the main
wholesale market in Lusaka, the Soweto Market (Figure 11.1 and 11.2).
Figure 11.1: Irrigated plot 1 owners: percentage of encountering marketing problems.
Figure 11.2: Rainfed plot 4 owner: percentage of encountering marketing problems.
Marketing is less often a problem than financing inputs (Figure 11.3. and 11.4), but still between 25%
and 50% of plot owners see it as a problem. Owners of rainfed plots see it as a problem more often
than owners of irrigated plots, possibly because of the channels for rainfed crops are less established
and possibly more centralised than for irrigated crops. Wives and female household heads have
fewer marketing problems on their irrigated plots than husbands do on their irrigated plots.
Figure 11.3: Irrigated plot 1 owners: percentage of encountering marketing problem.
0% 10% 20% 30% 40% 50% 60%
Sinazongwe
Monze
Chibombo
Mpika
n=
9/2
6n
=7
/27
n=
22
/38
n=
16
/35
Percentage of Irrigated Plot 1 Owners in the
Districts that encounter Problems with Marketing
0% 10% 20% 30% 40% 50% 60%
Sinazongwe
Monze
Chibombo
Mpika
n=
4/7
n=
13
/27
n=
7/1
5n
=1
9/4
5
Percentage of Rain-fed Plot 4 Owners in the
Districts that encounter Problems with Marketing
0% 10% 20% 30% 40% 50%
other owner
Female HH head owner
Wife owner
Husband owner
n=
3/1
2n
=4
/13
n=
5/1
3n
=4
2/8
9
Percentage of Irrigated Plot 1 Owners that
encountered Problems with Marketing
39
Figure 11.4: Rainfed plot 4 owners: percentage of encountering marketing problems.
The most common problems experienced by plot owners are the low prices for produce and high
transport costs (Figure 11.5). The exception is Sinazongwe (the public irrigation scheme) where the
main marketing problems mentioned by owners of irrigated plots are flooded markets and too many
middle-men. Although too many middle-men are seen as a problem, competition between them
could possibly favor the farmer. For example, “crooked briefcase business men” or fake buyers who
buy on credit but never return to pay. Sinazongwe is in a remote rural area, with low population
densities as compared to the other districts which are close to main roads.
Figure 11.5: Marketing problems experience by plot owners.
Wives and female household heads who are owners of irrigated plots have specific marketing
problems, among these low prices and high transport costs, which are more common for them than
for the other type of owners (Figure 11.6).
• 40% of wife-owners see flooded markets and too many middle-men as problems, while 50% of
female household head owners see crooked briefcase business men, bad roads and distance to
markets as specific problems. The general impression is that women mention more and different
problems in marketing than men. For owners of rainfed plots, the main problem is low prices for
produce.
0% 10% 20% 30% 40% 50%
other owner
Female HH head owner
Wife owner
Husband owner
n=
2/6
n=
8/1
6n
=4
/8n
=2
9/6
4
Percentage of Rain-fed Plot 4 Owners that
encountered Problems with Marketing
0% 20% 40% 60% 80% 100% 120%
Sinanzongwe
Monze
Chibombo
Mpika
Sinazongwe
Monze
Chibombo
Mpika
n=
4/4
0n
=1
3/1
29
n=
7/7
0n
=2
5/1
90
n=
22
/81
n=
12
/63
n=
47
/19
8n
=2
8/1
35
RA
IN-F
ED
PLO
T 4
IRR
IGA
TE
D P
LOT 1
Specific Marketing Problems
experienced by Plot Owners in Districts
Low Prices for Produce High Transport costs
Flooded Markets Too many middle men
Crooked Briefcase business men Bad roads to markets
Regional markets too far No Local Markets
Gov/companies take long to pay Others
40
Figure 11.6: Specific marketing problems experienced by gendered plot owners.
