Presented by Abeyou Wale, Amy S Collick, David G Rossiter, Simon Langan and Tammo S. Steenhuis at the Nile Basin Development Challenge (NBDC) Science Workshop, Addis Ababa, Ethiopia, 9–10 July 2013

1. 1
Realistic Assessment of Irrigation
Potential in the Lake Tana Basin,
Ethiopia
Abeyou Wale
Amy S Collick,
David G Rossiter,
Simon Langan and
Tammo S. Steenhuis
Nile Basin Development Challenge (NBDC)
Science Workshop
Addis Ababa, Ethiopia
9 – 10 July 2013

2. Contents
1. Introduction
1.1. Study Area
1.2. Objectives
2. Method
3. Result
4. Conclusion and Recommendation
2

3. Introduction
3
 Ethiopia has a large potential of water and land resources that could
be easily developed for irrigation.
 12 major river basin, annual runoff volume of 122 bm3 of water.
 Water resources potential of Ethiopia is demonstrated by the
under utilized, from 3.7 m ha of irrigation potential
approximately 5 to 7% is only develop (Awulachew et al 2007).
 The government of Ethiopia is planning to solve this paradox through
agricultural led development program.
 The study area is considered as development corridor of the national
and regional government for 2011–2016 Plan for Accelerated and
Sustained Development to End Poverty (PASDEP).
 This study is aiming to give a close view of the surface irrigation
potential of Lake Tana Basin.

4. Introduction…
4
Study area
Objectives
The general objective of this research is to assess the surface irrigation
potential based on river discharge and land suitability in the Lake Tana Basin.
The specific objectives of this study are:
 Mapping of areas suitable for surface irrigation based on a GIS based multi-
criteria evaluation technique.
 Identifying medium and large-scale areas over 200 ha, those are suitable for
irrigations and areas that can be irrigated with the existing river discharges.
Area 15,000 km2, lake covers 20%
North-West highlands of Ethiopia.

5. Method
5
Factors affecting
surface irrigation:
Climate condition
River proximity
Topography (slope)
Market outlets (Roads and Urban proximity)
Soil type
Land cover

6. Method…
6
Suitability classes
 FAO (1976 and 1981) framework
Class S1
Highly
Suitable:
Land without significant limitations. This land is not perfect but
is the best that can be hoped for.
Class S2
Moderately
Suitable:
Land that is clearly suitable but which has limitations that either
reduce productivity or increase the inputs needed to sustain
productivity compared with those needed on S1 land
Class S3
Marginally
Suitable:
Land with limitations so severe that benefits are reduced and/or
the inputs needed to sustain production are increased so that
this cost is only marginally justified.
Class S4
Less
Suitable:
Land that cannot support the land use on a sustained basis, or
land on which benefits do not justify necessary inputs

7. Method…
7
 Mapping factors: Soil map
Soil groups
Suitability for Irrigation
FAO (2006)
Suitability
Eutric Leptosols Extremely gravelly and/or
stony
S4
Lithic Leptosols
Eutric Vertisols
Considerable agricultural
potential
S2
Haplic Alisols Poor natural soil fertility S3
Haplic Nitisols Very productive soils S1
EMWR
Highly suitable : 47.43%
Moderately suitable: 27.11%
Marginally suitable: 6.40%
Not suitable: 19.06%

8. Method…
8
 Mapping factors: Land use map
Land use Description Suitability
Dominantly cultivated Agricultural land S1
Moderately cultivated Agricultural land S1
Forest Natural Forest S4
Grassland Grass land S2
Plantations Artificial forest S4
Shrub land Dominated by shrubs S3
Highly suitable : 73.8%
Moderately suitable: 2.8%
Marginally suitable: 2.9%
Not suitable: 20.5%

9. Method…
9
 Market outlets
Urban proximity
50, 000 population (2007 Census of Ethiopia)
Euclidean distance
Equal ranging technique
Distance to town 0 to 84 km
Highly suitable : 0 to 21 km
Moderately suitable: 21 to 42 km
Marginally suitable: 42 to 63 km
Less suitable: 63 to 84 km
Town proximity

10. Method…
10
 Market outlets
Road proximity
Paved road
Euclidean distance
Equal ranging technique
Distance to road 0 to 62.5km
Highly suitable : 0 to 15km
Moderately suitable: 15 to 31km
Marginally suitable: 31 to 46km
Less suitable: 46 to 62.5km
Road proximity

11. Method…
11
 Slope
DEM SRTM 90m
Reclassified based on FAO slope class
FAO (1999)
http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp
% Slope
Class
Suitability
Class
< 2 S1
2 to 4 S2
4 to 8 S3
> 8 S4
DEM Slope

12. Method…
12
 River proximity
DEM SRTM 90m
Extracting major drainage networks
Euclidean distance
Equal ranging technique
Distance to road 0 to 27km
Highly suitable : 0 to 6.7km
Moderately suitable: 6.7 to 13.5km
Marginally suitable: 13.5 to 20.2km
Less suitable: 20.2 to 27km
Major
Perianal
rivers
River proximity map

13. Method…
13
Climate Condition (Rainfall deficit)
Aug
EToPpt
ET
ET
ET
ET
Rainfall deficit
(1992 to 2006)
8 Ppt stations
4 Eto stations
Annual rainfall
deficit -440 to -810
mm

