FutureWater Evaluation
ThirdEye Project in Mozambique
SECURING WATER FOR FOOD
NOVEMBER 2018
Prepared By: Alice Kasznar Feghali
Masters student in Environmental Studies and Sustainability Science (LUMES) at Lund University 
Center for Sustainability Studies (LUCSUS) 
The Kaizen Company | Contract #: AID-OAA-C-15-00011 
www.securingwaterforfood.org | securingwaterforfood@gmail.com
TABLE OF CONTENTS
I. INTRODUCTION 2
II. BACKGROUND 3
1. Gender 4
2. Farm size 5
3. Farmers’ experience 5
4. Other occupations or sources of income 5
III. METHODOLOGY 4
1. Sample selection 4
2. Scope of survey and service reach 5
3. Other methodological considerations 5
IV. RESULTS 11
1. Types of information received by farmers from innovation 17
2. Water usage and benefits 24
3. Crop benefits 30
4. Farmers’ incomes and income benefits 33
5. Poverty reduction benefits 35
6. Adherence to service 37
7. Gender differences in benefits 38
8. Regional differences 43
V. DISCUSSION 38
1. Crop and water benefits 46
2. Usage/availability 50
3. Innovation affected farm size and general benefits 52
4. Changes in income 53
5. Impact on poverty 54
6. Gender differences 54
7. Affordability of the innovation 55
8. Benefits for Leaders of Farmers’ Association 55
VI. CONCLUSION 44
VII. REFERENCES 44
2 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
FutureWater’s ThirdEye was a SWFF-supported infrared flying sensors project that created a group 
of flying sensors operators equipped with tools to analyze near infrared imagery in order to help 
farmers to make better decisions concerning the use of their limited resources, such as water, seeds 
and fertilizers. This report analyses the results obtained by the monitoring and evaluation field intern 
who conducted an evaluation survey in July and August 2018 in Mozambique, after the project had 
been active there for 3 years.
A sample of 62 predominantly female smallholder farmers were interviewed out of an estimated total 
of 2,891 farmers located in the areas where the project was carried out: surroundings of the towns of 
Xai-Xai and Chokwé, in Gaza province. Farmers were randomly selected through visits to their farms 
and data was obtained on household income, crop yields, water practices and expenses. Even though 
it was not possible to quantify changes in water usage, the innovation is seen as having a positive 
indirect impact over water efficiency in some areas by serving as encouragement for farmers to clean 
water channels or by providing the necessary justification to have fields leveled.
Even though 59% of farmers increased their yields over the period examined, other factors besides 
the innovation were identified by farmers as also having an impact over production, explaining 
why farmers’ attitudes towards the innovation varied: 77% of farmers felt that the innovation was 
beneficial, even if indirectly, but 34%of the farmers felt either unsure or not interested in having the 
service continue.
ABSTRACT
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 3
In Sub-Saharan Africa, where most of the population depends on subsistence farming and have 
low access to agricultural inputs, decisions concerning resources (such as seeds, water, fertilizers, 
pesticides, etc.) become challenges that can directly impact on food security and nutrition. In 
Mozambique, agriculture is the main economic activity, being carried out by small-scale farmers that 
are responsible for 95% of the country’s agricultural production (FAO, 2018). Most of Mozambican 
farmers practice subsistence agriculture and suffer from extreme weather events, such as floods 
and droughts (USAID, 2018). 
ThirdEye thus intends to increase efficiency in food production by providing farmers with 
FutureWater, a service that brings relevant information to farmers by setting up a network of flying 
sensors operators, which can detect crop stress two weeks before the human eye can actually see it 
(ThirdEye, n.d.). According to the innovator’s description of the service, the operators fly sensors over 
farmland, obtain and analyse imagery and then inform farmers of the current situation in their fields. 
With this information farmers would be able to improve farm management and make efficient use of 
resources and inputs by knowing where to use them in their farms (ThirdEye, n.d.). 
FutureWater (hereinafter “service” or “innovation”) has been implemented in Mozambique, in the 
surroundings of the towns of Xai-Xai, Chokwé and Moamba and also in Kenya. In Mozambique, which 
is the focus of this report, the project was carried out from 2014 to 2017, and, according to ThirdEye’s 
website (ThirdEye, n.d.), reached more than 3,500 farmers and 1,600 hectares (the number informed 
in the innovator’s last report available to the evaluator was of 2,892 “active users”). 
In July and August 2018, an impact assessment 
was carried out by a SWFF Field Evaluator, who 
interviewed 63 farmers that stated they had used 
the ThirdEye service in Mozambique. Farmers 
were randomly selected through visits to their 
farms and data was obtained on household 
income, crop yields, water practices and expenses. 
The main purpose of the assessment was to 
understand the benefits, limitations and impacts 
for farmers using ThirdEye innovation, which will 
be detailed here. 
I. INTRODUCTION
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In their reports, ThirdEye supported a total of 2,892 active ThirdEye farmers in the third year of the 
project in Mozambique receiving the service, comprising the regions of Xai-Xai, Chokwè and Moamba 
(Table 1). Interviews were conducted in-person by the Monitoring and Evaluation field intern with the 
assistance, when needed, of a translator (as detailed in the Methods section below). The evaluator 
followed a questionnaire available in the Fulcrum App, comprising approximately 45 questions. 
Answers were inputted in the mobile-based version of the Fulcrum App during the interviews, which 
were also recorded with a mobile phone app. After collected, data from the Fulcrum App was 
processed in Excel.
In this assessment, farmers in Xai-Xai and Chokwè were surveyed. In Xai-Xai farmers work in the 
Nhampondzoene Association, which is divided in blocks and sub-blocks. In the surroundings of 
Chokwè, farmers are located around dickes and channels, in different associations or individually. 
All of the locations covered by the service, as informed in ThirdEye reports provided to the evaluator, 
were visited by the interviewer, except for Moamba, where there is only one farmer using the service. 
Since this farmer is not a small scale farmer and only started using the service in 2017 he was not 
included in the survey. 
II. BACKGROUND
MAP 1. HEATMAP OF FARMERS INTERVIEWED IN THE SURROUNDINGS 
OF CHOKWÉ AND XAI-XAI, IN THE GAZA PROVINCE IN MOZAMBIQUE
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1. GENDER 
Approximately 52% of Mozambicans are women in both rural and urban areas. The percentage of 
women in the Gaza province, where the innovation was active in Mozambique, is of 54% (Instituto 
Nacional de Estatísticas, 2017). However, subsistence agriculture has become an activity mostly 
practiced by women, which means that most small-scale farmers are women (Oliveira, 2016). In this 
survey, women constitute the majority of respondents: 68% (42 out of 62) of them were women and 
32% (20 out of 62) of them were men, as illustrated in Graph 1 below.
This is also in accordance with the gender distribution previously identified by ThirdEye among the total 
number of active users of the service (71% women farmers in the third year of the project). It also relates 
to the general distribution of gender roles in the country, where most of subsistence agriculture is 
practiced by women, who not only sow and cultivate crops, but are also the ones commercializing their 
produce informally in urban centers (Oliveira, 2016).
GRAPH 1. GENDER OF INTERVIEWED FARMERS GENDER OF INTERVIEWED FARMERS 
n=62
32% Male
68% Female
PHOTO 1. Women farmers in Xai-Xai 
collecting sweet potato leaves. 
6 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
2. FARM SIZE
Most farmers in the region practice small-scale agriculture, as is clear from Graph 2 below, which 
presents range of land size owned by respondents. 73% of farms (45 out of 62) are smaller than 1 
hectare (10,000 m²), 24% of farmers (15 out of 62) have farms bigger than 1 ha and up to 5 ha, and 
only 3% (2 out of 62) of farmers own farms with area equal or greater than 5 ha. This is in line with the 
national context, where 99% of farming units are smaller than 5 hectares (Oliveira, 2016) .
The average farm size owned by interviewed farmers is of 2.79 ha and the median is 0.5 ha. However, 
one farmer out of the 62 respondents owns 72 hectares and another farmer owns 15 hectares, which 
is much above the average. Excluding these larger farmers, the average land size in the sample would 
be of 0.99 hectares per farmer. 
Women respondents own smaller farms than men: 81% of the women (34 out of 42) have farms up to 
1 ha, while only 55% of the men have farms up to 1 ha and only men own farms larger than 5 hectares, 
as shown in Graph 3 below.
GRAPH 2. RANGE OF LAND SIZE OWNED BY INTERVIEWED FARMERS RANGE OF LAND SIZE
OWNED BY INTERVIEWED FARMERS 
n=62
0
5
10
15
20
25
30
35
40
45
≤ 1 ha 1–5 ha ≥ 5 ha
45
2
15
NUMBER OF FARMERS
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GRAPH 3. SIZE OF FARMS OWNED BY PERCENTAGE OF FARMERS OF EACH GENDER 
≤ 1 ha
Males Females
0%
10%
20%
30%
40%
50%
1–5 ha ≥ 5 ha
60%
70%
80%
55%
35%
18%
10%
81%
SIZE OF FARMS OWNED BY PERCENTAGE
OF FARMERS OF EACH GENDER 
n=62
PERCENTAGE OF FARMERS PER GENDER
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The area affected by the innovation is smaller than the total area owned by farmers since some 
farmers have land in areas where the innovation is not active. Including the two larger farmers, 
the average area affected by innovation per farmer is 1.5 hectares and the median, 0.5 hectares. 
Excluding the larger farmers, the average area affected by the innovation per farmer is 0.8 hectares. 
Graph 4 below presents the data on size of innovation affected areas owned by farmers.
For the sake of understanding how the innovation impacted local farmers, yields and and information 
on crops and farming practices, as presented in the following sections, were asked only about areas 
affected by the innovation. 
It is also important to clarify that in Mozambique farmers do not own land, since all land is property 
of the state. Individuals and organisations are granted the right to use the land and this can either 
be done informally or though the issuance of an official document (Magin, 2015). For the purpose of 
this survey, “land owned” is land used by the farmer independent of how he/she has acquired it. In 
some cases farmers had either borrowed from or lent land to other people and in all these cases no 
monetary compensation was established between the parties. Use of land was compensated through 
exchange of services (keeping the land weeded, rotating the soil, borrowing tools). 
3. FARMER’S EXPERIENCE 
A relevant number of farmers (39% or 24 out of 61 respondents) were not sure when they had started 
using the service. 61% (37 out of 61 respondents) informed the year they thought they had started 
using the service, presented in Table 1 below. The high level of uncertainty among farmers may be due 
to the fact that the innovation is not a product that was acquired by the farmers, did not require a 
monthly payment or frequent maintenance, but only depended on the visit by a drone operator to the 
farm, which happened sporadically.
GRAPH 4. SIZE OF INNOVATION AFFECTED AREAS OWNED BY FARMERS 
10
20
30
40
50
SIZE OF INNOVATION AFFECTED
AREAS OWNED BY FARMERS 
n=62
0 ≤ 1 ha 1–5 ha ≥ 5 ha
45
2
15
NUMBER OF FARMERS
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TABLE 1. YEARS INDICATED BY 37 FARMERS THAT 
COULD INFORM WHEN THEY STARTED USING THE SERVICE
Year
Number of farmers 
who thought 
innovation started 
in this year 
Percentage 
of the sample
(N=37)
According to innovator, service 
started in this year for this percentage 
of farmers in the sample 
(according to their locations)
2015 15 40.5% 63%
2016 15 40.5% 37%
2017 17 19% 0
When comparing ThirdEye’s reports referring to the year in which the service started in each location 
with the location of the 37 respondents presented in Table 1 above, there is a difference in timing. 
63% (or 20 out of 37) of the respondents were farming in locations that started receiving the service 
in 2015 and 37% (or 17 out of 37) were located in areas that started receiving the service in 2016, as 
informed by the innovator. No new locations started receiving the service in 2017. Many reasons could 
have caused a delay in farmers not receiving the service as soon as it was active in their locations 
(incompatibility between drone operators’ schedule and the farmers’) or farmers not remembering 
the year in which service started correctly. 
