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Nile Basin Focal Project

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Presented at the Basin Focal Project workshop 'Clarifying the global picture of water, food and poverty' from 18-20th September in Chiang Mai, Thailand.

Presented at the Basin Focal Project workshop 'Clarifying the global picture of water, food and poverty' from 18-20th September in Chiang Mai, Thailand.

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  • 1. IWMI NBI ENTRO ILRI WORLD FISH CENTER Supported by: CPWF 19/09/2009, Chaingmai
  • 2. Outline 1. Background 2. WP1 Poverty analysis 3. WP2: Assessment of Water Resources 4. WP3 Assessment of Water productivity 5. WP4 Institutional analysis 6. WP5 Intervention analysis 7. Conclusions Supported by: CPWF 19/09/2009, Chaingmai
  • 3. 1. Background assessment of the basin Nile BFP Project Objective: To identify high potential water management interventions to reduce poverty and increase water productivity Supported by: CPWF 19/09/2009, Chaingmai
  • 4. Basin is highly variable The Basin is highly variable, theSupported by: CPWF river is very important, various interventions 19/09/2009, Chaingmai
  • 5. Key ideas: • Access to water is related to poverty, not availability – need to differentiate access and availability • Water productivity can be a key driver of wealth generation • Issues are different between Egypt and Northern part of Sudan and the rest of the basin – access to water, productivity, institutions, etc. • In US Basin countries water access is limited, and water productivity low – key to poverty reduction. Supported by: CPWF 19/09/2009, Chaingmai
  • 6. Project premise: • These are missed opportunities because agriculture water management for rainfed, wetland, livestock, fisheries, aquaculture tend to fall in a void. • There are inadequate institutional arrangements to support this. Supported by: CPWF 19/09/2009, Chaingmai
  • 7. Project premise: • There are numerous opportunities to manage water better for agriculture in order to improve productivity, food security and livelihoods. • While most of the focus is on river water, we start with rainfall to look for opportunities outside of the river. • Significant gains can be made through improving rainfed production systems through better agricultural water management • Livestock, fisheries, aquaculture, wetlands provide opportunities, but are generally absent in Nile discourse. Supported by: CPWF 19/09/2009, Chaingmai
  • 8. Baseline Conditions • High poverty and low development 0.90 Egypt Sudan Kenya • High Rainfall Poor Water Distribution-high loss Uganda Hum developm index 0.78 Ethiopia Tanzania upstream Rwanda ent 0.65 average, all countries • Drought & flooding 0.53 • High rainfall variability an 0.40 • High agriculture dependency, slow 0.28 transformation 0.15 1972 1978 1984 1990 1996 2002 2008 • Despite potential, low water usage Year 10000 3618 Agricultural Population in the Nile Basin Pe rc en tag e o f A g ric u ltu ra l 936 1050 1012 Precipitation (km 3 yr -1 ) 1000 285 402 100 1979-1981 Po p u la tio n 80 100 1989-1991 51 45 60 34 32 1999-2001 40 2003 10 20 2004 0 1 t ia i n ea a ia da da yp DR nd da op ny an it r an an Eg ru Egypt Eritrea Rw anda U ganda Kenya Ethiopia Tanzania Burundi Sudan D R Congo Su Ke hi o, Er nz Ug Bu Rw Et ng Ta Co Supported by: CPWF Countries 19/09/2009, Chaingmai
  • 9. Nile Basin Study Sites: Study Sites Nile Delta Sudan Transect Basin Wide Sudd Ethiopian Highlands Cattle Corridor Lake Victoria: Ugandan Highlands Supported by: CPWF 19/09/2009, Chaingmai
