Realistic assessment of irrigation potential in the Lake Tana Basin, Ethiopia

  • 983 views
Uploaded on

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 …

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

More in: Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
983
On Slideshare
0
From Embeds
0
Number of Embeds
5

Actions

Shares
Downloads
18
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide
  • Area 15,000 km2 (1,500,000 ha) 1.5m ha
  • S1 Highly suitable: without significant limitations Chromic LuvisolsS2 Moderately Suitable has limitations Eutric CambisolsS3 Marginally Suitable benefits are reducedHaplic Alisols S4 Not suitable cannot supportLithic Leptosols
  • S1 Highly suitable: without significant limitations Agricultural landS2 Moderately Suitable has limitations Grass landS3 Marginally Suitable benefits are reducedDominated by shrubs/ Stony grass land S4 Not suitable cannot supportDeveloped area
  • Coordinates are collected from Google earth
  • Paved roads digitized manually from Google Earth
  • The first three impotent three factors will require huge amount of investment, and weighted according to their unit rate Artificial channel construction unit rate Paved road construction unit rate Land laveling 9: Absolutely more important 4 : More important 1: Equal importanceReciprocal is entered in the transpose
  • The first three impotent three factors will require huge amount of investment, and weighted according to their unit rate per m2.
  • The dominant crops in the Lake Tana area include barley, corn, millet, wheat, sorghum, teff, beans and rice.
  • The first three impotent three factors will require huge amount of investment, and weighted according to their unit rate per m2.Urban proximity has smaller weight in the pairwise 4% Equal 14 and Ranking = 9
  • The first three impotent three factors will require huge amount of investment, and weighted according to their unit rate per m2.Urban proximity has smaller weight in the pairwise 4% Equal 14 and Ranking = 9
  • Water is distributed by flooding the crops Surface irrigation It is less expensive Labor intensive
  • Daily rainfall dataPotential evaporation: the evaporation potential of the climate Penman monteath (Tmax, Tmin, Wind speed, relative humidity etc)
  • Factors affecting surface irrigation Climate condition (temperature, humidity, rainfall wind speed etc)Water availability (river proximity) Topography (slope)Market outlets (Roads and Urban proximity)Soil typeLand cover

Transcript

  • 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