12. Changes in the households due to AWM technology adoption
This section compares the situation in adopter households before and after adoption. Observations
on food security in adopter households (Figure 12.1) include:
• 20% of households said that buckets and dambos/wetlands had not improved their food
security, while this was less than 10% for adopters of other technologies.
• Food security increased in the majority of households (60% to 90% of households).
• The most important technologies contributing to food security are:
o Motor pumps: 92% of households.
o Conservation agriculture and communal canals: 75% of households.
o Dambos, wetlands and buckets: 64% to 67% of households.
Figure 12.1: How household food security changed after AWM technology adoption.
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Other
Female HH Head
Wife
Husband
Other
Female HH Head
Wife
Husband
n=
2/2
3n
=9
/10
9n
=5
/49
n=
33
/40
4n
=5
/27
n=
10
/36
n=
9/4
5n
=8
5/3
69
OW
NE
RS R
AIN
-FED
PLO
T 4
OW
NE
RS
IRR
IGA
TED
PLO
T 1
Specific Marketing Problems
experienced by Gendered Plot Owners
Low Prices for Produce High Transport costs
Flooded Markets Too many middle men
Crooked Briefcase business men Bad roads to markets
Regional markets too far No Local Markets
Gov/companies take long to pay Others
48%
69%
75%
64%
50%
19%
23%
25%
11%
7%
9%
25%
11%
9%
21%
8%
4%
18%
1%
4%
n=100
n=13
n=28
n=11
n=4
Bu
cke
ts
Mo
tor
Pu
mp
s
Co
mm
un
al
Ca
na
l
Da
mb
o/
We
tla
nd
Co
nse
r-
va
tio
n
Ag
ricu
ltu
re
Valid n = 156 CHANGES DUE TO ADOPTION OF AWM TECHNOLOGIES
Missing n = 84
Total n = 240
THE
MO
ST IM
PO
RT
AN
T A
WM
TE
CH
NO
LOG
IES
How HH food security changed after
AWM Technology Adoption
Adoption of technology increased food security
Adoption of technology increased food security and income
Adoption of technology increased food production
Adoption of technology supplemented the rainfed production
Food security remained the same
Other
41
Change in household income after adoption of specific AWM technologies (Figure 12.2 and 12.3)
• 19% of households said that buckets had not improved their household income, while this was
less than 10% for the other technologies.
• Income changed in 80% to 95% of the adopter households.
Figure 12.2: How household income changed after AWM technology adoption.
Change in food security and income in adopter FHHs and MHHs (Figure 12.4 and 12.5)
• In 25% of the adopter FHHs, food security did not change while this was only 14% in MHHs.
• In 19% of the adopter FHHs, income from sales did not change while this was only 13% in MHHs.
Figure 12.3: How household food security, income and food production changed in FHHs and MHHs
after AWM technology adoption.
30%
46%
46%
27%
25%
50%
46%
50%
64%
75%
19%
8%
4%
9%
1%n=100
n=13
n=28
n=11
n=4
Bu
cke
t
Mo
tor
Pu
mp
Co
mm
un
al
Ca
na
l
Da
mb
o/
We
tla
nd
Co
nse
r-
va
tio
n
Ag
ricu
ltu
re
Valid n = 156 CHANGES IN HH INCOME AFTER ADOPTION
Missing n = 84
Total n = 240
THE
MO
ST
IMP
OR
TA
NT
AW
M T
EC
HN
OLO
GIE
S
How Household Income changed after
AWM Technology Adoption
HH Income improved considerably
HH Income improved, but only a bit
No Change
Reduced
55%
56%
16%
15%
14%
26%
11%
4%
4%n=134
n=27
MH
HF
HH
Valid n = 161 CHANGES DUE TO ADOPTION OF AWM TECHNOLOGIES
Missing n = 79
Total n = 240
How HH food security, income and food production changed
in FHHs & MHHs after AWM Technology Adoption
Adoption of technology increased food security
Adoption of technology increased food security & income
Food security remained the same
Adoption of technology increased food production
Other
42
Figure 12.4: How household income changed in the opinion of FHHs and MHHs after AWM
technology adoption.