  • 10. Case Study Sites Y # SU D A M ong alla Y # [ % N im ule L aropi As w a P anyang o # Y Y # P akw ac h # Paraa A lb Y Y K am d ini er t # M u rchision Fa lls N il e Y # Ma sind i P ort B ut iaba Y # D R C Bu n ia L. Albert Y # [ % B ug ond o L. K y og a Kaf u Na ma sag ali [ % V ic B we ram ule Y # tori ki S em ili M bu lam u ti Y # aN Fo rt P o rtal M u z izi [ % ile N ga m b a O w e n Falls D am ia N zo S io Y # Y # Jinja [ % Y ala K at on ga Ka m p ala K asen y i # L. G e orge Y E n teb b e % [ Kis u m u So nd u Ish a ng o Y # Y # # K azing a C ha n ne l Y [ % K atw e L. E d war d Ka ge L. Victoria ra Bu ko b a [ % [ % M ara M u s om a K ig ali L. K ivu [ % Nyaborongo D im [ % a M w a nza vuvu Sim yu Ru L. Ta ng any ik a Y # D isc harge Stations [ % Tow ns Falls Equatorial La ke S ub- Basins Supported by: CPWF 19/09/2009, Chaingmai Riv ers Sc a le 1 :4 , 25 0 , 00 0
  • 11. The Nile Basin Food or environment? Supported by: CPWF 19/09/2009, Chaingmai
  • 12. Irrigation Schemes Country Irrig. Water Irrigation Irrigated Requirement, Potential, ha Area, ha m3/ha/yr Burundi 13,000 80,000 0 DRC 10,000 10,000 0 Egypt 13,000 4,420,000 3,078,000 Eritrea 11,000 150,000 15,124 Ethiopia 9,000 2,220,000 23,160 Kenya 8,500 180,000 0 Rwanda 12,500 150,000 2,000 Sudan 14,000 2,750,000 1,935,200 Tanzania 11,000 30,000 10,000 Uganda 8,000 202,000 9,120 Supported by: CPWF 19/09/2009, Chaingmai
  • 13. Irrigation Schemes, current & future … Supported by: CPWF 19/09/2009, Chaingmai
  • 14. Hydropower Plants, current & future Existing Sites New Planned Sites Supported by: CPWF 19/09/2009, Chaingmai
  • 15. Irrigated A green-blue view Rain = 1745 km3 Rainfed ET – 190 km3 Irrigated ET – 67 km3 Outflow – 10 to 30 km3 Limited options to expand Pastoral irrigation – but gets attention Rainfed Ample options to upgrade Wetlands agriculture on rainfed lands – gets little attention Supported by: CPWF 19/09/2009, Chaingmai
  • 16. Supported by: CPWF 19/09/2009, Chaingmai
  • 17. Nile Wetlands 14 Ramsar Sites All support agriculture and/or fisheries All sites listed as threatened by these activities Image of the Sudd CPWF, IWMI, WorldFish, ILRI, NBI Supported by: CPWF 19/09/2009, Chaingmai
  • 18. The Sudd Wetland: Inundation Extent Image courtesy of JAXA K&C Image courtesy of JAXA K&C ALOS PALSAR L-band SAR RED: June 2008, GREEN: September 2008, BLUE: December 2008 Supported by: CPWF 19/09/2009, Chaingmai
  • 19. Jonglei Canal Supported by: CPWF 19/09/2009, Chaingmai
  • 20. Jonglei Canal 360 km long 7 5 m wide 4 to 8m deep Supported by: CPWF 19/09/2009, Chaingmai
  • 21. Irrigation Schemes Country Irrig. Water Irrigation Irrigated Requirement, Potential, ha Area, ha m3/ha/yr Burundi 13,000 80,000 0 DRC 10,000 10,000 0 Egypt 13,000 4,420,000 3,078,000 Eritrea 11,000 150,000 15,124 Ethiopia 9,000 2,220,000 23,160 Kenya 8,500 180,000 0 Rwanda 12,500 150,000 2,000 Sudan 14,000 2,750,000 1,935,200 Tanzania 11,000 30,000 10,000 Uganda 8,000 202,000 9,120 Supported by: CPWF 19/09/2009, Chaingmai
  • 22. Irrigation Schemes, current & future … Supported by: CPWF 19/09/2009, Chaingmai
  • 23. Supported by: CPWF 19/09/2009, Chaingmai
  • 24. Supported by: CPWF 19/09/2009, Chaingmai
  • 25. 2. WP1 Poverty analysis Objectives: • To establish a broad understanding of poverty and how it relates to water access in production systems in the Nile • To create an overview of poverty and vulnerability indicators relevant for the Nile basin • To test links between water, agriculture and poverty in the Nile basin Supported by: CPWF 19/09/2009, Chaingmai
  • 26. Research questions: • What are the basin characteristics of water and poverty and how are they linked? • Where are the poor and what are their water related problems? • What are the water-related risks in crop-livestock systems? Supported by: CPWF 19/09/2009, Chaingmai
