Reducing rural poverty and improving household nutrition are common goals across all developing countries in the
Asia and Pacific region. To this end, the region has experienced a recent resurgence in large investments in irrigation
infrastructure. This surge in funding flows has created pressure from donors and central financing agencies, both of
which are increasingly demanding more robust justification for the investments. To date, providing this justification for
irrigation investments has been challenging due to a lack of reliable longitudinal data that measure the performance of
irrigated agriculture and associated water delivery services. Consequently, there is very little information on the real
returns on investments already made. Historic data has tended to be project based, point-in-time data constrained to a
defined area of infrastructure investment, not on-going and geographically broad-based.
Irrigation benchmarking is a process of comparative analysis of irrigation performance that enables scheme managers
to understand the performance of their irrigation services (International Water Management Institute, 2019). To better
understand the process of monitoring irrigation performance, this brief will use Cambodia as an illustrative example.
Irrigated rice production in Cambodia has significant potential, yet performance of the sector lags behind surrounding
countries, such as Viet Nam’s delta region (Mainuddin and Kirby, 2009). In addition, there are limited available and
published data in Cambodia, making it difficult to analyse the current and changing state of irrigation in the country,
the productivity levels, or irrigation’s contribution to poverty alleviation and economic growth (Tucker et al., 2020). For
these reasons, Cambodia was selected as a country to pilot the transfer of key learnings from the Australian experience
of irrigation performance benchmarking, and to develop a benchmarking methodology as a first step to undertake
ongoing performance assessment of irrigation schemes for strategic investments in increasing water productivity.
2. 2 waterpartnership.org.au
Project Objective – Develop an irrigation performance
assessment framework
Collect scheme and
farm level data for
performance analysis
Prioritise schemes for
capital investment
renewal
Monitor Operations and
maintenance
performance
Measure success of
investments made
Irrigation
Performance
Assessment
Framework
3. 3 waterpartnership.org.au
Key Criteria for an Irrigation Performance Assessment
Framework
•Suitable for application in developing
countries with no prior experience
Simple
•Low set-up and operating costs, not reliant
on expensive external resources
Affordable
•Robust approach that can be applied across
time and differing agro-ecologies
Reliable
•The performance measures and the
approach taken are locally relevant
Local
•The framework is able to deliver
meaningful insights from local to national
scales
Scalable
4. 4 waterpartnership.org.au
METHODOLOGY
1. Determine the key questions that need answering
2. Determine the performance indicators for the key questions
3. Develop data collection techniques
4. Collect and analyse data
5. Produce a draft irrigation performance assessment report
6. 6 waterpartnership.org.au
Key questions => Performance Indicators - Method
Key questions Indicator Method
Questionnaire Remote sensing
1.
How well does an irrigation
scheme deliver and
drain water?
Overall consumed ratio X
Delivery performance ratio X
Water level ratio X
Drainage X X
2.
How productive is an irrigation
scheme?
Cropping intensity X X
Land occupation X X
Crop yield X X
3.
How well is an irrigation scheme
managed?
Income per unit area X
Sustainability of irrigable area X X
Infrastructure effectiveness X X
Fee collection ratio X
Farmer water user
group function
X
7. 7 waterpartnership.org.au
1. Survey questionnaire:
a) Farmers
b) Farmer water user groups
c) Government staff – water managers, agricultural extension
2. Remote sensing:
a) Total surface water area
b) Total cropped area in different seasons
c) Total irrigable area managed
Two data collection methods selected
8. 8 waterpartnership.org.au
1. Survey questionnaire:
• Provides detailed information on all performance indicators
and WHY things happen, BUT:
• Can only cover a small portion of the total area
• Slow & costly
2. Remote sensing:
• Covers whole area and is low cost, BUT:
• Cannot provide all the performance indicators
• Does not explain WHY things happen
By combining questionnaire and remote sensing techniques we
understand both WHAT happened and WHY it happened.
Why have two data collection methods?
9. 9 waterpartnership.org.au
Short (only 9 questions), targeted to the 12 performance indicators:
1. What type, area yield of crops did you grow in each season?
2. Did the irrigation system supply enough water for you to grow and finish
you crops?
3. Did you have to pump irrigation water?
4. Did you use any water (groundwater or surface) other than from canals?
5. How much irrigation service fee did you pay in the last 12 months?
Farmer questionnaire
10. 10 waterpartnership.org.au
6. How well is the irrigation scheme being maintained?
7. How would you rate the ability of irrigation water delivery system to
supply your needs?