Observations on Food Security and Income from sales in adopter households (Figure 12.5 and 12.6)
• Less than 20% of the households said that food security had not changed after adoption; food
security and food production changed in about 80% of the households in the 4 districts.
• 80 to 90% of the adopter households consider that income from sales has considerably
improved or improved a little.
Figure 12.5: Changes due to adoption: How household food security changed in 4 districts after
AWM technology adoption.
Figure 12.6: Changes in household income: How household income changed after AWM technology
adoption.
33%
44%
54%
37%
13%
19%
1%n=134
n=27
MH
HF
HH
Valid n = 161 CHANGES IN HH INCOME AFTER ADOPTION
Missing n = 79
Total n = 240
How HH Income changed in the opinion of FHHs &
MHHs after AWM Technology Adoption
HH Income improved considerably
HH Income improved, but only a bit
No Change
Reduced
56%
44%
51%
67%
10%
26%
27%
10%
10%
2%
17%
21%
21%
17%
7%
3%
2%
9%
n=39
n=39
n=41
n=42
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
Valid n = 161 CHANGES DUE TO ADOPTION OF AWM TECHNOLOGIES
Missing n = 79
Total n = 240
How HH food security changed in the 4 Districts after
AWM Technology Adoption
Adoption of technology increased food security
Adoption of technology increased food security & income
Adoption of technology increased food production
Food security remained the same
others
15%
33%
46%
43%
72%
46%
39%
48%
13%
21%
15%
7% 2%
n=39
n=41
n=41
n=42
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
Valid n = 163 CHANGES IN HH INCOME AFTER ADOPTION
Missing n = 77
Total n = 240
How HH Income changed in the 4 Districts after
AWM Technology Adoption
HH Income improved considerably
HH Income improved, but only a bit
No Change
Reduced
43
13. Changes after AWM technology adoption in the households of
married adopters
Change in collaboration between spouses after AWM adoption (Figure 13.1)
• Only in Mpika was there a change in collaboration between spouses in 53% of the households.
• In other districts there was hardly a change in collaboration (only 3% to 13% of the households).
Figure 13.1: Collaboration between spouses after AWM technology adoption.
Change in decision making on outputs and income between spouses after AWM adoption (Figure
13.2)
• Only in Mpika was there a considerable change in decision making (42% of households).
• In other districts there was hardly any change in decision making (6% to13%).
Figure 13.2: Decision making on outputs and income between spouses after AWM technology
adoption.
13%
3%
9%
53%
87%
97%
91%
47%
n=31
n=33
n=32
n=34
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
Valid n = 130
Missing n = 110
Total n = 240
Nature of collaboration between spouses
after AWM Technology Adoption
collaboration between spouses is
DIFFERENT after AWM adoptioncollaboration between spouses is NOT
DIFFERENT after AWM adoption
9%
6%
13%
42%
91%
94%
88%
58%
n=32
n=33
n=32
n=36
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
Valid n = 133 NATURE OF DECISION MAKING
Missing n = 107
Total n = 240
Nature of decision making on Outputs and Income
between spouses after AWM adoption
Decision making on output and income is DIFFERENT
after AWM adoption
Decision making on output and income is NOT
DIFFERENT after AWM adoption
44
14. Changes related to years after adoption
The majority of respondents said there has been an increase in food security since adoption of an
AWM technology. The minority said there has been an increase in household income and about half
said there has been only a slight change in income. Increased food security is seen as an impact of
AWM technology adoption rather than household income.9 There is no clear difference in impact
between younger and older adopters (Figure 14.1 and 14.2).
Figure 14.1: Change in food security in the years after AWM technology adoption.
Figure 14.2: Change in household income in the years after AWM technology adoption.