  • 27. Methods: • Literature review of the basin • Mapping hotspots of poverty in agricultural systems – We use food security, poverty level and poverty inequality to map poverty in the rural agricultural production systems of the Nile Basin. – Poverty in this case is related to household expenditure on food and non- food items. – Poverty line is drawn from expenditure required to purchase cost of a basket of goods that allows minimum nutrition requirements • Mapping vulnerability and water related risks • Case study on mapping poverty indicators and water access - Uganda Supported by: CPWF 19/09/2009, Chaingmai
  • 28. Poverty Hotspots: ± ± KEY KEY Rivers Water bodies Rivers Poverty level (%) Poverty hotspots <15 KEY Water bodies KEY 15 - 25 Poverty hotspots Mixed rainfed Rivers 25 - 35 Lakes Production system Cereals Nile Basin bnd 35 - 45 Agro-Pastoral Cereals+ Poverty level > 50% 45 - 55 Treecrops Legumes >55 Pastoral Rootcrops+ No data Legumes+ Treecrops+ 0 290 580 870 1,160 0 145 290 580 870 1,160 0 145 290 580 870 1,160 Rootcrops Kilometers Kilometers Mixed rain Kilometers 0 130 260 520 780 1,040 Kilometers Poverty in the Poverty in pastoral Poverty in cereal Poverty in tree and basin and agropastoral and legume root crop systems systems systems (banana, cassava & cotton) Supported by: CPWF 19/09/2009, Chaingmai
  • 29. Mapping vulnerability and water related risks • Vulnerability as exposure to risk, ability to cope with resulting impacts and the capacity to adapt to new conditions • Mapped several indicators of bio-physical and social risks which results into vulnerability • The outcomes of these cluster data were combined as severity indices ranging from 4 to 5 levels depending on the number of variables used • Vulnerability maps indicate levels of exposure to risk. These risks ranged from very high risk, high risk, moderate risk, low risk and very low risk. Supported by: CPWF 19/09/2009, Chaingmai
  • 30. Vulnerability hotspots: KEY KEY River Nile KEY River Nile River Nile Water bodies Water bodies Bio-physical vulnerability Water bodies Bio-physical risk Very low KEY Bio-physical risk Very low River Nile Low Very low Low Water bodies Medium Medium Bio-Physical risks Low High High Very low Medium Very high Very high Low 0 145 290 580 870 1,160 0 145 290 580 870 1,160 High Kilometers Kilometers Medium High Very high 0 145 290 580 870 1,160 Kilometers Very high 0 145 290 580 870 1,160 Kilometers Rainfed cereals Rainfed tree crops Irrigated Agropastoral • hotspots of vulnerability in agricultural systems (biophysical risks estimated from cluster data classification of human and livestock population, market access, internal renewable water resources and area of crop suitability) • population is a key driver of exposure to biophysical vulnerability especially in the intensifying crop livestock systems throughout the highlands and in the central belt of Sudan Supported by: CPWF 19/09/2009, Chaingmai
  • 31. Vulnerability: KEY River Nile KEY KEY Water bodies River Nile River Nile Social risk KEY Water bodies Water bodies Very low River_Nile Social risk Social risks Water bodies Very low Low Very Low Social risk Low Medium Low Low Medium High Medium Medium High Very high 0 145 290 580 870 1,160 High 0 145 290 580 870 1,160 0 145 290 580 870 1,160 High Kilometers Kilometers Very high Kilometers Agropastoral Rainfed cereals Rainfed tree crops Irrigated -cluster data vulnerability in agricultural systems (social risks estimatedstunted hotspots of classification of disease prevalence; malaria HIV/AIDS and from growth and malnourished children below age 5) - high vulnerability index in agropastoral areas reflects exposure and low capacity to cope with disease and food insecurity due to high poverty rates - low vulnerability index in irrigated systems reflects better institutional capacity to cope with the impacts of disease and food insecurity - exposure to disease and food insecurity is widespread in the rainfed agricultural systems of the basin except along the lower nile and into the delta region Supported by: CPWF 19/09/2009, Chaingmai