14. Method…
14
 Weighting of factors
 Ranking technique: involves ordering of decision factors in their relative order of
importance.
 Pairwise comparison (Saaty 1977): each factor will be matched head-to-head (one-to-
one) and a comparison matrix is prepared to express the relative importance.
Importance Definition Explanation
1 Equal importance Two factors contribute equally to the objective
3 Somewhat more
important
Experience and judgement slightly favour one
over the other
5 Much more
important
Experience and judgement strongly favour one
over the other.
7 Very much more
important
Experience and judgement very strongly favour
one over the other. Its importance is
demonstrated in practice.
9. Absolutely more
important
The evidence favouring one over the other is of
the highest possible validity.
2,4,6,8 Intermediate values When compromise is needed

15. Method…
15
 Pairwise comparison (Saaty 1977):
Factors SO LU RiP UP RoP RD SL
Wt.
Pairwi
se
Wt.
Rankin
g
River Proximity
(RiP) 3 7 1 6 2 4 2 32 20
Road Proximity
(RoP) 2 6 1/2 5 1 2 2 22 18
Slope (SL) 3 5 1/2 4 1/2 3 1 19 17
Soil (SO) 1 4 1/3 4 1/2 2 1/3 12 15
 The rows indicate the strength of the factors
 Given a the factor (on the left) and another (on top) how much
strongly important is the first factor for surface irrigation area
suitability than the second?
To evaluate the credibility of the pairwise matrix consistency was
checked, the result indicated the judgment to be trustworthy

16. Result
16
 Preliminary Suitability Map
Weights are distributed to four classes of suitability by equal
interval ranging technique:
Ranking Pairwise
𝑆 = 𝑓𝑖 𝑤𝑖
𝑛
𝑖=1
Constraint map
Ranking Pairwise

17. Result…
17
Ranking
Pairwise
 Optimal sights: Preliminary Suit. > 85
 Majority pixel filter Area > 200ha
Ranking Pairwise
Suitable
Area (ha)
No Large
scale area
No Medium
Scale
Percentage of
suitable area
Gilgle Abay 54,894 4 78 12
Ribb 31,780 3 4 16
Gumara 24,805 2 16 14
Megech 19,029 2 8 19
Total 130,508 11 106
60,750 ha
5% of the
land
130,500 ha
11% of the
land

18. 18

19. Water Availability
19
Watershed Irrigation potential of Q90 (ha)
Gilgel Abay 0.607 (2,040 to 2,780 ha)
Gumara 0.577 (750 to 1,020 ha)
Ribb 0.086 (129 to 175 ha)
Megech 0.088 (64 to 87 ha)

20. Conclusion and recommendation
20
Conclusion
Nearly 11% of the land in the Lake Tana Basin is suitable
for surface irrigation.
However, by analyzing 27 years of river discharge, less
than 3% of the potential irrigable area (or less than
0.25% of the basin area) could be irrigated consistently
by 90 percentile available flow.
The main limitation for irrigation in Lake Tana Basin is the
available water and not land suitable for irrigation. The
irrigation potential around lake Tana can be met by
construction of reservoirs or by pump systems using
water from the Lake Tana.

21. Conclusion and recommendations
21
Recommendation
 In order to improve the result of this study:
Chemical property of soil and soil depth has to
be considered.
 The study can also be done crop specific.

22. 22
አአአአአአአ!
Thank you!

23. 23
አአአአአአአ!
Thank you!

24. Anticipated Outcomes
24
Background
 Area of interest
 Problem statement
 Objectives
Approach
 General description of study area
 General description of spatial data needed
 Proposed analytical methods
 Spatial analysis flow diagram
Graphics
Maps
References

25. Introduction …
25
Irrigation
 Irrigation: is the artificial application of water to soil to assist
the production of crops
 if crop water requirement is met by rainfall irrigation is not
required
 Surface irrigation: water is distributed over the field by gravity,
the water is introduced at a highest point

26. Introduction…
26
Blue Nile Basin
 Contributes more than 60% to the
Nile River
 In Ethiopia second largest watershed
covering 20% of country area,
contributing 27% the country
irrigation potential
 Accounts 50% the total surface
runoff, more than 50% of ground
water potential
 Until recently there is only one water
resource structure to control flow of
water downstream
 The Irr. potential developed is below
the national less than 2%

27. Method…
27
Constraint map
 Limit the application of surface irrigation
 Constraints include water body's, urban areas, forest and
protected areas.
 Constraint map has a value of 1 and 0, value of zero is assigned
for constraints areas.
0
00
0
0
0
0
0
0
0
0
0
0
00
0
0

28. Method…
28
 Rainfall deficit (1992 to 2006)
• 8 rainfall station
• 4 potential evaporation
• Interpolation by Thiessen
Polygon method
• Rainfall deficit map is computed
ET
ET
ET
ET
2
2
34.01
273
900
)(408.0
U
eeU
T
GR
ET
asn
o

29. Method
29
Factors affecting surface irrigation
Factors included in this study :
• Climate condition (temperature, humidity, rainfall wind
speed etc)
• Water availability (river proximity)
• Topography (slope)
• Market outlets (Roads and Urban proximity)
• Soil type
• Land cover