9 The figures present information for adopters of 10 years ago; information for older adopters was collected
but frequencies were too low for a meaningful analysis.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 2 3 4 5 6 7 8 9 10
n=13 n=26 n=13 n=8 n=10 n=12 n=5 n=5 n=5 n=16
Number of years after adoption (1 - 10 years) and
number of adopters (n) for each year
Change in Food Security in the years
after AWM Technology Adoption
food security increased
food security & income increased
Food security remained the same
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1 2 3 4 5 6 7 8 9 10
n=15 n=29 n=15 n=11 n=10 n=13 n=6 n=4 n=5 n=17
Number of years after adoption (1 - 10 years) and
number of adopters (n) for each year
Change in HH Income in the years
after AWM Technology Adoption
Income improved considerably
Income improved, but only a bit
No change in Income
45
15. Obstacles for future irrigation expansion
Problems in getting suitable land for irrigation for future expansion (Figure 15.1 and 15.2)
• On average, 79% of FHHs said that land acquisition is no problem or if it is it can be resolved,
while this percentage is 76% for MHHs.
• There are a major difference between districts in terms of land acquisition. In Mpika and
Chibombo, there is no problem, or resolvable problems, in 90% to 100% of the households,
while these percentages are 65% to 75% in Monze and 50% in Sinazongwe.
• FHHs in Monze have more problems (38%) in land acquisition than MHHs (25%), while in
Chibombo and Mpika, FHHs have fewer problems (0%) than MHHs (5% to 11%).
• In Sinazongwe, the same number of FHHs and MHHs (50%) have problems getting suitable
land for irrigation.
Figure 15.1: Problems in getting suitable land for irritation with sufficient tenure for expansion by
gender of household head.
Figure 15.2: Problems in getting suitable land for irrigation with sufficient tenure security for
expansion by district and gender of household head.
Availability of inputs for expansion of irrigation (Figure 15.3 and 15.4)
• The majority of households consider availability of inputs a problem for future expansion of
irrigation; more FHHs see it as a problem (74%) than MHHs (58%).
• There are major differences between the districts. In Chibombo, 50% of households see inputs
as a problem, but in Mpika and Sinazongwe inputs are seen as a problem by 60% to 80% of the
households. In Monze the figure is between 60% (MHHs) and 100% (FHHs).
61%
68%
15%
11%
24%
21%
n=128
n=28
MH
HF
HH
valid n = 156 Do you have problems in getting suitable land for irrigation?
missing n = 84
total n = 240
Problems in getting suitable land for irrigation with sufficient
tenure security for expansion, by Gender of HH Head
This is no problem for me
I encounter this problem but can cope with it
This problem applies strongly to my situation
21%
33%
61%
50%
81%
89%
91%
100%
29%
17%
14%
13%
8%
11%
5%
50%
50%
25%
38%
11%
5%
n=34
n=6
n=36
n=8
n=36
n=9
n=22
n=5
MH
HF
HH
MH
HF
HH
MH
HFH
HM
HH
FH
H
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
valid n = 156 Do you have problems in getting suitable land for irrigation?
missing n = 84
total n = 240
Problems in getting suitable land for irrigation with
sufficient tenure security for expansion,
by District and by Gender of HH Head
This is no problem for me
I encounter this problem but can cope with it
This problem applies strongly to my situation
46
Figure 15.3: Availability of inputs for irrigation by gender of household head.
Figure 15.4: Availability of inputs for irritation by district and gender of household head.
24%
16%
18%
10%
58%
74%
n=148
n=31
MH
HF
HH
Valid n = 179
Missing n = 61
Total n = 240
Availability of Inputs for Irrigation by
Gender of HH head
This is no problem for me
I encounter this problem but can cope with it
This problem applies strongly to my situation
23%
25%
6%
38%
30%
31%
18%
33%
8%
20%
11%
20%
60%
75%
61%
100%
54%
50%
57%
80%
n=40
n=8
n=36
n=8
n=37
n=10
n=35
n=5
MH
HF
HH
MH
HF
HH
MH
HFH
HM
HH
FH
H
Sin
azo
ng
we
Mo
nze
Ch
ibo
mb
oM
pik
a
Valid n = 179
Missing n = 61
Total n = 240
Availability of Inputs for Irrigation by District and
Gender of HH head
This is no problem for me
I encounter this problem but can cope with it
This problem applies strongly to my situation
47
ANNEX 1: Additional Figures on AWM Technology and Farm
Operations Note: These are in addition to the Figures in section 9.