  • 32. Water related risks: ± KEY KEY KEY River Nile KEY River Nile River Nile Water bodies River Nile Water bodies Water bodies Water bodies Risk due to water Risks due to water Risk due to water Risk due to water Very low Very low Low Ver Low Low Low Medium Medium Low Medium High High Medium High Very high Very high 0 145 290 580 870 1,160 High 0 145 290 580 870 1,160 Very high 0 145 290 580 870 1,160 Kilometers 0 145 290 580 870 1,160 Kilometers Kilometers Kilometers Agropastoral Rainfed cereals Rainfed tree crops Irrigated - hotspots of water related risks in agricultural systems (hazards estimated from cluster data classification of drought index; rainfall variability as CV rain and changes in the length of growing period; LGP) - high risk index in agropastoral and rainfed areas reflects high variation due to rainfall and changes in the length of growing period - low risk index in irrigated systems reflectsCPWF dependency on rainfall Supported by: less 19/09/2009, Chaingmai
  • 33. Linking water, agriculture and poverty Where are the poor? What are their water related problems? • in hotspots with high population • Food insecurity due to high poverty densities in the mixed rainfed rates and dependency on rainfed agricultural systems particularly agriculture those supporting cereal-legume cropping and banana/cassava • high risk of rainfall variation and changes in length of growing season in systems pastoral and agropastoral systems • These are concentrated in the • high exposure to disease and highlands of east Africa (Kenya, malnutrition due to low institutional Uganda, Rwanda, Burundi and capacity to cope with the negative Ethiopia) impacts • In pastoral and agropastoral • low risk of rainfall variation and systems of the central belt of changes in length of growing season in the highlands as well as lake Victoria Sudan, northern Uganda and the sub-basin but widespread poverty still lake region of Tanzania unexplained by good market access • Low poverty in rice, wheat and cotton systems Supported by: CPWF 19/09/2009, Chaingmai
  • 34. 3. WP2: Assessment of Water Availability and Access Egypt Objectives: – Assess Nile water availability (spatio- temporal distribution) – Assess water demands and use – Assess water accessibility Eritrea Sudan Methodology Ethiopia – Rapid Assessment through literature review – Identify and fill in gaps of existing knowledge – Statistical analysis (trends, frequencies) Uganda Congo, DRC Kenya – Water accounting Rwanda Tanzania Burundi Supported by: CPWF 19/09/2009, Chaingmai
  • 35. Nile Basin Databases • Hydrological data base • Climate (precipitation) database (+ grid data) • ET, soil moisture, biomass, etc., (WaterWatch) • Storage systems database Flow station rainfall station (under development) Supported by: CPWF 19/09/2009, Chaingmai
  • 36. Sample results: Data collection Nile Database: Monthly river flow: 1910 to 2000 Discharge Processed [m3/s] 11-1910 11-1920 11-1930 11-1940 11-1950 11-1960 11-1970 11-1980 11-1990 11-2000 11-2010 ASWAN QP BAHIR_DAR QP DONGOLA QP GIRBA QP HASSANAB QP J_AULIA QP JINJA QP KESSIE QP KHARTOUM QP KILO_3 QP MALAKAL QP MANGALA QP ROSEIRES QP SENNAR QP TAMANIAT QP Supported by: CPWF 19/09/2009, Chaingmai
  • 37. How much is the Nile Is it 84.5 billion m3 (Blue) water? (data from 1900 to 1950) Long term mean: source Sutcliffe and Parks, 1999 Supported by: CPWF 19/09/2009, Chaingmai