All the farmers interviewed were working in their farms at least 1 year before the service started so 
that comparisons could be drawn with farmers’ previous yields. 30 farmers out of 57 respondents 
were precise when informing for how long they had practiced agriculture. 12 other farmers said 
they had been farming for more than 10 years. From this group of 40 farmers, 8% (3 out of 40) of 
the farmers had been farming for up to 5 years, 3% (1 out of 40) had been farming between 5 to 10 
years, and 90% of the farmers (36 farmers out of 40) had been farming for more than 10 years, as 
presented in Graph 5 below. The other 17 farmers declared they were farming for at least a certain 
number of years, but were not precise, thus, were not considered. 
GRAPH 5. RESPONDENTS’ EXPERIENCE (IN YEARS) IN FARMING 
20%
40%
60%
80%
100%
RESPONDENTS’ EXPERIENCE
(IN YEARS) IN FARMING 
n=40
0%
≤ 5 years 5–10 years ≥ 10 years
8%
90%
3%
NUMBER OF FARMERS
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GRAPH 6. PERCENTAGE OF FARMERS THAT HAVE 
OTHER SOURCES OF INCOME BESIDES FARMING 
PERCENTAGE OF FARMERS THAT
HAVE OTHER SOURCES OF INCOME 
BESIDES FARMING 
n=62
64% None
13% Sporadic small jobs
11% Offspring help
3% Security guard
1% School teacher
2% Retirement
2% Church donations
2% Driver
2% Cattle
4. OTHER OCCUPATIONS OR SOURCES OF INCOME 
Most of the respondents (64% or 40 out of 62) have no other income source in their households 
besides farming (Graph 6). 3 of these farmers said that besides managing their own farms they also 
carry out sporadic small jobs for other farmers such as weeding their farms for a daily payment (of 
around MZN 100), which they use to buy inputs for their farms. 
In other sectors of economy, 8 farmers declared to have sporadic income in their households 
coming from small jobs in the services sector, such as carpentry (1 respondent), collecting straw 
(1 respondent), sales (1 respondent), construction (2 respondents), and mining (2 respondents). 2 
farmers declared that her husbands are security guards and one of these farmers also said that she 
raises cattle for financial emergencies, selling them when needed. One farmer is a school teacher 
(in the afternoons) and one farmer is a church leader, that receives church donations, and another 
farmer declared that her husband is retired. 7 farmers informed that they receive some kind of 
financial help from their offspring who work. 
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 11
1. SAMPLE SELECTION 
Sampling was done by visiting the farming areas, walking through the fields spotting farmers working 
on their land and asking if they had used the innovation. If they responded positively, then an in￾person interview was conducted on the spot. Some farmers did not immediately understand about 
which service we were asking, so a set of introductory questions and explanations was established 
to help them recall the innovation (“Do you remember the drone that flew here?” “Do you remember 
when a drone operator/technician came speak to you and show images that the drone had taken 
of your fields?” or “Did the leader in your association share the drone information with you and other 
farmers?”) 
In total, 62 farmers were interviewed out of 2,982 “ThirdEye Active Farmers” (as users were called in 
the innovator’s reports), that were spread around the locations identified in Maps 1 and 2 below. The 
total number of farmers per location and of interviewees is detailed in Table 2 below. 
III. METHODOLOGY
MAP 2. CLOSER LOOK AT RESPONDENTS´LOCATIONS 
IN THE SURROUNDINGS OF CHOKWÉ XAI-XAI
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TABLE 2. LOCATION OF “ACTIVE THIRDEYE FARMERS”, AS INFORMED BY 
INNOVATOR AND NUMBER OF INTERVIEWED FARMERS PER LOCATION 
Location Area 
Total Active 
ThirdEye Farmers
(in year 3)
Number of 
interviewed 
farmers
Xai-Xai Nhampondzoene Block 1, Subblocks 1-12 498 9
Xai-Xai Nhampondzoene Block 2, Subblocks 1-12 518 10
Xai-Xai Nhampondzoene Block 3, Subblocks 1-6 262 7
Xai-Xai Nhampondzoene Block 4, Subblocks 1-6 103 6
Xai-Xai Subtotal 1381 31
Chokwè D5A 103 8
Chokwè D5B 108 5
Chokwè Canal Esquerdo 0 0
Chokwè D6 98 4
Chokwè D11 296 4
Chokwè D12 539 3
Chokwè Macarretane 366 6
Chokwè Subtotal 1510 30
Moamba Carthage 1 0
Total 2892 62
 Source: First 3 columns were based on data provided by ThirdEye, fourth column is based on the present survey.
Sampling could not be done based on a contact list of innovator’s users since neither the 
innovator nor the leaders of associations had these lists ready. When speaking to the leader of the 
Nhampondzoene Association in Xai-Xai he was not sure of the number of farmers that had had 
access to the innovation. In fact, not using associations as a criteria for organizing the sample proved 
to be more appropriate since some farmers interviewed in the Chokwè area had used the service and 
had not been part of an association in their area. 
For the chosen sampling method to work, the field intern had to be accompanied by drone operators who 
knew the farming areas, how their subdivisions (in blocks and dickes) were organized, the roads to reach 
them and how to walk around in these areas, which are a maze of water channels. To ensure randomness, 
every morning before entering the field, the evaluator chose a path to walk that would cover a reasonable 
amount of area for that day and the drone operator was not given the chance to choose beforehand 
which farmers to visit in the field. Farmers were spotted while the team walked in the fields. 
The initial plan was to have the sample in proportion to the number of farmers in each location, which 
was achieved in Xai-Xai. In the Chokwé region, on the other hand, this was not possible since locations 
were almost empty when we visited them. For instance, even though the D12 area has the highest 
number of active ThirdEye farmers, the region is mainly used for rice plantation, which was only going 
to start in October. The D5A area, on the other hand, has less users, but many users of the service 
were present when the evaluator came to visit. 
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 13
One benefit of this sampling method is that it did not rely on leaders’ suggestions or a previous 
selected list of users, which made the sample free from any possible bias or underlying interests that 
leaders could have in referencing certain farmers. It also ensured randomness, since the field intern 
did not know the farmers beforehand or how they were spread out in the fields, or even who would 
be working on the days she visited the farming areas. It also allowed the evaluator to see farming 
practices in loco and gather important evidence through observation. 
On the other hand, this method brought relevant limitations. First, as interviews were not previously 
scheduled and farmers were not expecting to stop their work to answer a long survey, this limited 
how thorough and detailed the interview could be. Also, as interviews were carried outdoors, weather 
conditions played a relevant role, specially in the first week of interviews in Xai-Xai, which were carried 
out under heavy rain and low temperatures, which lead the evaluator to reduce the number of follow-up 
questions. For these reasons, not all interviewees answered all questions, since some questions were 
prioritized over others and whenever possible, questions were answered through direct observation of 
evidences in the farm. The number of respondents of each question in informed as “N” in this report. 
The drone operators also worked as translators when needed (Picture 2). Some farmers could 
understand Portuguese as spoken by the Field Evaluator, (who is a national of Brazil), but not all of 
them had the level of fluency necessary to provide thorough answers for questions that required 
higher levels of abstraction, especially, making connections between the drone flying over their land, 
the imagery presented to them and how this could have affected their farming decisions. The fact 
that the drone operator was present during the interviews does not seem to have affected farmers’ 
disposition to speak honestly. In the one hand, not all farmers knew the operator (since there were 
different operators working in different regions) and the evaluator made sure to emphasize that it was 
important that farmers were honest about their thoughts.
PHOTO 2. From left to right, 
Francisco Manjate (Leader of 
the Farmers’ Association in 
Xai-Xai), the Field Evaluator and 
Dércio Chissaque, former drone 
operator for ThirdEye. 
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It proved quite helpful to have the drone operator in the field since some farmers were mistaking 
the innovation with SDAE (Serviço Distrital de Atividades Econômicas), a state-run service to 
instruct farmers on better agricultural techniques. SDAE had been active in the same region as the 
innovation before the innovation was active and also consisted on a technician coming to speak to 
farmers about their farming practices in their land. During the interviews then, in many occasions, 
drone operators had to help farmers distinguish the service we were asking about, by showing their 
tablets or detailing their routines. 
In Chokwé, where one of the drone operators also worked as an SDAE technician, distinguishing 
the impact of the innovation from that of the SDAE service was a complex task, that was not 
always possible. 
PHOTO 3. Translator greeting a farmer, early morning in Xai-Xai.
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 15
2. SCOPE OF SURVEY AND SERVICE REACH 
The survey was targeted only at users of the service, so if a farmer answered that he/she had not 
used the service, the interview was not conducted with him/her. However, after walking in the fields in 
Xai-Xai for some days asking farmers about ThirdEye’s service and receiving many negative answers, 
concern arose about the actual reach of the service. For instance, in one day walking around Block 3 
in Xai-Xai, the evaluator met 6 farmers, besides the 4 interviewed farmers on this day, who said they 
had never spoken to the drone operator. 
As this was not part of the scope of the survey, the total number of farmers identified that had not 
used the service was not assessed, neither were the reasons for this to happen. However, speaking 
to drone operators about how the service was offered to farmers and observing the frequency of 
farmers in their land could help bring some understanding to the reasons why some farmers did not 
have access to the service or answered negatively. 
According to one drone operator in Xai-Xai, the service worked in the following way. Per week, each 
drone operator had 2 missions. In one mission they flew over 2 sub-blocks and then went to speak 
with up to 15 farmers from these 2 sub-blocks. In one month, they had to carry out 6 missions, so 
they flew 12 sub-blocks per month and were expected to speak to 90 farmers in total. The maximum 
number of drone operators in Xai-Xai working simultaneously was 3, which would lead to a maximum 
of 270 farmers visited per month in Xai-Xai when all of them were working. ThirdEye, in the document 
entitled “Appendix 1.1B Breakdown of ThirdEye Farmers” identified 1,381 “active ThirdEye farmers” in 
Xai-Xai. If the drone operators visited different farmers in every mission, it would have taken them 
around 5 months to have spoken at least once to all the farmers in Xai-Xai. If operators, for different 
reasons (such as farmers absence on that day, bad weather, inaccessible areas, etc.), spoke to the 
same farmers in their missions, this means that a relevant parcel of the farmers identified as ThirdEye 
“active farmers” were seldom visited by a drone operator. 
On the other hand, there are other possible reasons we could think of for why farmers answered that 
they had not spoken to a drone operator before, such as: (a) They had just recently started working 
on that land, (b) They share the land with someone else who comes to the farm more often, (d) They 
were receiving information through someone else (association leader, for instance) instead of directly 
speaking to the drone operator, (e) They did not want to speak to the drone operator, etc. However, 
all these are only hypotheses, since the real reasons were not assessed and would require further 
research. The evaluator also met 3 farmers during the entire survey who remembered speaking at 
least once to a drone operator but could not remember anything the operator had told them or what 
the service was about. These farmers were not interviewed. 
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3. OTHER METHODOLOGICAL CONSIDERATIONS
The fact that the innovation was considered to be active in the region from a certain year does not 
necessarily mean that farmers started having access to the service in that year, since this depended 
on the operator visiting the farm or not. When comparing changes before the innovation was active 
and after farmers had used the innovation, farmers were asked to provide information on their yields 
and practices before they started using the service. Some farmers could not tell exactly when this 
happened and in other cases, dates varied from farmer to farmer even within a same region, since 
farmers were visited by the drone operator in different moments. Whenever a farmer did not know 
when he began using the innovation, he was asked to provide information from before the innovation 
was officially active in his region. When asked to provide information after the use of the innovation 
(that is, after receiving information from drone operator), preference was given to the most recent 
yields and practices, in general yields from the end of 2017 or beginning of 2018 (depending on the 
crop cycle). The assumption here was that once the farmer received information from the drone 
operator, the effects of the service would be felt in the following yields since it took farmers some time 
to solve the issues identified by the service or to implement new techniques in the following seasons. 
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 17
1. TYPES OF INFORMATION RECEIVED BY FARMERS 
 FROM INNOVATION
The innovation affected farmers and their practices by providing them with information that was 
brought to them by the drone operators. Among the farmers who remembered to have spoken with a 
drone operator at least once and were able to explain what kind of information they had received (55 
farmers), 40% of them (22 out of 55) said that the drone operator had informed them where certain 
issues were located in their farms. 36% of the farmers (20 out of 55) declared that the operator 
had given them some form of advice on farming practices. 24% (13 out of 55) received both types of 
information combined. These results are summarized in Graph 7 below. 
