Recent development of irrigation scheduling technologies and ICT platforms have shown potential in providing farmers with sufficient information to improve irrigation decisions. However, for small-scale farmers in developing countries, access to these options remains challenging due to insufficient network facilities (e.g. ICT platforms) or the local availability of technologies. Developing local information networks around irrigation technologies in water user groups (WUG) has the potential to provide an option to mutually improve on-farm water management and water user group performance in irrigation schemes. The study explored whether farmers who had access to information would obtain similar agricultural and water productivity results as their peers who had access to a technology within the same group. Furthermore, the study aimed at evaluating whether the water user groups who had developed an information sharing platform would outperform the control group. Ninety WUGs allocated in six irrigation blocks were randomly assigned into three groups: i) control (36 WUGs), Wetting front detector (WFD) based network (36 WUGs) and chameleon sensor based network (18 WUGs) covering a total of 990 wheat producing farmers. In technology based networks four technologies were distributed randomly to farmers who provided irrigation information to the other farmers growing the same crop within the same WUG. The information shared included time to irrigate one furrow and time to irrigate the total area of the field. Preliminary results showed that the irrigation depth applied in fields where farmers received the information was similar compared to those who used the tools in their fields. The WUGs, who had established information networks around the irrigation tools, used significantly lower irrigation amounts compared to the control groups. The impact on wheat yield and subsequently water productivity on-farm was influenced by the heterogeneity in farm management (i.e. nitrogen applied, irrigation experience) and water allocation to various WUGs (i.e. location of the WUG in the scheme). Depending on water allocation to the WUGs, the increases in water productivity could be classified into two groups: 1) reduction of irrigation without significant increments in agricultural productivity (nitrogen limiting) or 2) reduction of irrigation with significant increments in agricultural productivity (no nitrogen limitation). Whilst the project is validating its findings in a second irrigation season, preliminary results suggest that building local information networks around low-cost irrigation scheduling technologies could leap-frog improving agricultural and water productivity in schemes without the need for upscaling technologies to each and every farm.

1. Improving water productivity in water user
groups through on-farm irrigation scheduling
tools and local information networks
Petra Schmitter, Desalegn Tegegne, Seifu A. Tilahun,
Lisa-Maria Rebelo
International Water Management Institute
Contract: P.schmitter@cgiar.org

2. • Abundance of tools available (ICT, field based) to guide irrigation
scheduling, frequently driven by scientific community
• Few tools provide “easy” information for smallholder farmers
• Adoption remains low (awareness, access, affordability)
• Participtory irrigation management – visous cycle: Efficient use
on-farm does not necessarily translate in more efficient use at water
user group or scheme level
Improving on-farm water management in
schemes
Could local information platforms established around easy low
cost tools help improve water productivity on-farm and in water
user groups?

3. Two tools selected
Wetting front detector
• Mechanical
• In field
• Not web-based
• How much irrigated
Chameleon sensor
• Electrical
• In field
• Web-based
• When to irrigate
• How much irrigated
More information about the tools (CSIRO)
https://via.farm/

4. Irrigation season – over-irrigation on-farm and poor rotation
 Lack of knowledge of how much to irrigate and when
 Low yields, low water productivity
 Water conflicts between irrigators
 Study across the scheme (head to tail)
Irrigation scheme for smallholder farmers
• 12 irrigation blocks, 7000 ha (dry season: Nov-May)
• 10,000 beneficiaries
• WUA established to improve water allocation and
rotation
Koga irrigation scheme

5. Establishing local information platforms
Self-selection of
“Technology farmers”
who will share
information in WUG
Information receivers
within the WUG
Improving water
management on-farm
and within the water
user group
54 WUG (36 WFD, 18 CS)
602 farmers
240 ha
Control group 36 WUG: 388 farmers 139 ha
(no tools, no information)
203 farmers
86 ha
399 farmers
154 ha

6. Reducing amount of water irrigated in wheat
Proportional Cumulative
Frequency with number of
observations: Control
(n=387), WFD (n=137),
WFD-info (n=255),
Chameleon (n=66),
Chameleon-info (n=145).
Blue stripped lines= 0.1
and 0.9 reference line,
respectively; Red striped
line = 0.5 reference line
• Access to information
reduced irrigation
similarly as access to
the technology:
• WFD-WUG: 11 %
• Chameleon-WUG: 21%