  • 38. Nile trends: water flows MAIN NILE Monthly Flows: 1871/72 -2000/01 160.00 Q 1900 to 1950 = 86.3 140.00 What are the recent trends? More Q 1900 to 1995 = 80.8 water? 88km3 120.00 Billion M3 100.00 TOTAL 80.00 5yr moving mean 60.00 40.00 Q 1951 to 1995 = 76.0 20.00 0.00 84 96 20 32 44 56 74 98 72 78 90 02 08 14 26 38 50 62 68 80 86 92 - - - - - - - - - - - - - - - - - - - - - - 83 95 19 31 43 55 73 97 71 77 89 01 07 13 25 37 49 61 67 79 85 91 18 18 19 19 19 19 19 19 18 18 18 19 19 19 19 19 19 19 19 19 19 19 Supported by: CPWF 19/09/2009, Chaingmai
  • 39. < 25 25 - 50 50 - 100 100 - 200 200-400 400 - 600 Mean P 600 - 800 Mean ET0 800 - 1000 1000 - 1200 1200 -1400 1400 - 1600 >1600 Supported by: CPWF 19/09/2009, Chaingmai
  • 40. What is the seasonal variability? Supported by: CPWF 19/09/2009, Chaingmai
  • 41. Nile water accounting: Methodology • Based on water balance principle (inflow = ∆ outflow +∆S) • Define indictors: supply, consumption, beneficial (economical, environmental), non- beneficial • Boundary conditions (Inputs): – Water Supply: Rain, River, Groundwater – Water use: Consumptive (ET), non- consumptive, beneficial (T), non-beneficial (E), committed (treaties), etc. • Scales: – Spatial: catchment, production system, Source: Molden, 1997 sub-basin, basin, country – Temporal: month, season, annual, long term mean • Output – Water accounting water Supported by: CPWF productivity 19/09/2009, Chaingmai
  • 42. Input: Land and water use classes clas No. Land use s 1 closed forest NL 2 open forest NL 3 shrub land NL 4 woody savanna NL 5 open savanna NL 6 sparse savanna NL 7 natural wetland NL 8 rainfed crops ML 9 Urban + industustry MW 10 desert NL 11 irrigated crop MW 12 reservoir natural lakes and MW 13 rivers NL 14 managed wetland MW 15 saline sinks MW Supported by: CPWF 19/09/2009, Chaingmai
  • 43. Input: Land and water use classes Productio landus Area Area Rainfall ET T E n o. Landuse e type Km2 % mm mm mm mm Kg/ha 1 Closed forest NL 85,821 3% 1350 1113 929 183 33818 2 Open forest NL 19,337 1% 900 791 613 177 17316 3 Shrub land NL 260,299 8% 290 227 162 65 5074 4 Woody savannah NL 373,785 12% 1090 919 699 220 23348 5 Open savannah NL 764,232 24% 780 699 510 189 16429 6 Sparse savannah NL 315,078 10% 685 612 504 107 8741 7 Natural wetland NL 14,077 0% 670 1299 1088 210 17447 8 Rainfed crops ML 235,526 7% 910 839 684 155 13672 Urban and 9 industrial MW 5,377 0% 350 227 121 105 5776 10 Desert NL 941,604 30% 60 53 21 32 328 11 Irrigated crop MW 51,493 2% 250 975 894 80 14758 12 Reservoir MW 5,991 0% 400 2916 0 2916 0 13 Lakes & rivers NL 88,832 3% 1250 1555 0 1555 0 14 Managed wetlands MW 501 0% 450 1704 0 1704 0 15 Saline sinks MW 313 0% 450 2132 0 2132 0 3,162,26 Total 6 Supported by: CPWF 19/09/2009, Chaingmai
  • 44. Water balance for 2007 in km3 atural land cover Managed land use Managed water use atural forest P, ET Forest plantation P, ET Irrigation P, ET Savanna P, ET Rainfed crop P, ET Managed wetlands P, ET Desert P, ET .. P, ET Drinking water P, ET .. P, ET .. P, ET 81.4 5.0 -57.4 0.0 inflow 0.0 29.0 Outflow Aquifer & reservoirs Committed 9.8 Supported by: CPWF 19/09/2009, Chaingmai
  • 45. Water balance indicators for 2007 water balance components 2000 1745 1716 1500 km3 1000 500 76.6 57.4 29.0 9.8 19.2 0 y e ed ed ow ed s l bl pp es um itt rt ila tfl su xc ve m va ou ns om E di er A co at C w Water Balance indicators 100% 75% 50% 25% 0% Consumed Available Diverted Excess Committed Supported by: CPWF 19/09/2009, Chaingmai
  • 46. Water consumption for 2007 w ater consum ption 2000 1458 1305 ET, km3 1500 1000 716 588 411 500 189 69 0 l al nv n ia t.. .. co .. ici f ic -E n. wa c. -E f ne la ne al nd al ed ed be Be ici l la ici ag f ag n- ne f ne ra an No an Be tu Be m m na Water consumption indicators 100% 80% 60% 40% 20% 0% LU T LU T U T .E .E lE W al ed nv n ia ed ur co ag fic E ag at E n_ ne an N n_ an Be Be M Be M Supported by: CPWF 19/09/2009, Chaingmai