It is possible to breakdown farmers’ description of information they received even further, since 46 
(out of the 55) farmers gave detailed answers on the main issues/matters they received information 
on. For the first category of information (identifying where there were problems in the farm) there 
were 8 different themes, listed in Table 3 below.
IV. RESULTS: Benefits of Innovation
GRAPH 7. TYPES OF INFORMATION RECEIVED FROM 
DRONE OPERATORS AS RECALLED BY FARMERS 
TYPES OF INFORMATION RECEIVED 
FROM DRONE OPERATORS AS 
RECALLED BY FARMERS 
n=55
32% Advice on farming practices
32% Both
Identified where there were
problems (Problem location)
68%
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TABLE 3. LIST OF ISSUES THAT FARMERS RECALL WERE IDENTIFIED BY DRONE 
OPERATOR IN THEIR FARMS AND HOW FREQUENTLY THEY WERE MENTIONED 1
Issues that farmers recall were identified 
by drone operator in their farms
Number of farmers that 
mentioned receiving 
information on the issue 
Percentage of farmers
(N=34)
Good/bad soil 16 47%
Pests 9 26%
Clogged channels 8 24%
Crop stress 4 12%
Unlevelled fields 3 9%
Flooding 1 3%
Confirmed what farmer was seeing 1 3%
Where to irrigate 1 3%
When it comes to the second category of information (advice on farming practices), farmers recalled 
receiving advice on 12 different topics relative to farming practices. The topics that were mentioned 
the most were related to pests (treating and avoiding them) and methods and techniques to sow and 
cultivate crops, as presented in Table 4 below.
TABLE 4. LIST OF TOPICS RELATED TO FARMING PRACTICES THAT 
FARMERS RECALL RECEIVING ADVICE ON BY DRONE OPERATORS 
AND HOW FREQUENTLY THEY WERE MENTIONED
ITopics related to farming practices that 
farmers recall receiving advice on by 
drone operators
Number of farmers that 
mentioned receiving 
information on the issue
Percentage
(N=31)
How to treat/avoid pests 9 29%
How to sow and cultivate crops 9 29%
Correct crop spacing 8 26%
How to use fertilizer 7 23%
How/when to irrigate 6 16%
Which crop to plant 3 10%
Causes of crop stress 2 6%
Stop burning weed 2 6%
Confirmed or encouraged continuation 
of good practices 2 6%
Explained crop stress 2 6%
Correct time to plant 1 3%
How to recognize stressed crops 1 3%
1 For the data summarized in Tables 4 and 3, topics were counted as mentions. Farmers mentioned at least one topic, meaning 
they and can also have mentioned more than one topic for each category of information.
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 19
Again pests were a major theme discussed with the drone operators and many farmers who received 
this type of information (29% or 9 out of the 31) received some kind of advice on how to treat or avoid 
pests (which pesticide to use, how much to use, when to use it, etc.). The second most common topic 
was advice on how to sow and cultivate crops: again 9 out of the 31 farmers who received advice on 
farming practices (or 29%) received advice on these matters. This category also included any general 
mentions on “how to plant” crops.
In the table above, farmers mentioned “pests” in general, but there is one specific pest that has been 
a common problem to many farmers and was frequently mentioned throughout the interviews as a 
main cause for reduced yields or for not producing as much as planned: rats. Out of 62 farmers, 9 
farmers (14%) explicitly complained, in some point of the interview, of how rat infestations affected 
their yields and motivation to farm. 3 of these farmers explicitly said that the drone did not have a 
positive impact on their work because it is not able to identify or solve the rat infestation in their farms. 
In fact, while walking around the fields in Xai-Xai the evaluator met a group of boys who were hired to 
try to eliminate rats in some farms. 
1.1. Perception of general benefits from innovation
Out of the 60 users that spoke about general benefits they perceived from innovation, 77% of them 
(46 out of 60) felt that there was some kind of benefit (direct/indirect) from the information they 
received while using the service and 23% of them (14 out of 60) felt that there were no benefits 
whatsoever. As summarized in Graph 8 below, from the 46 who perceived some kind of benefits, 
• 39 farmers (or 65% of the sample of 60 respondents) felt that there was only an individual or direct 
benefit from the information provided by the service;
• 4 farmers (or 7% of the 60 respondents) thought that there was both an individual/direct benefit 
and an indirect/collective benefit;
• 3 farmers (or 5% of the 60 respondents) thought that it brought an indirect/collective benefit, even 
though they did not find any individual/direct benefit from the service. 
GRAPH 8. PERCENTAGE OF FARMERS PER TYPE OF BENEFIT PERCEIVED 
PERCENTAGE OF FARMERS PER TYPE 
OF BENEFIT PERCEIVED 
n=60
65% Only individual/direct benefits
Individual/direct benefits and
collective/indirect benefits
7%
5% Only collective/indirect benefits
23% No benefits
20 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
3 of 43 farmers that felt an individual/direct benefit from the use of innovation also declared that, 
besides the information received from the operator, an important benefit of the innovation was that it 
made them feel more motivated to work after the drone operator visited their farm. 
In total, there were 7 farmers (12% of the sample of 60 farmers) that perceived a collective/indirect 
benefit from the use of the service. The indirect benefits identified by these farmers are listed in Table 
5 below. Of these 7 farmers, 3 have leadership positions (2 are leaders in their farmers’ associations 
and 1 is a member of the board in the association). Benefits of the service for leaders will be further 
discussed in Section IV.8 below.
TABLE 5. LIST OF INDIRECT/COLLECTIVE BENEFITS GENERATED BY 
USE OF INNOVATION IN THE REGION AS PERCEIVED BY FARMERS 
Consequences of the service Possible Indirect/collective benefit
Number of farmers 
that mentioned it
Encouraged farmers to clean 
water channels 
Can improve water circulation 
and availability 2 + 1 Leader
Encouraged farmers to keep 
their farms clean 
Can decrease the 
spread of pests 2 + 1 Leader
Farmers in general feel 
ike someone is checking on 
his/her progress
Can make farmers encouraged/
pressured to work 1 
Unlevelled fields 3 9%
Flooding 1 3%
Confirmed what farmer 
was seeing 1 3%
Where to irrigate 1 3%
Leaders of Association have 
an overview of the entire 
farming area and where 
problems are located
Allowed leaders to speak to farmers 
and try to help them solve issues or 
encourage them to work more
Produced images of the 
farming area
Leaders of associations could use 
images to confirm their observations 
or have more evidence to convince 
farmers to work
As mentioned before, 28% of respondents (17 out of 60) did not feel that using the innovation brought 
them any kind of benefits. The reasons given by these farmers for this negative perception are 
summarized in Table 6. 
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 21
TABLE 6. LIST OF INDIRECT/COLLECTIVE BENEFITS GENERATED BY 
USE OF INNOVATION IN THE REGION AS PERCEIVED BY FARMERS 
Why no benefit?
Number of farmers that 
mentioned the reason 
(N=17) 
Could not afford solution 7
Could already see the problem 5
Just identifying where problems are located is not really helpful, drone 
does not fix the problem 4
Has other factors that impact much more her production (pests, weather) 
that the drone does not fix 2
Could not understand the images and how they would be helpful 1
Did not know how to fix the problem 1
Already produced well 1
The 3 most common reasons given by farmers are related to the innovation’s main purpose, i.e, 
to inform farmers where problems are located in their farms. This type of information, however, 
did not bring these farmers positive change either because they could not afford the solution to 
the problem (normally, buying pesticides or fertilizers), or did not know how to fix the problem or 
because the innovation in itself does not provide a solution to the problem that had already been 
identified by the farmer. 
On the other hand, when comparing which type of information provided made most farmers perceive 
benefits, data suggests (Graph 9) that the type of information deemed as most beneficial to farmers 
was not the main scope of the innovation, but rather advice on farming practices. 
GRAPH 9. NUMBER OF FARMERS THAT PERCEIVED BENEFITS FROM USE 
OF INNOVATION PER TYPE OF INFORMATION FARMERS RECEIVED 
20%
40%
60%
80%
100%
NUMBER OF FARMERS THAT PERCEIVED
BENEFITS FROM USE OF INNOVATION PER TYPE OF 
INFORMATION FARMERS RECEIVED 
n=55
0% Identified where
there were problems
Advice on
farming practices
Both
Did not feel direct
benefits from innovaton
FARMERS THAT RECIEVED THIS INFORMATION
TYPE OF INFORMATION
41%
59%
10% 15%
85%
90%
Felt the innocation
was directly benefictial
22 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
As summarized above, 59% (13 out of 22) of farmers who received information on where a problem 
was located in his/her farm perceived a benefit from the use of innovation, while 90% (18 out of 20) 
of those who received advice on farming practices and 85% (11 out of 13) of those who received both 
types of information felt they benefited from innovation. 
This helps explain why when farmers were asked how could the service improve, 56% of respondents 
(19 out of 34) said that the service would be more effective if it not only identified where problems were 
located in the farms but also provided means to solve these problems, mostly fertilizers and pesticides. 
The second most common suggestion was that the innovation should provide farmers with more advice 
on farming practices. These and the other suggestions given by farmers are listed in Table 7 below. The 
other suggestions will be approached in the sections that follow whenever appropriate.
TABLE 7. FARMERS’ VIEWS ON HOW TO IMPROVE THE INNOVATION 
How can the service/innovation 
be improved?
Number of 
farmers 
Percentage over all farmers that 
answered about improvements
(n=34)
Not just identify problem but provide farm inputs 
(fertilizers/pesticides) to solve the problem 19 56%
Provide farmers with more knowledge/advice on 
farming practices 11 32%
Provide farmers with seeds 2 6%
Visit the most people they can 1 3%
Increase frequency of visits 1 3%
Visiting farmers in crucial moments 1 Leader 3%
Focus on solving water drainage issues 1 3%
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 23
2. WATER USAGE AND BENEFITS 
2.1. Irrigation methods
Farmers throughout the sample use different methods of irrigation and, in some cases, a combination 
of methods (rainf-fed, flooding and manual irrigation with buckets). 48% of farmers (29 out of 61) 
declared using flooding as primary irrigation method. These are actually all from the region of Chokwé, 
where flooding techniques are more common and well developed then in the farms visited in Xai-Xai. 
In Chokwé water comes from rivers (most stemming from the Limpopo River) in the surrounding areas 
that are channeled to the farms. 
All farmers from Xai-Xai (32 out of 61) have rain as primary source for water, which leads them 
to plant mostly maize. 69% (22 out of 32) of the farmers in Xai-Xai also mentioned using manual 
methods of irrigation (buckets and 1 farmer used a spray system) for irrigating vegetables, that are 
normally planted beside the maize plantations (mostly cale, sweet potatoes, lettuce and onions). 
Graph 10 below presents results for irrigation methods with percentages over the total amount of 
respondents for these questions (n=61).
PHOTO 4. Irrigation by flooding being practiced in the surroundings of Chokwé.
24 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
It was not possible to establish precise amounts of water used by farmers, either in Xai-Xai or Chokwé. 
In Xai-Xai, there were no measuring systems tracking water usage in the Nhampodzoene Association. 
When contacted, the regadio responsible for the area confirmed that they did not have information 
available on water flow and usage in the area. There also seemed to be very little consistency on 
frequency of irrigation by farmers or quantity of water used for each irrigation since farmers were very 
reliant on rain, adapting irrigation frequency to weather conditions (how dry or wet it is), amount and 
types of vegetables planted (which varies from season to season depending on quality, availability 
and accessibility of seeds).
To have a general idea of water consumption, farmers who use manual methods of irrigation 
(buckets) were asked to inform irrigation specifications for a warm day considering the average 
amount of vegetables they would have in their farms. The average of the amounts informed by 15 out 
of the 19 farmers who used buckets was of 69 liters per day. In warm and dry seasons farmers said 
they watered vegetables everyday. Graph 11 below summarizes the ranges of water usage among 
farmers in Xai-Xai that used buckets for irrigating vegetables. As described in the graph, 53% of these 
farmers (8 out of 15) use 50L/day of water or less in their vegetable gardens, 13% of farmers (2 out of 
15) use more than 50L/day but less than 100L/day and 33% (5 out of 15) use 100L/day or more.