7. Response to wheat yield shows interaction
Proportional Cumulative
Frequency with number of
observations: Control
(n=387), WFD (n=137),
WFD-info (n=255),
Chameleon (n=66),
Chameleon-info (n=145).
Blue stripped lines= 0.1
and 0.9 reference line,
respectively; Red striped
line = 0.5 reference line
• Differences between
treatments most
pronounced for yields
below 3.5 t ha-1
• Impact on yield increase
influenced by N-applied
and number of irrigation
events

8. Increasing water productivity at farm level...
Proportional Cumulative
Frequency with number of
observations: Control
(n=387), WFD (n=137),
WFD-info (n=255),
Chameleon (n=66),
Chameleon-info (n=145).
Blue stripped lines= 0.1
and 0.9 reference line,
respectively; Red striped
line = 0.5 reference line
Increase depends on:
• Interaction between the
technology installed and
information received
• Interaction between the field
size and the technology used
• Interaction between irrigation
depth applied and number of
irrigation events
• Interaction between nitrogen
applied and access to
irrigation information

9. Access to information can be as transformative as technologies
CONTROL TECHNOLOGY INFORMATION
Irrigation labor (person-days/ha) 13 11 11
Irrigation depth (mm) 576 461 494
Yield (t/ha) 2.8 3.4 3.2
Water productivity (kg/m3) 0.48 0.73 0.61

10. • Information providers: trust
in the technology, capability
to use the technology,
presence of information
receivers
• Information receivers: trust
in the information provider,
strength of the information
chain
Sharing and receiving of information
0%
20%
40%
60%
80%
100%
Provider Receiver Provider Receiver
WFD Chameleon
Percentageofrespondents
Yes No

11. WFD Chameleon
How do you rate the use of the technology?
Very difficult 0% 6%
Difficult 5% 32%
Not bad 21% 31%
Easy 38% 23%
Very easy 36% 9%
Were there times that you wanted to irrigate based on the technology
but you couldn’t due to water access?
Yes 82% 86%
No 18% 14%
Were there times that you couldn’t follow the duration of irrigation
based on the technology due to water restrictions in your water user
group?
Yes 62% 58%
No 38% 42%
Farmer perception – Technology users

12. WFD Chameleon
How do you rate the use of the information?
Very difficult 0% 0%
Difficult 0% 0%
Not bad 20% 43%
Easy 39% 50%
Very easy 41% 7%
Were there times that you wanted to irrigate based information
received but you couldn’t due to water access?
Yes 93% 60%
No 7% 40%
Were there times that you couldn’t follow the duration of irrigation
based on the information received due to water restrictions in
your water user group?
Yes 73% 55%
No 27% 45%
Farmer perception – Information users

13. Information type
WFD Chameleon
Provider Receiver Provider Receiver
Do you think, you obtained a higher
yield this year compared to
previous years?
Yes 88% 67% 89% 78%
No 12% 33% 11% 22%
How do you rate the “usefulness”
of the WUG –information platform in
relation to yield and water
consumption?
Very useful 77% 50% 42% 47%
Useful 18% 32% 52% 31%
Not useful 5% 18% 2% 22%
Bad 0% 0% 4% 0%
Perception of WUG on information platform

14. Opportunities and challenges...
Opportunities ….
• Less internal conflicts and better allocation within the WUG: Establishing local
information sharing networks provided support to both farmers and water user groups:
strengthening of governance
• Information is easy and digestible: Farmers who “trusted” the information reported that the
information was easy to use and apply.
Challenges …
• Breaking the information chain: Transferring information is challenging if irrigators change
throughout the season: rented labor or children.
• Ensuring inclusivity and avoid power struggles: Tendency to supply technologies to
“model” farmers who are more experienced and have better access to resources and
information. Elite capture - ensuring inclusivity and avoiding creating additional power
struggles when establishing information networks need to be addressed.

15. Thank You