Figure A.1: Tree cutting.
Figure A.2: Hiring draught power.
Figure A.3: Using improved seeds.
54%
48%
0%
75%
0%
19%
35%
100%
25%
33%
23%
13%
0%
0%
67%
4%
4%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
26
/78
n=
23
/10
1n
=1
/13
n=
4/2
8n
=3
/11
Valid n = 57
Missing n = 174
Total n = 231
Tree Cutting
mostly/excl male equally male & female
mostly/excl female mostly/excl children
62%
81%
100%
100%
100%
23%
10%
0%
0%
0%
12%
10%
0%
0%
0%
4%
0%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
26
/78
n=
21
/10
1n
=2
/13
n=
4/2
8n
=1
/11
Valid n = 54
Missing n = 177
Total n = 231
Hiring Draught Power
mostly/excl male equally male & female
mostly/excl female mostly/excl children
20%
34%
83%
38%
67%
33%
46%
0%
25%
0%
47%
20%
17%
38%
33%
0%
0%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
30
/78
n=
35
/10
1n
=6
/13
n=
8/2
8n
=3
/11
Valid n = 82
Missing n = 149
Total n = 231
Using Improved Seed
mostly/excl male equally male & female
mostly/excl female mostly/excl children
48
Figure A.4: Fertilizer application.
Figure A.5: Transplanting.
Figure A.6: Use of herbicides.
14%
20%
60%
16%
20%
51%
48%
40%
79%
60%
34%
30%
0%
0%
20%
0%
2%
0%
5%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlandsn
=3
5/7
8n
=5
6/1
01
n=
10
/13
n=
19
/28
n=
5/1
1
Valid n = 125
Missing n = 106
Total n = 231
Fertilizer Application
mostly/excl male equally male & female
mostly/excl female mostly/excl children
0%
18%
27%
50%
0%
0%
42%
64%
50%
100%
0%
40%
0%
0%
0%
0%
0%
9%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
0/7
8n
=5
5/1
01
n=
11
/13
n=
2/2
8n
=3
/11
Valid n = 71
Missing n = 160
Total n = 231
Transplanting
mostly/excl male equally male & female
mostly/excl female mostly/excl children
0%
27%
100%
40%
0%
50%
45%
0%
40%
50%
50%
27%
0%
20%
50%
0%
0%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
2/7
8n
=1
1/1
01
n=
2/1
3n
=5
/28
n=
2/1
1
Valid n = 82
Missing n = 149
Total n = 231
Use of Herbicides
male male & female female children
49
Figure A.7: Hiring paid labour.
Figure A.8: Transporting harvest.
100%
77%
100%
60%
100%
0%
8%
0%
40%
0%
0%
15%
0%
0%
0%
0%
0%
0%
0%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
4/7
8n
=1
3/1
01
n=
4/1
3n
=5
/28
n=
1/1
1
Valid n = 27
Missing n = 204
Total n = 231
Hiring Paid Labourmostly/excl male equally male & female
mostly/excl female mostly/excl children
14%
18%
33%
16%
22%
55%
59%
56%
68%
44%
30%
23%
11%
8%
33%
2%
0%
0%
8%
0%
NON / DIS-ADOPTERS
bucket / watering can
diesel / petrol pump
canal / river diversion
dambo / wetlands
n=
66
/78
n=
88
/10
1n
=9
/13
n=
25
/28
n=
9/1
1
Valid n = 197
Missing n = 34
Total n = 231
Transporting Harvest
mostly/excl male equally male & female
mostly/excl female mostly/excl children