  • 47. a n n u a l b io m a s s in 1 0 ^ 9 k g 0 500 1000 1500 19/09/2009, Chaingmai C lo s e d fo r e s t O pen fo r e s t S h ru b la n d W oody savannah O pen savannah S p a rs e savannah N a tu r a l w e tla n d 9 land and water use Supported by: CPWF Biomass production in 10 kg R a in fe d c ro p s U rb a n a n d in d u s tr ia l D e s e rt Ir r ig a te d Water production for 2007 c ro p R e s e r v o ir Env. Feed Food wood Biomass Lakes & r iv e r s M anaged w e tla n d s S a lin e s in k s
  • 48. 4. WP3: Production Systems & Productivity Basin PS: Low to High Resolution Supported by: CPWF 19/09/2009, Chaingmai
  • 49. Water productivity mapping: METHODOLOGY Supported by: CPWF 19/09/2009, Chaingmai
  • 50. Data sources • Production data: - Countries statistic departments - FAO database in 2005 • Market prices of agricultural products • RS images and secondary GIS data - Waterwatch 2007 ETa and Ta maps - Land use/land cover (LULC); GLC 2008/ Africover - Admin and basin boundaries, road network, ecological zones Supported by: CPWF 19/09/2009, Chaingmai
  • 51. Standardized gross value of production SGVP: is an index which helps to compare the economical value of different crops regardless in which country or region they are. i  local price crop i   SGVP = ∑  × production crop i  × International price base crop  crops  i =1  local price base crop      Wheat is the major crop in the basin and it is taken as base crop. Supported by: CPWF 19/09/2009, Chaingmai
  • 52. Rainfall and Water stress Supported by: CPWF 19/09/2009, Chaingmai
  • 53. SGVP SGVP/ha is highly variable across the basin. Egypt has the highest SGVP/ha, 1830 US$/ha Sudan has the lowest SGVP/ha, which goes down to about 20 US$/ha in Northern Darfur Supported by: CPWF 19/09/2009, Chaingmai
  • 54. WP – SGVP/ETa & SGVP/Ta Supported by: CPWF 19/09/2009, Chaingmai
  • 55. Conclusions - More than half of the basin area is under high water stress - SGVP and Water productivity are highly variable across the Nile basin - While Egypt has the highest SGVP and WP, Sudan has the lowest - Except Gezira and northern provinces of Sudan in which irrigated farming is common practice, WP is very low in other parts of the country where rainfed farming is predominant. Supported by: CPWF 19/09/2009, Chaingmai
  • 56. Livestock Productivity: Where are the animals? Tropical Livestock Nile Basin Units per Km2 <1 1-10 10-20 20-30 >30 Supported by: CPWF 19/09/2009, Chaingmai
  • 57. Water productivity calculations for livestock for the Nile Basin. Supported by: CPWF 19/09/2009, Chaingmai
  • 58. Water Productivity of Aquaculture Objective • to estimate quantities of water used per unit biomass of fish produced in ponds in the Nile Delta • to prepare water budgets for earthen pond aquaculture to help guide future water allocation policies • to assess the water productivity benefits of different aquaculture technologies and incorporating aquaculture with agriculture – production and incomes http://girlsoloinarabia.typepad.com/photos/egypt/water_wheel.jpg – poverty Supported by: CPWF 19/09/2009, Chaingmai
  • 59. Experimental plans Estimate net water use in pond aquaculture throughout production season at two sites in the Nile Delta (WorldFish Center pond farm, Abbassa, and at a commercial fish Site 2 farm, Kafr El-Sheikh) Estimate water losses through different routes (seepage, evaporation, drainage etc ) Site 1 Determine the amount of fish produced Estimate water consumption rates (m3) per kg fish production Supported by: CPWF 19/09/2009, Chaingmai
  • 60. Estimating water use modified from Nath & Bolte (1998) waterfeed + inflow = outflow + ∆S + waterfish excluding rain, surface runoff, waterfeed, and infiltration, inflow can be regarded as water added excluding overflow and waterfish outflow can be regarded as change in pond storage plus seepage and evaporation i.e. water consumption per kg fish production = kg fish pond-1/Ii – (E + S + Q ± ∆S) water consumption per pond = Ii – (E + S + Q ± ∆S) Supported by: CPWF 19/09/2009, Chaingmai