GRAPH 10. DISTRIBUTION OF IRRIGATION METHODS AMONG FARMERS 
DISTRIBUTION OF IRRIGATION
METHODS AMONG FARMERS 
n=61
36% Rain-fed and buckets
50% Mostly flooding
14% Mostly rain-fed
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 25
Also, unlike farmers in Chokwé, farmers in Xai-Xai do not pay a fee for water. The channels in the 
association in Xai-Xai (Nhampodzoene Association) are classified as primary, secondary and tertiary 
(from bigger to smaller) and the regadio is responsible for cleaning primary channels, while farmers 
are responsible for the secondary and tertiary channels, which are the smaller channels stemming 
from the primary ones. As observed during field visits, many channels (primary, secondary and 
tertiary) were frequently clogged with dirt, grasses or weeds, probably having an impact on water 
distribution and drainage in the region. In fact, as detailed in Section III.3 below, farmers complained 
of the negative impacts that floods had on their yields.
GRAPH 11. RANGE OF WATER USAGE IN MANUAL IRRIGATION IN XAI-XAI 
≤ 50 L/day
0
1
2
3
4
5
50–100 L/day ≥ 100 L/day
6
7
8
RANGE OF WATER USAGE
IN MANUAL IRRIGATION IN XAI-XAI 
n=15
NUMBER OF FARMERS
8
2
5
PHOTO 4. Irrigation by flooding being practiced in the surroundings of Chokwé.
26 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
As in Xai-Xai, there were no measuring systems in place for assessing water usage in the different 
farming locations in the surroundings of Chokwé. 6 (out of 29) farmers in the surroundings of Chokwè 
informed that they were using a motor pump to bring water to their farms: one is a large-scale 
farmer that owns 2 pumps for his own farm, 4 are small-scale farmers in Macarretane that share 
their association’s motor pump and individually pay for the fuel whenever they use it for irrigation, 1 is 
a farmer in the D11 location that uses the pump from his association. Questions were asked to these 
farmers to try to quantify amount of water used (pump’s capacity/output, model, for how long pump 
was on, etc.) but farmers were not able to answer these questions precisely, so amount of water was 
not quantified. 
In the different areas where the innovation was active around Chokwé, all farmers except two pay 
a fee for using water. One was excused by her association to pay for water since she owned only 
0.25 ha of land and the other one did not pay because she used only underground water (the local 
association charges only for surface water). Associations in the region use different criteria to define 
the price charged from farmers for water (type of crop planted, season of the year, size of land 
owned/planted), so fees varied in between areas, as summarized in Table 8 below (which provides 
values for 0.5 ha as a common criteria for the sake of comparison). In farms in D5A, D5B and D6, 
farmers paid a flat fee for water based on amount of land used for production, which did not change 
if a farmer was more efficient in irrigation or not. In Macarretane farmers paid for the fuel used by the 
motor pump to bring water to their farms, which allowed them to save money (and consequently use 
less water) if they adopted more efficient irrigation techniques or improved their farming practices.
TABLE 8. FEES OR COSTS INVOLVED IN IRRIGATION FOR THE 
FARMERS LOCATED IN THE SURROUNDINGS OF CHOKWÈ 
Location
Cost/Fee
(calculated per 0.5 ha) 
Number of farmers 
interviewed 
D5A, D5B, D6 400 MZN for rice
200 MZN for maize 17
D12 500 MZN for rice 3
Macarretane 
association 
(to use motor pump)
200 MZN in the winter 
400 MZN in the summer 3
Macarretane area 
(to use motor pump) 1000 MZN 1 (large-scale 
farmer)
D11
different fees informed:
400 MZN
250 MZN for rice
750 MZN (summer), 250MZN (winter)
1
1
1
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 27
2.2. Water benefits
For the reasons explained above, it was not possible to quantify water usage in Xai-Xai and Chokwè in 
order to assess if innovation helped decrease water consumption in the region as a whole. However, 
the innovation brought some water benefits that were identified by farmers. None of the farmers 
interviewed, in the two regions, changed their irrigation methods over the period while the innovation 
was active in Mozambique.
When asked specifically if they had observed changes in amount of water used since the innovation 
was active, 77% (48 out of 62) of farmers were not sure or did not think that they had changed the 
amount of water used in their farms since the innovation was implemented in the region (Graph 12 
below). 23% of farmers (14 out of 62) answered that they experienced some change in water usage 
when compared to amounts of water used before the innovation was active. Of these 23%, 3 farmers 
(5% of the 62 respondents), experienced changes that were not directly linked to the use of innovation: 
2 farmers were using less water due to problems with water drainage in the area (mainly due to 
clogged channels) and 1 farmer was being able to use more water due to cleaning of channels. 
The other 11 farmers (18% of the sample of 62 farmers) justified this change as being connected 
(either directly or indirectly) to the use of the innovation and their explanations for this change are 
summarized in Table 9 below. Of these 11 farmers, 4 farmers said that the drone operator advised 
them to decrease amount of water for irrigation, as this could alleviate the crop stress they were 
seeing in their farms. 1 farmer explained that he was using less water to irrigate because since the 
drone operator had explained him how to use straw to cover the soil, the soil had been able to retain 
humidity for longer periods. One farmer explained that she is using less water since she started using 
fertilizers, which was encouraged by the drone operator (before doing this, she thought that the plants 
were weak and would water them more to make them stronger).
GRAPH 12. PERCENTAGE OF FARMERS THAT EXPERIENCED CHANGES IN 
WATER USAGE IN THEIR FARMS AFTER THE INNOVATION WAS INTRODUCED 
PERCENTAGE OF FARMERS THAT EXPERIENCED 
CHANGES IN WATER USAGE IN THEIR FARMS 
AFTER THE INNOVATION WAS INTRODUCED 
n=62
Changes in water usage
due to innovation
18%
Changes in water usage
not related to innovation
5%
77% Unsure or no change
28 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
TABLE 9. CHANGES IN WATER USAGE AS EXPLAINED BY FARMERS THAT 
EXPERIENCED A DECREASE IN WATER USAGE DUE TO THE INNOVATION
Impact Change as perceived by farmers Due to
Number of farmers that 
mentioned impact
Direct Decreased water usage Operator’s advice on 
farming practices 6
Indirect More efficient use of water Levelling of the fields 5
Five of these 11 farmers noticed that the recent levelling of the fields in their farming areas improved 
water usage, avoiding floods and crop stress due to unleveled fields. This improvement is not a 
direct consequence of the innovation, but the leader of this association, already knowing that the 
fields needed to be levelled, used images provided by the service to reinforce his argument to local 
authorities that they needed to level the fields in that area. The leader of the association explained 
how the levelling makes water usage more efficient:
“If the fields are not levelled we produce less. Water does not 
flow correctly, so we end up using the incorrect amount of water, 
which in some areas causes hydric stress.”
Besides the benefits listed above, that were explained by farmers when they were specifically asked to 
explain if they saw any impacts of the innovation on their use of water, there are other other benefits 
that the innovation could have caused in terms of water usage. As mentioned before, in Section 
III.1, farmers received information from drone operators that consisted either on identifying where 
problems were located or on advice on how to improve farming practices. In both these categories, 
different topics were approached by the drone operator that could have lead to a positive impact on 
water usage, either directly or indirectly. Some information and advice received were more related to 
water usage (such as identifying clogged channels, unlevelled fields, flooding areas, where to irrigate, 
etc.) but, improving farming practices in general (for instance by following correct crop spacing, or 
learning about fertilizer and pesticide use) can also improve efficiency of water use. Also in Section III.1 
above, 3 farmers mentioned that the innovation could have an indirect benefit on water circulation in 
their areas since it encouraged farmers to clean the water channels around their farms. 
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 29
3. CROP BENEFITS 
During the period that the innovation was active, many farmers saw changes in their yields (Graph 
13). When comparing farmers’ last yields with average yields before using the innovation2, 59% (35 
out of 59) of the farmers had an increase in yields. The average increase in yields was of 89% and the 
median increase was of 50%. 24% (14 out of 59) of farmers saw no change in their yields and 17% (10 
out of 59) farmers saw their yields decrease over this time. The average decrease was of 70% and the 
median decrease was of 75% of the original yield. 
2 Changes to crop yields were compared between farmers’ average yield in one season before use of innovation and the yield in 
the most recent season, after having used the innovation. Only farmers’ main crop was used for comparison. For instance, if 
farmer plants mainly maize but sporadically plants vegetables or plants very few vegetables beside the maize, only maize was 
taken into consideration. In case a farmer planted different crops but the farmer felt that the innovation only had an impact on 
one specific crop, this crop was taken in consideration and not the others. In the region of Chokwè, where many farmers worked 
in a rotation system (rotating between beans, maize and rice) preference was given to comparing one season of rice since this 
crop was the main source of income of most of the farmers, unless stated otherwise or innovation had affected another crop. 
PHOTO 6. Beans harvested by female farmers in D5B, surroundings of Chokwè.
GRAPH 13. CHANGES IN YIELDS, WHEN COMPARING 
BEFORE AND AFTER THE INNOVATION WAS ACTIVE CHANGES IN YIELDS, WHEN COMPARING BEFORE 
AND AFTER THE INNOVATION WAS ACTIVE 
n=59
Farmers whose yields
did not change
24%
Farmers that had
an increase
59%
Farmers who had
a decrease
17%
30 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
But not all farmers who increased their yields made an explicit direct connection between this change 
and the use of the innovation. Among the 35 farmers who had an increase in yields, 19 of them (54% 
of those who had an increase) established a connection between this change and the innovation: 
18 of these farmers think that the information they received from the drone operator had a positive 
impact on their production, and 1 farmer highlighted that the levelling of fields in his association (a 
process that used drone images as visual support) had an impact on his production, also increasing 
yields. This means that 32% of all respondents (or 19 out of 59) established an explicit direct 
connection between the increase in their yields over the period analyzed and the use of the innovation. 
Other factors that were highlighted by farmers while explaining the increase in their yields were: being 
able to buy/have access to agricultural inputs such as fertilizers, pesticides or seeds (3 mentions), 
improving water drainage in their farms or surroundings (2 mentions) and fixing salinity of soils (1 
mention), as summarized in Graph 14.
GRAPH 14. FACTORS THAT POSITIVELY IMPACTED YIELDS AND 
HOW FREQUENTLY THEY WERE MENTIONED BY FARMERS3
On the other hand, 23 farmers (out of the 59 respondents) gave detailed explanations as to why 
they did not see a change in yields, produced less or did not produce as much as planned (even 
for those who had an increase). The following factors were mentioned as negatively impacting 
production: pests (18 mentions), floods (7 mentions), weather (6 mentions), not having farming inputs 
such as fertilizers, pesticides or seeds (4 mentions), insufficient workforce to share the workload with 
(1 mention), salinity of soils (1 mention), low quality of seeds (1 mention), lack of knowledge about 
agricultural techniques (1 mention), as summarized in Graph 15 below. 
At least 6 of these mentions to pests are referent to rats. As explained before, rat infestations were 
common in both Xai-Xai and Chokwé farms and farmers perceived them as having a negative impact 
on yields since rats ate most of the produce (maize, sweet potatoes). This also also impacted seed 
availability for the following season, decreasing yields. 
3 It is important to observe that both Graphs 14 and 15 refer to the frequency in which a factor was mentioned compared to all 
mentioned factors and that some farmers mentioned more than one factor.
FACTORS THAT POSITIVELY IMPACTED 
YIELDS AND HOW FREQUENTLY THEY 
WERE MENTIONED BY FARMERS 
n=24
Percentages calculated for each mention over a total of 25 mentions.