8. In your opinion what are the main issues with the current state of the
irrigation network?
9. Was there an improvement in the irrigation service in the last 12 months
compared to previous years?
This questionnaire took 15 – 30 minutes (our target rate was 20min)
Farmer questionnaire cont.
11. 11 waterpartnership.org.au
Remote Sensing Methodology
Ground-
Referenced
Data
Wet Season
Imagery
Command
Area
Utilisation
Rice
Production
Drainage
Categorised
NDDI Imagery
Water Area
Scheme Area
Rice Area
Scheme Area
Rice Area
Command Area
Dry Season
Imagery
Data Inputs Data Training Functions Performance Indicators
1
2
3
2 minutes per scheme/season/year
US$0.05 per ha
12. 12 waterpartnership.org.au
Taing Krasaing Irrigation Scheme
• The scheme was broken into three canal commands for analysis
• Chroab
• Kokoah
• Taing Krasaing Main Canal (TKMC)
• Approximately 25% of farmers were surveyed.
13. 13 waterpartnership.org.au
Productivity 1. Rice Yields - Questionnaire
• Dry Season = 3.1 T/ha
• Wet Season = 1 T/ha
Subproject Dry Season Rice Wet Season Rice
Chroab 80 ha (10%) 610 ha (70%)
Kokoah 690 ha (33%) 980 ha (47%)
TKMC 70 ha (5%) 540 (38%)
Kokoah
Chroab
TKMC
Kokoah
Chroab
TKMC
Subproject Dry Season Rice Wet Season Rice
Chroab 250 T 610 T
Kokoah 2140 T 980 T
TKMC 220 T 540 T
TOTAL 2610 T 2130 T
2. Rice Areas – Remote sensing
3. => Rice Production
14. 14 waterpartnership.org.au
Management
• 55-70% farmers thought
that the scheme had
improved in the last 12
months
• Fees for irrigation
services ranged from
US$4 – 11 per hectare
• Total annual fees paid
estimated at US$11,280
0
10
20
30
40
50
60
70
Good Medium Bad
%
of
Respondents
Chroab Kokoah Taing Krasaing
Farmer satisfaction with
scheme maintenance
15. 15 waterpartnership.org.au
Effects of Infrastructure Investment
• Kokoah canal
investments in 2017 and
2019 allowed for greater
dry season cultivation
• Irrigable area was
estimated to have
increased from < 5% to
69% by 2020
• Strong correlation
between remote sensing
analysis and data from
the questionnaires
Year Actual Canal
Length (Km)
Estimated
Irrigable Area
(Ha)
Area Irrigated
(Ha)
% of Irrigable
Area Cropped
2016 - - 34 -
2017 14.0 700 30 4%
2018 14.0 700 106 15%
2019 18.3 915 567 62%
2020 18.3 915 634 69%
1st Investment
2nd Investment
17. 17 waterpartnership.org.au
Scheme Level Comparisons
• Remote sensing methods were
easily up-scaled to additional
schemes at low marginal cost
• Scheme performance can be
compared between regions
and years
• Data provided insight into
trends of irrigation system
functionality.
• Data highlighted drought and
flood effects upon cropping
0
5
10
15
20
25
Taing
Krasaing
O Kra Nhak Prek Chik O Tracheak
Chit
%
Cropped
Dry
Season
Rice
2016 2017 2018 2019 2020
0
20
40
60
80
Taing
Krasaing
O Kra Nhak Prek Chik O Tracheak
Chit
%
Cropped
Wet
Season
Rice
2016 2017 2018 2019
19. 19 waterpartnership.org.au
Key Performance Indicators for successful framework
•Pilot field survey delivered by university
students with minimal training – significant
opportunity for improvement with minimal
additional investment. Remotes sensing used
public domain data and freely available software
Simple
•4,000 ha pilot field survey cost USD$2.57/ha
•11,500 ha remote sensing cost USD$0.05/ha
•In future, the cost per hectare can be reduced
Affordable
•Remote sensing and field surveys enabled cross-
checking, data cleansing and higher levels of insight.
Good response rates achieved. Some ambiguities in
questionnaire and not all data could be fully
explained using rapid survey
Reliable
?
?
20. 20 waterpartnership.org.au
•Project engaged local delivery partners,
adapted the approach on local advice and
facilitated knowledge transfer.
Local
•Both the rapid-interview survey and
remote sensing methods could be used at a
national level.
Scalable
Key Performance Indicators for successful framework