  • 61. Abbassa ponds • 5 ponds, stocked 1 June 2008 Supported by: CPWF 19/09/2009, Chaingmai
  • 62. Routine measurements • pond water levels determined weekly using fixed graduated tube to measure pond tubes at three locations per pond water column height • water levels determined before and after water was added to compensate for losses • fish sampled monthly to determine growth • fortnightly water samples taken to determine DO, pH, Secchi disc depth, N and P • monthly analysis of phytoplankton Supported by: CPWF 19/09/2009, Chaingmai
  • 63. Fish growth in earthen ponds over a five-month growing period 250 200 Average fis weight (gm) Pond 1 150 Pond 5 Pond 10 Pond 13 100 Pond 16 50 0 1 2 3 4 5 t ar th th th th th St on on on on on m m m m m Groth period (month) Supported by: CPWF 19/09/2009, Chaingmai
  • 64. Water use – preliminary results (Abbassa Site) tube to measure pond water column height Supported by: CPWF 19/09/2009, Chaingmai
  • 65. Seasonal variation in losses of water Supported by: CPWF 19/09/2009, Chaingmai
  • 66. 5. WP4: Institutional Analysis of the Nile Basin Research questions • What are the water related institutions and policies that shape agricultural outcomes in the Nile Basin? • Do existing institutional and policy environment support beneficial use of water for poverty alleviation? • Are basin wide priorities and nation wide institutions and policies compatible? • What are the agriculture related outcomes in the basin? Supported by: CPWF 19/09/2009, Chaingmai
  • 67. Research methods • Understanding institutions and policies at multiple scales – Basin wide analysis: (Institutional analysis of the NBI and CFA) – Country analysis: Review of institutions and policies in selected countries (Egypt, Sudan and Ethiopia) – Micro level analysis at hotspots: Lake Victoria, Ethiopian Highlands, Gezira scheme and Sudd wetlands • Mixed methods: Literature review and primary data collection Supported by: CPWF 19/09/2009, Chaingmai
  • 68. Institutional analysis of NBI • What worked? – Promoted the culture of dialogue between riparian states – Attracted large donor funding – Basin wide perspective – Shared Vision and Subsidiary Action Program produced important outputs Supported by: CPWF 19/09/2009, Chaingmai
  • 69. Institutional analysis of NBI • What did not work as expected? – Not much evidence that power balance between upstream and downstream riparians have indeed changed – Absence of a clear regulatory framework even after 10 long years of negotiation • Conclusion – The future of cooperation in the Nile Basin is not ‘black or white’: the choice is not between, on the one hand, fully-fledged cooperation and non- cooperation on the other. On the contrary, there exists a large and diverse grey-scale and the different emerging scenarios involve their own complexities. Supported by: CPWF 19/09/2009, Chaingmai
  • 70. Results from micro-level institutional studies • Insights on collective action for watershed management in Ethiopian Highlands –Compared successful watershed intervention with a not so successful one –The inherent strength of local institutions & support given by implementing agency (GTZ in this case) are the two crucial factors in success. • Impact of institutional and policy change on productivity of Gezira –Change in institutional regime from joint account to individual account to economic liberalisation –Production, productivity and cropping pattern changed with every change in policy and institutions –Area under cotton fell and gave away to wheat and other food crops. Supported by: CPWF 19/09/2009, Chaingmai