12% Having inputs/money
8% Water drainage
4% Levelling of fields
4% Correcting salinity
Information received
from operator
72%
GRAPH 14. FACTORS THAT POSITIVELY IMPACTED YIELDS AND 
HOW FREQUENTLY THEY WERE MENTIONED BY FARMERS3
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 31
Regarding possible increases in crop survival rates or in crop quality, these questions were not asked 
to farmers who had a decrease or no change in their yields. All those who had an increase in yields 
(59% or 35 out of 59 farmers) thought that either crop survival or quality had increased. Farmers 
expressed that they could see the improve in quality of their crops through expressions like “yes, fat 
pretty beans”, “yes, clearly improved quality”, “yes, better beans” and “I was marveled at the quality of 
the corn after using pesticides”.
GRAPH 15. FACTORS THAT NEGATIVELY IMPACTED YIELDS 
AND HOW FREQUENTLY THEY WERE MENTIONED BY FARMERS 
FACTORS THAT NEGATIVELY IMPACTED 
YIELDS AND HOW FREQUENTLY THEY 
WERE MENTIONED BY FARMERS 
n=23
Percentages calculated for each mention over a total of 39 mentions.
46% Pests
18% Floods
15% Weather
Not having
inputs
10%
2% Insufficient workforce
3% Sailinity
Low quality
of seeds
3%
Little knowledge
on farming
3%
32 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
4. FARMERS’ INCOMES AND INCOME BENEFITS 
As many of the farmers interviewed did not keep track of their yearly incomes or were not able to 
remember yearly incomes from previous years as far as 2015 or 2014 with accuracy, to have an 
overview of farmers’ income this report considered data based on revenues for one season’s harvest. 
That is, change in income was assessed by comparing how much farmers used to earn, in average, 
by selling their yields before the innovation was active in their region and how much they earned by 
selling their yields after using the innovation. Regarding income after using the innovation, farmers 
were asked to focus on the most recent season for the sake of comparison. Income was considered 
per season of the farmers’ main crop (or the crop affected by the innovation in case this was not the 
same), that is, how much money a farmer earned by selling one harvest (or a part of it) of his/her 
main crop. 51 farmers were able to provide data on their revenues from selling crops and other data 
relevant to this section on income and on the next section, on poverty reduction. 
Before innovation was active, 53% (27 out of 51) of the farmers were selling their yields and had an 
average revenue of 21,800 MZN per harvest. The other 47% (24 out of 51) of the farmers practiced 
subsistence agriculture, meaning that they did not use to sell their yields, which were consumed 
mostly within their households. After having the innovation active in Mozambique, 55% (28 out of 
51) farmers, sold their yields and this time the average income of was of 33,466 MZN, meaning an 
increase of 54% in income. 
But not all farmers had an increase in income and not all farmers who were selling before continued 
selling after the innovation. 4 out of the 28 farmers who were selling before did not sell their yields 
recently and 5 farmers who were not selling before, sold their yields recently. In fact, data shows, as 
illustrated in Graph 16 below, that 55% (28 out of 51) of the farmers had no changes in income, while 
27% (14 out of 51) of the farmers had an increase in income and 18% (9 out of 51) had a decrease 
in income. The decreases in income were preceded by decreases in yields, except in 2 (out of the 9) 
cases, where decrease in income was due to the fact that farmers were too late to sell their yields. All 
the farmers who saw an increase in income also had an increase in yields. 
GRAPH 16. CHANGES IN INCOME EXPERIENCED BY FARMERS COMPARING INCOMES 
AFTER THE INNOVATION WAS ACTIVE WITH BEFORE THE INNOVATION WAS INTRODUCED 
CHANGES IN INCOME EXPERIENCED BY 
FARMERS COMPARING INCOMES AFTER THE 
INNOVATION WAS ACTIVE WITH BEFORE 
THE INNOVATION WAS INTRODUCED 
n=51
27% Farmers that had in increase
18% Farmers that had a decrease
55% Farmers that had no change
By using farmers’ data on their incomes before and after the innovation was active, it was possible 
to classify them into income groups and compare the distribution of farmers per income groups 
before and after the innovation was active, as presented in Graph 17 below. Group D corresponds to 
the poorest group of farmers, i.e., farmers who in that period (either before or after innovation was 
active) had no other source of income and practiced subsistence agriculture. Group C corresponds to 
farmers who when selling their yields (either before or after the innovation was active) did not obtain 
incomes greater than 5,000 MZN or another source of income that would provide them with same 
amount in one season. Group B corresponds to farmers who, when selling their yields (either before 
or after the innovation was active), earned more than 5,000 MZN but did not obtain incomes greater 
than 10,000 MZN, also considering other income sources. Group A corresponds to farmers who, when 
selling their yields (either before or after the innovation was active), obtained incomes greater than 
10,000 MZN, also considering other income sources. 
When looking at the individual progress that farmers had, as detailed above, we see that 14 (out of 
51) farmers had an increase in their income, outnumbering farmers who had a decrease (9 out of 51). 
However, if we look at the sample as a whole, Graph 17 shows that there was actually little change 
for the entire sample and within income groups. Comparing income groups before and after the 
innovation was active, the only visible change for the entire sample was that the number of farmers in 
Group B decreased because 2 farmers were able to improve their classifications, moving from Group 
B to Group A.
GRAPH 17. INCOME RANGE OF FARMERS BEFORE AND 
AFTER INNOVATION WAS ACTIVE IN THEIR FARMS 
5
10
15
20
25
Group A Group B Group C Group D
10
5
3
24
13
24
13 12
0
INCOME RANGE OF FARMERS BEFORE AND AFTER 
INNOVATION WAS ACTIVE IN THEIR FARMS 
n=51
Before innovation After innovation
NUMBER OF FARMERS
34 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
5. POVERTY REDUCTION BENEFITS 
According to the international poverty line standards, 62.2% of Mozambicans were living with less 
than USD 1.90 in 2014 (World Bank, 2018). Even though this survey did not focus on collecting 
specific data to analyse poverty trends and that time constraints limited amount of observations 
and data collection that could help assess farmers’ poverty levels, poverty will be assessed based on 
combination of answers to different questions of the survey. We will look at data from 51 respondents 
who provided enough information on the relevant questions (concerning income, yields, adherence to 
innovation and perception of benefits). 
As mentioned in the previous section, before the innovation was active, 47% (24 out of 51) of the 
farmers practiced subsistence agriculture, meaning that they did not use to sell their yields, which 
were consumed mostly within their households. 11 of these farmers (or 22% of the sample of 51 
farmers) had no other source of income, depending entirely on subsistence farming or on very 
sporadic commercialization of very small amounts of their produce. This not only sets them below the 
international poverty line but sets them as the poorest farmers in the sample. 
From this set of poorest farmers, 3 out of 11 or 27% of the poorest farmers started selling some of 
their yields after the innovation was introduced, and their average income was of 13,500 MZN in their 
last harvest. None of these 3 farmers, however made an explicit connection between the use of the 
innovation and their increase in yields and in income. 
On the other hand, 8 out of 11 or 73% of the poorest farmers had no changes in their situation. 3 farmers 
recently joined the group of poorest farmers after the innovation was introduced since they did not 
have any other source of income and did not sell their harvest recently, keeping the number of poorest 
farmers still at 11. In the case of these 3 farmers, the decrease in income is connected to a decrease in 
yields and as discussed above, in Section III.3, different factors could have influenced this change. 
Using the same income group classification as in Section III.4 above (but adapting it accordingly4), it was 
possible to compare farmers’ perception of benefits per income group, as presented in Graph 18 below.
4 In Section 4, farmers were classified per income group for the period before innovation was active and then classified again, 
according to their incomes before innovation was active. For this graph in Section 5, change over time was not being assessed, 
so farmers were classified only once according to their highest income, according to values established for each income group 
in Section 4.
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 35
As information provided by 51 respondents show, less farmers from Group D, i.e., the poorest group 
of farmers, felt that the innovation brought a direct benefit to them as compared to farmers that fall 
into Groups A, B and C. Seventy-one percent (10 out of 14) of the farmers in Group A, 80% (4 out of 
5) of the farmers in Group B, and 78% (18 out of 23) of the farmers in Group C felt the innovation was 
directly beneficial to them, while only 56% (5 out of 9) of the farmers in Group D felt that way.
GRAPH 18. FARMERS’ PERCEPTION OF GENERAL BENEFITS PER INCOME GROUP 
20%
40%
60%
80%
100%
0%
Group A Group B Group C Group D
Did not feel direct
benefits from innovaton
PERCENTAGE OF FARMERS IN GROUP
29%
71%
56%
80% 78%
20% 22% 44%
Felt the innovation
was directly benefictial
FARMERS’ PERCEPTION OF GENERAL
BENEFITS PER INCOME GROUP 
n=51
36 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
6. ADHERENCE TO SERVICE 
To have the service active in a certain region was not an individual decision, since this decision was 
either made collectively by the farmers’ association or by the innovator, who chose an area to work in. 
These factors impacted how farmers answered questions regarding if they would like to continue with 
the service and if they would be willing to pay for it, since most of the farmers would first explain that 
this did not depend on them individually and that they had never paid for it and were not sure of which 
price they could afford. 
When asked if they would like the service to continue, 66% (41 out of 62) of the farmers said yes, 24% 
(15 out of 62) said no, and 10% (6 out of 62) said they were unsure about it, as illustrated in Graph 
19 below. Of the 6 farmers who were unsure, 4 of them explained that they were not sure if the 
innovation was really beneficial to them or if it would continue being. The farmers who answered that 
they did not want the service to continue and justified their answers, gave the following reasons for it: 
• The innovation has no real impact for the farmer (9 farmers)
• He cannot afford it (1 farmer)
• There are no problems in his farm so help is not needed (1 farmer)
• She does not understand how the service worked (1 farmer)
GRAPH 19. FARMERS’ ANSWERS WHEN ASKED 
IF THEY WOULD LIKE THE SERVICE TO CONTINUE FARMERS’ ANSWERS WHEN ASKED IF THEY 
WOULD LIKE THE SERVICE TO CONTINUE
n=62
66% Yes
24% No
10% Unsure
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 37
When it comes to adherence per income group, it is interesting that, despite the fact that more 
farmers from higher income groups perceived direct benefits from innovation, when farmers were 
asked if they wanted the service to continue, more farmers from the lower income groups (Groups D 
and C) were positive about having the service continue, as detailed in Graph 20 below. 50% (7 out 
of 14) of the farmers in Group A and 60% (3 out of 5) of the farmers in group B stated that they did 
not want the service to continue, while 83% (19 out of 23) of the farmers in Group C and 78% (7 out of 
9) of the farmers in Group D stated that they would like the service to continue. Possible reasons for 
these trends will be discussed in Section IV below.
GRAPH 20. FARMERS’ ADHERENCE TO THE INNOVATION PER INCOME GROUP 
20%
40%
60%
80%
100%
0%
Group A Group B Group C Group D
Did not want service
to continue or insure
PERCENTAGE OF FARMERS IN GROUP
50%
50%
78%
60%
83%
40% 17% 22%
Would like service
to continue
FARMERS’ ADHERENCE TO
THE INNOVATION PER INCOME GROUP 
n=51
38 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
7. GENDER DIFFERENCES IN BENEFITS 
7.1. Gender and general perception of benefits by type of information received
In terms of perceived benefits, as detailed in Section III.1.1 above, 77% of farmers perceived that the 
innovation was beneficial to them (either directly or indirectly). This same proportion was kept within 
female and male farmers (Graph 20): 76% of the female farmers (29 out of 38) felt they benefited 
(either directly or indirectly) from the use of the innovation as did 76% of the male farmers (13 out of 17). 
There were small differences regarding benefits when comparing the type of information received by 
farmers from drone operators, as it is clear by comparing Graphs 22 and 23 below. However, both 
men and women felt that the innovation was less beneficial when they received only information 
identifying where problems were located in their farms: 60% (9 out of 15) of the women felt that was 
beneficial as did 57% (4 out of 7) of the men. More men felt the innovation was beneficial when they 
received advice on farming practices: 100% (7 out of 7) of the male farmers who received this type of 
information thought the innovation was beneficial, compared to 67% (2 out of 3), who received both 
types of information. Women, on the other hand, felt the innovation was beneficial when they received 
both types of information combined (identification of where problem is located and advice on farming 
practices): 90% of the women who received the combination felt the innovation was beneficial, 
compared to 85% (11 out of 13) who received only advice on farming practices.
GRAPH 21. COMPARISON BETWEEN FEMALE AND MALE FARMERS’ 
PERCEPTION ON GENERAL BENEFITS PROVIDED BY THE INNOVATION 
20%
40%
60%
80%
100%
0%
PERCENTAGE OF FARMERS IN GENDER GROUP
24%
76%
24%
76%
COMPARISON BETWEEN FEMALE AND MALE 
FARMERS’ PERCEPTION ON GENERAL BENEFITS 
PROVIDED BY THE INNOVATION
n=55
Did not feel direct
benefits from innovaton
Felt the innocation
was directly benefictial
Male Female
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 39
Women also seem to have found an indirect benefit in the innovation that was not mentioned by any 
men: 3 women mentioned how the fact that the drone operator came visit their farms gave them 
extra motivation to work. One female farmer also said that after her husband passed away, having 
the drone operator come visit her gave her motivation to keep working by herself.
GRAPH 22. PERCEPTION OF GENERAL BENEFITS BY 
MALE FARMERS PER TYPE OF INFORMATION RECEIVED 
20%
40%
60%
80%
100%
0% Problem location Advice on
farming practices
Both
Did not feel direct
benefits from innovaton
PERCENTAGE OF FARMERS
43%
57%
100% 34%
66%
Felt the innocation
was directly benefictial
PERCEPTION OF GENERAL BENEFITS BY MALE 
FARMERS PER TYPE OF INFORMATION RECEIVED 
n=17
GRAPH 23. PERCEPTION OF GENERAL BENEFITS BY 
FEMALE FARMERS PER TYPE OF INFORMATION RECEIVED 
20%
40%
60%
80%
100%
0% Problem location Advice on
farming practices
Both
Did not feel direct
benefits from innovaton
PERCENTAGE OF FARMERS
40%
60%
15% 10%
85%
90%
Felt the innocation
was directly benefictial
PERCEPTION OF GENERAL BENEFITS BY FEMALE 
FARMERS PER TYPE OF INFORMATION RECEIVED 
n=38
40 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
7.2. Gender and changes in yields 
Compared to men, female farmers, in average, had a lower 
increase in yields when comparing their last yields with those 
before the innovation was active in Mozambique. The average 
increase of the 20 female farmers who provided information on 
yields was of 66%, compared to an average increase of 136% for 
the 10 male farmers who provided this information. If we consider 
both increases and decreases in yields within gender groups, 
male farmers still had a better average: 63% of net increase 
(based on answers by 15 male farmers) compared to 47% of net 
increase for women (based on answers by 24 female farmers). 
However, more women saw their yields increase over the time 
the innovation was active (Graph 24). 62% (24 out of 39) of the 
female farmers had an increase in their yields, compared to 
55% (11 out of 20) of the male farmers. And more male farmers, 
30% (6 out of 20), saw their yields decrease, when compared 
to female farmers, 10% (4 out of 39). 28% (11 out of 39) of the 
female farmers and 15% (3 out of 20) of the male farmers saw 
no change in yields. 
Also, more women that had an increase in yields established a connection between their change in 
yields and the use of the innovation: 58% (14 out of 24) women compared to 45% (5 out of 11) men.
GRAPH 24. CHANGES IN YIELDS PER GENDER, COMPARING 
AVERAGE YIELDS BEFORE INNOVATION WAS ACTIVE WITH YIELDS 
AFTER FARMERS USED THE INNOVATION (MOST RECENT YIELDS) 
% of farmers who
had an increase
Males Females
0%
10%
20%
30%
40%
50%
% of farmers who
had a decrease
% of farmers who
had no change
60%
70%
55%
30%
10%
28%
15%
62%
CHANGES IN YIELDS PER GENDER, COMPARING 
AVERAGE YIELDS BEFORE INNOVATION WAS ACTIVE 
WITH YIELDS AFTER FARMERS USED THE INNOVATION 
(MOST RECENT YIELDS) 
n=59
PHOTO 7. Farmer preparing beans in 
Macarretane, surroundings of Chokwé.
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 41
7.3. Gender and income 
Data also shows that, besides owning more land, male farmers are wealthier than female farmers 
(Graph 25). 40% of male farmers (6 out of 15) are classified in Group A, compared to 22% female 
farmers (8 out of 36). In fact When adding the number of female farmers in the wealthiest groups 
(Group A and B), it is still proportionately less than male farmers only in Group A: 36% (12 farmers 
in Group A and 4 farmers in Group B). There were no male farmers in Group B, and there are 
more male farmers in Group C than female farmers: 53% (7 out of 15) compared to 42% (16 out of 
36). However, there were more female farmers in Group D than male farmers: 22% (8 out of 36) 
compared to 7% (1 out of 15). 
GRAPH 25. INCOME DISTRIBUTION BETWEEN MALE AND FEMALE FARMERS 
20%
40%
60%
80%
100%
0% Male
(15 farmers)
Female
(36 farmers)
Group A
PERCENTAGE OF FARMERS PER GENDER GROUP
40%
53%
7%
22%
22%
42%
14%
Group B Group C Group D
INCOME DISTRIBUTION
BETWEEN MALE AND FEMALE FARMERS 
n=51
42 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
7.4. Gender and adherence to service 
Even though farmers’ perception of benefits between gender groups was the same (with slight 
differences according to type of information provided), less women had a positive answer when asked 
if the service should continue active in their region, when compared to men (Graph 26). 
GRAPH 26. ADHERENCE TO SERVICE PER GENDER 
20%
40%
60%
80%
100%
0%
Does not think service
should continue
PERCENTAGE OF FARMERS IN GENDER GROUP
20%
10%
70%
26%
64%
10%
Is unsure Thinks service
should continue
ADHERENCE TO SERVICE PER GENDER 
n=62
Male (20 farmers) Female (42 farmers)
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 43
8. REGIONAL DIFFERENCES 
After conducting the survey in the two regions where innovation was active, Xai-Xai and Chokwé, it was 
clear that there were differences between the two, specially in terms of benefits perceived by farmers. 
Even though the same type of information was given to approximately the same number of farmers 
(Graph 27 below), less farmers’ in Xai-Xai perceived a direct benefit from the innovation (Graph 28).
GRAPH 27. DISTRIBUTION OF TYPES OF INFORMATION RECEIVED 
BY FARMERS PER REGION WHERE INNOVATION WAS ACTIVE 
20%
40%
60%
80%
100%
0%
Both
PERCENTAGE OF FARMERS PER REGION
28%
32%
40%
20%
40%
40%
Advice on farming practices Problem location
FARMERS’ ANSWERS TO THE QUESTION “WOULD YOU 
LIKE SERVICE TO CONTINUE ACTIVE?” IN EACH REGION n=62
Xai-Xai
(25 farmers)
Chokwè
(30 farmers)
GRAPH 28. FARMERS’ PERCEPTION OF DIRECT BENEFITS 
IN EACH LOCATION WHERE INNOVATION WAS ACTIVE 
20%
40%
60%
80%
100%
0%
FARMERS PER REGION
36%
64%
13%
87%
FARMERS’ PERCEPTION OF DIRECT BENEFITS IN EACH 
LOCATION WHERE INNOVATION WAS ACTIVE
n=55
Did not feel direct
benefits from innovaton
Felt the innocation
was directly benefictial
Xai-Xai
(27 farmers)
Chokwè
(24 farmers)
44 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
It goes beyond the scope of this survey to thoroughly understand all the reasons that could explain 
this regional difference, but looking at some of the farmers’ comments about their experience with the 
innovation could bring some insights. For instance, in Xai-Xai most of the farmers that did not perceive 
a benefit in the innovation complained that they could not afford the solutions for the problems 
identified or to buy the inputs suggested by the drone operator. In some farms in Chokwé, on the other 
hand, the drone operator suggested cheap solutions to problems identified, which made farmers very 
positive about the innovation. Solutions and advice like these were not mentioned by farmers in Xai-Xai. 
It should also be considered that farmers’ situation differ from one region to the other. Just as an 
example, Xai-Xai farmers are poorer (Graph 29) and own smaller farms than farmers in Chokwé, 
but there are other differences that will not be assessed here. While 89% (24 out of 27) of farmers in 
Xai-Xai classified in the poorest income groups (Group D and C), only 33% (8 out of 24) of the farmers 
in Chokwé fell in these income groups. Actually, 50% (12 out of 24) of the farmers in Chokwé were in 
Group A, the wealthiest group of farmers, compared to 7% (2 out of 27) of the farmers in Xai-Xai.
GRAPH 29. INCOME DISTRIBUTION PER GROUPS IN BOTH 
LOCATIONS WHERE INNOVATION WAS ACTIVE 
20%
40%
60%
80%
100%
0% Xai-Xai (27 farmers)
Chokwè (24 farmers)
Group A
PERCENTAGE OF FARMERS PER LOCATION
7%
60%
30%
50%
4%
28%
18%
3%
Group B Group C Group D
INCOME DISTRIBUTION PER GROUPS IN BOTH 
LOCATIONS WHERE INNOVATION WAS ACTIVE 
n=51
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 45
When it comes to size of farms, Xai-Xai farmers 
own in average 0.7 hectares, while farmers in 
Chokwé own 1.4 hectares, excluding the two 
larger farmers (who own 72 and 15 hectares 
each), which is twice the average area owned 
by farmers in Xai-Xai. Including the large-scale 
farmers, the average in Chokwé increases to 4.2 
hectares. The median for farm size in Xai-Xai is 
0.5 hectares, compared to 1.0 in Chokwé.
On the other hand, despite the differences in 
benefit perception, when farmers were asked 
if they wanted the service to continue, there 
were almost no differences in farmers answers 
between these two regions (Graph 30).
GRAPH 30. FARMERS’ ANSWERS TO THE QUESTION 
“WOULD YOU LIKE SERVICE TO CONTINUE ACTIVE?” IN EACH REGION 
20%
40%
60%
80%
100%
0%
Does not think service
should continue
PERCENTAGE OF FARMERS PER LOCATION
25%
10%
65%
23%
67%
10%
Is unsure Thinks service
should continue
FARMERS’ ANSWERS TO THE QUESTION “WOULD YOU 
LIKE SERVICE TO CONTINUE ACTIVE?” IN EACH REGION n=62
Xai-Xai (32 farmers) Chokwè (30 farmers)
46 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
1. CROP AND WATER BENEFITS
1.1. Crop benefits 
As detailed in Section III.3 above, 59% (35 out of 59) farmers saw their yields increase over the period 
the innovation was active in Mozambique. All of those who had increases felt that there was better 
quality or improved survival rates of their crops. However, only 32% (or 19 out of 59) of all respondents 
established an explicit direct connection between the increase in their yields over the period analyzed 
and the use of the innovation. Many other factors besides the innovation played a critical role on crop 
survival rates and farmers’ results. The many factors that farmers perceived as causes for increasing 
or decreasing yields were also presented in Section III.3 above. 
Among the main factors that were seen as hindering production, rat infestations and extreme 
weather conditions were highlighted as problems that the innovation is not able to solve or provide 
a useful solution to, therefore not having a significant impact on yields. In fact, Mozambique is well 
known for suffering from extreme weather events and variability, such as droughts and floods that 
have direct consequences on agriculture (World Bank, 2011). These results thus raise the question 
as to what extent the innovation has been able to impact crop survival and yields in unfavourable 
scenarios such as the one found in Mozambique. 
V. DISCUSSION
PHOTO 8. Farmer in the surroundings of Chokwé who thought the innovation was 
beneficial because it helped improve her farming techniques and increased her yields.
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 47
Data also shows that farmers who received advice on farming practices or this type of information 
combined with the location of problems in their farms obtained better yields then those who only 
received information on the location of problems (Graph 31 below). 85% of the farmers who received 
advice on farming practices (17 out of 20) had an increase in their yields, while 15% (3 out of 20) saw 
no change in yields. This was a much better result than that experienced by farmers who received only 
information on location of problems in their farms: 55% of them (11 out of 20) had an increase in yields, 
but 30% (6 out of 20) saw their yields decrease and 15% (3 out of 20) saw no change. 46% of farmers 
who received both types of information (6 out of 13) saw their yields increase, while 31% (4 out of 13) 
saw no changes and 23% (3 out of 13) saw yields decrease.
In this sense, data shows that it is possible that innovation benefited crop yields more through 
advising farmers on farming practices than by only showing them imagery to help them locate where 
an issue was occuring in their farms. Farming knowledge is highly valued and requested by many of 
the farmers interviewed. Providing farmers with more knowledge on farming practices and techniques 
was the second most common suggestion that farmers gave when asked about how the service 
could be improved, as detailed in Table 7, Section III.1.1 above. 
And even though the most common suggestion was that innovation should provide farmers with the 
inputs to solve the problems in their farms rather than just identify their location, farming knowledge 
played an important role in giving farmers access to farming inputs. In Chokwé, for instance, this 
GRAPH 31. CHANGES IN YIELDS COMPARED TO TYPE OF INFORMATION 
THAT FARMER RECALLED RECEIVING FROM DRONE OPERATOR 
CHANGES IN YIELDS COMPARED TO TYPE OF 
INFORMATION THAT FARMER RECALLED RECEIVING 
FROM DRONE OPERATOR 
n=62
0
10%
20%
30%
40%
50%
60%
70%
80%
90%
Problem location Advice on
farming pactices
Both
30%
55%
15%
85%
13%
46%
23%
31%
FARMERS WHO RECEIVED THAT INFORMATION
Yields increased Yields decreased Yields suffered no change
48 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
relation was very clear and led to positive results for satisfied and enthusiastic farmers. Drone 
operators in this region, when advising farmers’ on farming practices, gave them suggestions on how 
to improve soil quality through techniques that are cheaper and easier to access then commercial 
fertilizers, bringing to light the important relation between knowledge of farming techniques, using 
resources efficiently and having access to farming inputs. The following quotes, from 3 different 
farmers in the surroundings of Chokwé, all benefited from learning about how to use straw, weed and 
manure as fertilizers in their farms: 
“Operator told me to keep weeding the fields and cleaning the channels to 
find out where the water was coming through. She confirmed that what I 
had planted was good and that the soil had good quality, but also explained 
me that weeds could be used to fertilize the soil for better rice production. I 
used to burn weeds before. Now I produce more rice.”
__________________
“We produced more because operator came and explained the spacing in 
between crops (maize, cabbage and green pepper). She told us that for soil 
to be fertile we should cover it with straw. I saw productivity increase.”
__________________
“The operator told me to keep weeding. He told me that my crops were good 
and that I could use manure in my fields instead of fertilizer, so I decided 
to try it. I had done it years before but I had seen everybody using the 
commercial fertilizer so I had switched to fertilizer. After speaking to drone 
operator I decided to try to use manure together with fertilizer on my 
rice plantation. And yes, it improved quality of the crops.”
If providing farming advice to farmers was not the original intent and is not the future plan of ThirdEye, 
it would probably make the service more effective if it is implemented in regions where farmers 
have good knowledge of farming techniques or are being advised by local services, like the SDAE in 
Mozambique. 
Finally, if the original purpose of the service was not to provide farmers with advice on farming 
practices, but ended up expanding to include this, it is also worth questioning if drone operators 
had the adequate training to provide farmers with this type of service (and even if they were being 
rewarded by the extra work delivered). 
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 49
1.2. Water benefits
When it comes to water benefits, even though it was not 
possible to entirely measure water flows and quantify usage 
in the locations evaluated, there are different ways in which 
innovation could have affected water efficiency in the region, 
depending on the kind of information that the drone operator 
provided to farmers. 
Informing farmers about the location of problems in their 
farms (Table 3 above) could have had an indirect impact on 
water usage, as explained by farmers and detailed in Section 
III.2.2 above. Specifically, drone operators told farmers 
where channels were clogged and encouraged them to keep 
the channels surrounding their farms clean, which could 
have impacted water drainage and flow in these areas. In 
the location called D5A in Chokwé, images provided by the 
innovation were used to support the local farmers’ association 
request to have their fields levelled, which also has an impact 
on how water is used.
Advising farmers on better farming techniques, as detailed in 
Section III.1 above (Table 4), allowed farmers to make better 
use of water resources. Some of the advice offered focused 
on water use specifically (explaining how and when to irrigate) 
but the fact that farmers improved their farming techniques in 
general (sowing, crop spacing, use of fertilizers and pesticides, 
when to plant, etc.) can also have had an indirect positive 
impact on water usage. One farmers’ comment makes this 
relation very clear:
PHOTO 9. Farmers in Xai-Xai cleaning 
the channel close to their farm.
“After I started using fertilizers (as suggested by the drone operator), I use 
less water on my plants. Before I thought that they were looking weak and 
I thought it was because they needed more water, now they are strong so I 
don’t water them that much.”
50 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
2. USAGE/AVAILABILITY 
2.1. Usage of innovation
Only 3% (2 out of 62) of the farmers said they had problems understanding the service. These were 
two female farmers who said they were not able to understand the images the drone operators 
showed them. From the 97% who did not declare to have any problems in understanding the 
innovation, 11% (7 out of 62) commented that the drone operators were able to explain very well the 
information they were presenting. 5 out of these 7 farmers were women and 2 were men. 
2.2. Decision to start using innovation
When it comes to farmers’ usage of the innovation, it is important to clarify that it was not decided by 
the the farmer individually to use the innovation, it was a decision made by farmers’ associations (in 
most of the regions). In other places, like in D11 (in the surroundings of Chokwé), some farmers were 
not aware of why the service began to be offered there. 
As summarized in Graph 32 below, 59% (34 out of 58) of farmers first heard about the innovation 
because the drone operator came speak to them, 36% (21 out of 58) because they went to a meeting 
in their farmers association where the innovation was presented and explained to them, 3% (2 out 
of 58) first heard about the innovation from other farmers and 2% (1 out of 58) heard about the 
innovation on the news (radio). 
GRAPH 32. WAYS IN WHICH FARMERS FIRST HEARD ABOUT THE INNOVATION 
WAYS IN WHICH FARMERS FIRST HEARD 
ABOUT THE INNOVATION 
n=58
36% Meeting in association
3% Heard from other farmers
2% Heard about it on the news
59% Operator came and explained
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 51
2.3. Frequency and timing of use 
Regarding frequency of use of innovation (i.e., deciding when to obtain drone information), this was not a 
users’ choice either. It depended on the drone operator coming to farms and presenting the information 
to farmers (which also depended on farmers being present on that day), which was done according 
to the operators’ working schedule. From what two operators explained, operators’ working schedule 
and farm visits were not necessarily decided together with farmers or previously informed to them. This 
could have had an impact on issues related to both (i) the frequency in which farmers were offered 
information about their farms and (ii) the relevance of the moment this information was provided. 
As detailed in Section II.2 above, if drone operators in Xai-Xai, for instance, visited all of the “active 
ThirdEye users” in the region as identified by the innovator, it would take around 8 months for a farmer 
to receive a drone operator in his farm. If by any chance this farmer was absent on the day of the 
operator’s visit, it would take even longer for the farmer to receive information from the drone operator. 
Also, even if a farmer is visited a few times during the year, further consideration should be taken on 
the possibility of synchronizing visits with crucial moments in the farming cycle. One association leader 
pointed out that (even though he was satisfied with the service in general) there are specific moments 
during the year that information on soil quality and crop stress is more crucial than in other moments, 
such as just before the harvest or when farmers are preparing the soil to sow. 
This is very important in terms of effectivity of the service. The main purpose of the innovation was to 
provide spatial information to farmers allowing them to see where crop stress is happening before 
it would be visible to the human eye (which would be 2 weeks according to innovator’s website) 
(ThirdEye, n.d.) or, at least, in an adequate time frame to allow them to make decisions concerning 
their resources. This would allow farmers to “make decisions based on facts” and “see when and 
where they should apply their limited resources” (ThirdEye,n.d.). If farms are only being visited around 
once or twice per year, it is questionable to what extent the information provided by the innovation 
was given as early as possible so as to to allow farmers to anticipate their decisions, fulfilling the main 
benefit promised by the innovator. 
In some cases, however, even if problems were spotted in advance by the innovation, this would not 
automatically translate into a concrete benefit to farmers for two main reasons: some farmers could 
not afford the necessary solutions to fix their problems and improve their yields, or farmers were not well 
informed of farming practices and techniques that would have allowed them to solve their problems. 
52 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
3. INNOVATION AFFECTED FARM SIZE AND GENERAL BENEFITS 
If innovation is not providing information before farmers can spot problems with their own eyes, it 
could still be useful by bringing information about areas that farmers cannot reach or are too far. 
However, the average size of farm area affected by the innovation is of 0.8 hectares (excluding the 2 
larger farmers, who own 27 and 15 hectares affected by innovation, each). This means that most of 
the farmers can easily walk around their farms and spot main issues when they are already visible. 
In fact, data shows that farmers owning smaller farms were the ones that less perceived direct 
benefits from the innovation when they were provided with only information about where problems 
were located in their farms, as presented in Graph 33 below. 
56% (10 out of 18) of farmers owning farms with an area equal or smaller to 1 hectare perceived 
direct benefits from innovation, while 75% (3 out of 4) of farmers owning farms between 1 hectare 
and 5 hectares perceived benefits. Farmers owning farms with an area of 5 hectares or more did 
not mention receiving only this type of information, so their perception of benefits from this type of 
information could not be assessed. 
Farmers with larger farms also perceived more benefits than smaller farmers when they received 
advice on farming practices and techniques: 87% (13 out of 15) of farmers owning 1 hectare or less 
found direct benefits when the service provided them with this type of information, compared to 100% 
(3 out of 3) of the farmers who own farms with areas between 1 and 5 hectares. Farmers owning 
farms with an area of 5 hectares or more did not mention receiving only this type of information, so 
their perception of benefits from this type of information could not be assessed. 
GRAPH 33. FARMERS’ PERCEPTION OF BENEFITS PER FARM SIZE (AFFECTED BY THE 
INNOVATION) AND TYPE OF INFORMATION RECEIVED FROM DRONE OPERATOR 
FARMERS’ PERCEPTION OF BENEFITS PER FARM SIZE 
(AFFECTED BY THE INNOVATION) AND TYPE OF 
INFORMATION RECEIVED FROM DRONE OPERATOR 
n=55
44%
≤ 1 ha
0
20%
40%
60%
80%
100% 25%
> 1 ha and
< 5 ha
12%
≤ 1 ha
100%
> 1 ha and
< 5 ha
12%
≤ 1 ha
33%
> 1 ha and
< 5 ha
100%
≥ 5 ha
PERCENTAGE OF FARMER IN EACH CATEGORY
Did not feel direct
benefits from innovaton
Felt the innocation
was directly benefictial
PROBLEM
LOCATION
ADVICE ON 
FARMING PRACTICES BOTH
56%
75%
87% 88%
67%
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 53
Farmers with farms with an area of 5 hectares or more were the ones who felt more direct benefits 
from receiving both types of information (problem location and advice on farming practices) 
combined: 100% (2 out of 2) of them, compared to 88% (7 out of 8) of the farmers owning 1 hectare or 
less and 67% (2 out of 3) of the farmers owning between 1 and 5 hectares. 
4. CHANGES IN INCOME 
Even though there was a slight increase in the number of farmers selling their yields after the innovation 
was active and an increase of 53% of the average revenue obtained by these farmers, as detailed 
in Section III.4 above, there are other factors, besides the innovation, that had an impact on income 
changes experienced by farmers, such as price fluctuations, access to markets, timing of harvest, etc. 
One of the main reasons for farmers being able to sell more of their produce was an increase in yields. 
But, if we look solely into increase in yields, for instance, only 7 out of the 14 farmers who had increases 
in income made an explicit connection between their increase in yields and the use of the innovation. 
It is also important to consider that many farmers were advised by the drone operators on farming 
practices, such as how to use fertilizers or pesticides, which could probably have had an impact on 
how much they spend with farming inputs, affecting farming incomes. This change in investment on 
farming inputs was not included in the scope of the survey. But as discussed in Section IV.1.1 above, 
farmers that received advice from drone operators on how to use and have access to cheap/non￾commercial forms of fertilizers not only were able to solve their issues, but were able to save on other 
inputs (such as water) and had a very positive attitude towards the innovation. 
5. IMPACT ON POVERTY 
As presented in Section III.5 above, the innovation had small impact on poverty alleviation since the 
number of poorest farmers after the innovation was introduced continued the same, even though 
some farmers improved their incomes. In fact, data shows that after innovation was active, the 
number of wealthier farmers slightly increased but the overall number of farmers in the lower income 
groups (Groups C and D) remained the same. On the other hand, the average earnings of farmers 
who were selling their yields increased, which can also be seen as beneficial. 
This is in line with the fact that less farmers among the poorest felt the innovation brought direct 
benefits to them, while more farmers from the higher income groups felt direct benefits. It is 
interesting however, that more farmers from the lower income groups (Group C and D) were more 
interested when asked if the service should continue. It was not possible to evaluate all the reasons 
behind this trend, but one reason could be, as explained by one farmer in Group D, that he is “so poor 
that any help or service is welcome”. Another farmer from Group D, when asked if he wanted the 
innovation to continue even without producing any direct benefits to him explained that he would be 
interested if in the future the innovation could help him. Also, a wealthy farmer from Group A said that 
the innovation was beneficial to him (he learned how to solve the issue with his beans from drone 
operator) but now he has no other problems, so he does not need the innovation anymore. 
54 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
6. GENDER DIFFERENCES 
As detailed in Section II above, women are the majority of farmers both in Mozambique and in the 
sample as small-scale agriculture has become a gendered activity where women are seen as the 
main responsible for farming (even though they not always have final decision over financial gains, 
as noted by Oliveira, 2016). Female farmers interviewed are are poorer (Graph 24 above) and own 
smaller farms (Graph 3 above) than the interviewed male farmers. 
Even though men had higher average yield increases and overall net changes in yields, which is line 
with the national tendency of female small-scale farmers being less productive than men due to 
inequalities in education and access to farming inputs (Ministério do Género Criança e Acção Social 
de Moçambique, 2016) a higher proportion of women than men saw their yields increase while the 
innovation was active in Mozambique. 
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 55
However, when asked if the service should continue active, less women responded positively, when 
compared to men (see Section IV.7 below). It is not clear what could be the exact reasons for this, 
especially when we see that, as detailed in Section III above, the same proportion of men and women 
perceived direct benefits from innovation. 
However, more women felt the innovation was beneficial when they received both types of 
information (location of problems and advice on farming practices). It was not the scope of this survey 
to evaluate gender disparities in knowledge of farming practices and techniques, but further research 
on this could help better understand how effective the innovation could be to women depending on 
their previous knowledge or how to tailor it specifically for female farmers’ needs. 
Also, as previously described, a few women also stated that the innovation brought them more 
motivation to continue farming (since someone was “checking” or “helping” them), which is an indirect 
benefit that could also be better researched to bring more benefits to women. For instance, one 
question that was not asked in this survey is if the farmer works alone (many women were widows) or 
with spouse/husband and how does this affect their will to farm. 
7. AFFORDABILITY OF THE INNOVATION
Because of limitations of time, the affordability of the innovation was not thoroughly assessed. But, 
when answering that they would like the service to continue, 29% (12 out of 41) of these farmers 
immediately continued the answer by saying that they cannot afford the service, even before a 
hypothetical price was mentioned. 
In fact, 15% of the entire sample of farmers (9 out of 62) do not invest any money in farming inputs. 
They use seeds they stored from previous seasons and do not apply commercial fertilizers or 
pesticides. In Xai-Xai, specifically, farmers used to receive seeds for free as part of a government 
subsidy programme. Having to store or buy seeds now has put an extra pressure on farmers in this 
region. The leader of the farmers’ association in Xai-Xai informed us that they were discussing with 
the board of the association if they should include the service in the fee that they are planning to start 
charging farmers in this area. 
However, as detailed in Section III.6 above, many farmers had a positive attitude towards the 
innovation and would like it to continue active. 
56 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
8. BENEFITS FOR LEADERS OF FARMERS’ ASSOCIATION 
As mentioned in sections above, leaders of farmers associations benefited from the innovation in 
different ways. 3 leaders were interviewed: the leader from the Nhampondzoene Association in 
Xai-Xai, and from the D5B and D5A locations in the surroundings of Chokwè. All of the 3 leaders 
interviewed stated that besides being beneficial to them as farmers, the innovation was useful to their 
work as leaders of farmers associations, as summarized in Table 10 below.
TABLE 10. BENEFITS PERCEIVED BY LEADERS OF FARMERS ASSOCIATIONS 
Benefits from the service Possible Indirect/collective benefit
Number of leaders 
that mentioned it
Allows leaders to have an 
overview of the farming 
area and where problems 
are located
Allowed leaders to speak to farmers and 
try to help them solve issues or encourage 
them to work more
3 Leaders
Produced images of the 
farming area
Leaders of associations could use images to 
confirm their observations or have evidence 
to convince farmers to improve their work 
3 Leaders
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 57
For instance, the leader of association in D5B, (surroundings of Chokwè), explained that the innovation 
allows her to know which fields are facing problems and get in contact with these farmers to try to 
solve their issues: 
“As a leader, the innovation helps me to know which fields 
in this association are problematic. So I go and speak to farmers 
to tell them what I saw in the images and I tell them where 
to find pesticides for them to improve their work.”
 The leader of the association in D5A (surroundings of Chokwè) used the images provided by the 
innovation to support his demand to local authorities that fields in their region had to be levelled, 
besides showing where issues are located: 
“As leader of the association, the innovation helped us to see where 
problems were located in peoples’ farms, where the soil needed 
fertilizer, for example, or where there was too much salinity. It also 
confirmed where the soil was not levelled and we were able to take 
the images to the authorities to request the levelling. When soils are 
not levelled we produce less, water does not flow correctly, we use the 
incorrect amount of water, which causes hydric stress.”
Despite the positive uptake of the innovation among the interviewed leaders, it is also important to 
mention that while walking around the locations where the innovation was supposed to be active, we 
met the leader of Armalug, in Macarretane (surroundings of Chokwè), who had spoken to the drone 
operator at least once and seen the drone fly over his farm. However, he told us that “there was no 
need for new technology to identify where problems are if they won’t explain them what the problem 
is and how to solve it”. He was very negative about the service and did not want to speak in details 
about it stating that he had not used it. 
58 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
FutureWater’s ThirdEye was a SWFF-supported infrared flying sensors project that intended to help 
farmers make better decisions concerning the use of their limited resources, such as water, seeds 
and fertilizers, by providing them with timely information about where issues were happening in their 
farms. This report analysed the results obtained by the monitoring and evaluation field intern who 
conducted an evaluation survey in July and August 2018 in Mozambique, after the project had been 
active there for 3 years. 
Most of the farmers interviewed are small-scale (owning up to 1 hectare of land) female farmers that 
depend on rain-fed and flooding irrigation techniques. The service had an impact over water usage, 
crops, yields and farmers’ income through information provided by drone operators, which were of 
two types: (i) problem location, meaning they they were informed of where a certain problem was 
occuring in their farms (crop stress, soil salinity, flooding, clogged water channels) and (ii) advice on 
farming practices: they were advised on farming techniques and skills, either confirming or improving 
their knowledge of farming. 40% of the farmers (N=55) received the first type of information, 36% of 
the farmers received the second type and 24% received both types of information. 
77% of the respondents (N=60) felt that there was some kind of (direct/indirect) benefit from the 
information they received while using the service and all leaders of association thought that the 
innovation made their work easier for different reasons. Even though it was not possible to quantify 
changes in water usage, the innovation is seen as having a positive indirect impact over water 
efficiency in some areas by serving as encouragement for farmers to clean water channels or by 
providing the necessary justification to have fields leveled. As the innovation also provided advice on 
farming practices it can also indirectly have led to better use of water and other resources in farming. 
When it comes to benefits to crops, even though 60% of farmers increased their yields over the period 
examined, other factors besides the innovation were identified by farmers as also having an impact 
over production. 
When it comes to farmers’ perceived benefits from innovation, the type of information deemed as 
most beneficial to farmers was not the main scope of the innovation (identifying in advance where 
problems were occuring), but rather advice on farming practices. 56% of respondents (N=34) said 
that the service would be more effective if it not only identified where problems were located in the 
farms but also provided means to solve these problems, mostly fertilizers and pesticides. The second 
most common suggestion was that the innovation should provide farmers with more advice on 
farming practices.
VI. CONCLUSION
SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018 59
This report also discussed to what extent the innovation’s main purpose (to inform farmers in advance 
about the location of problems in their farms) was actually occurring considering drone operators’ 
working schedule and the total number of users, and how beneficial can the innovation be to farmers 
who own, in average, not more than 1 hectare of land and cannot afford much farming inputs. In fact, 
data shows that farmers who owned smaller farms or that were classified in the poorest income 
groups were the ones that less perceived benefits from innovation. And data also showed that 
innovation had very little impact on poverty reduction when looking at the entire sample. 
When asked if they would like the service to continue, 66% (N= 62) of the farmers said yes, while the 
rest was not sure or not interested in continuing with the service. 
60 SECURING WATER FOR FOOD IGNITIA IMPACT EVALUATION | SEPTEMBER 2018
Instituto Nacional de Estatística de Moçambique. (2017). Mulheres e Homens em Moçambique 
2016. Retrieved on December 23, 2018 from http://www.ine.gov.mz/estatisticas/publicacoes/
mulheres-e-homens/mulheres-e-homens-em-mocambique-2017/at_download/file 
FAO. (2018). Mozambique at a glance. Retrieved on December 23, 2018 from http://www.fao.org/
mozambique/fao-in-mozambique/mozambique-at-a-glance/en/ 
Magin, P. (2015). Rule of Law for Whom? Questioning the Beneficiaries of Mozambican Land and 
Resource Rights. (Master’s Thesis), Lund University, Retrieved from http://lup.lub.lu.se/luur/
download?func=downloadFile&recordOId=5463382&fileOId=5463415 
Ministério do Género Criança e Acção Social de Moçambique (Ministry of Gender, Infancy and 
Social Action of Mozambique). (2016). Perfil de Género de Moçambique. Maputo, Moçambique. 
Retrieved from: http://www.mgcas.gov.mz/st/FileControl/Site/Doc/4021perfil_de_genero_de_
mocambique.pdf
Oliveira, P. (2016). Agricultura familiar, cultura e economia em Moçambique. Cadernos CERU, 27(2), 
156-170. Retrieved from http://www.revistas.usp.br/ceru/article/view/125090/122144 
ThirdEye. (n.d.). ThirdEye: Flying Sensors to Support Farmers’ Decision Making. Retrieved on December 
23, 2018 from https://www.futurewater.eu/projects/third-eye/ 
USAID. (2018). Agriculture and Food Security. Retrieved on December 23, 2018 from https://www.
usaid.gov/mozambique/agriculture-and-food-security 
World Bank. (2011). Climate Risk and Adaptation Country Profile - Vulnerability, Risk Reduction, and 
Adaptation to Climate Change in Mozambique. Washington DC, USA. Retrieved from: http://
sdwebx.worldbank.org/climateportal/countryprofile/doc/GFDRRCountryProfiles/wb_gfdrr_
climate_change_country_profile_for_MOZ.pdf 
World Bank. (2018). Shared Prosperity 2018 - Piecing Together the Poverty Puzzle. 
Washington DC, USA. Retrieved from: https://openknowledge.worldbank.org/bitstream/
handle/10986/30418/9781464813306.pdf 
VII. REFERENCES

Securing Water for Food has sourced and invested in a portfolio of innovative 
solutions that aim to help farmers use water more efficiently and effectively, 
improve water storage for lean times, and remove salt from water to make more 
food. Our cohort of innovators are helping people in 35 low-resource countries 
with tools they need to produce more food with less water.
To learn more about Securing Water for Food, 
visit www.securingwaterforfood.org.