  • 71. Results from micro-level institutional studies • Institutional mechanisms in Lake Victoria Multiplicity of institutions and overlap of authority and responsibilities; –Fisheries management is the best coordinated activity among the 3 eastern Nile country –Centrality of income from fisheries leads to such cooperation –Provides employment to 3 million people –Generates USD 400 million worth of income of which USD 250 is export earning Supported by: CPWF 19/09/2009, Chaingmai
  • 72. 6. WP5 Intervention Analysis Objectives: • To understand interventions that can have greater impacts in the Nile Basin • Specific objectives are to: – Inventory and characterize existing interventions in production systems – document success and failures of interventions and map intervention types – detail performance analysis of existing interventions and impacts – undertake tradeoff analysis, ranking and modeling to select and evaluate high impact interventions and implementation strategy – Develop problem tree & impact pathways through interventions Supported by: CPWF 19/09/2009, Chaingmai
  • 73. Key Research Questions • What are the existing water related interventions in the basin under various production systems? • Which interventions have succeeded and which ones failed? • What are the technical, economic, institutional setups for successful or failed interventions under various systems? • Which future interventions are required to bring high impact on poverty, water availability, access and productivity for various target groups? • Note: All questions may not be answered and some will lead to future work Supported by: CPWF 19/09/2009, Chaingmai
  • 74. Interventions Category/ Types - Production/Farming system based • Crop Based: Field Crops, Horticulture, Forestry/ agro-Forestry • Animal based: Livestock, Fisheries/Aquaculture • Rain fed, irrigation, mixed crop-livestock, etc – Physical based • Infrastructural interventions • Water and land based interventions: eg watershed management – Socio-economic based • Ag trade, virtual water • Hydropower-generation, power trade, interconnection • Industrial – value addition – Institutional and policy based • Institutional innovations, basin, sub-basin institutions • Benefit/water-sharing Supported by: CPWF 19/09/2009, Chaingmai
  • 75. Interventions Category Regions/zones – 5 specific detail case study sites • Ethiopian Highlands • Victoria Nile • The Sudd • Gezirra • Delta – One integrated basin wide analysis Supported by: CPWF 19/09/2009, Chaingmai
  • 76. Example 1: Ethiopian Highlands Agricultural Interventions (Agriculture - main source of livelihood) Challenges • Extreme biophysical variations Increased poverty, food insecurity & – Elevation, soil, climate Major chalenges to agriculture • Population pressure and land Vulnerability to climate change degradation ⇒ Shortage of land ⇒ Encroachment to marginal lands ⇒ Exacerbating deforestation and erosion ⇒ Reduced land and water productivity • Poor infrastructural development • Limited use of modern technologies – Lack of site specific technologies – Lack of integrated approach Required: Identification +Disseminate of Site specific Technologies Pre-requisite: identify by: CPWF Supported “Homogeneous Units” 19/09/2009, Chaingmai
  • 77. Methodology • “Homogenous” units of farming systems (FS) have been mapped based on: – Agro-ecology (Elevation, Soil, LGP) (BMPS, Woody Biomass) data – Major crops grown (BMPS, CSA reports) • Current crop and livestock productivity of the FS examined (BMPS,CSA reports) • Major productivity limiting constraints identified • Promising technologies identified (secondary data) • Productivity & Poverty impacts analyzed (HH consumption data) 77 Supported by: CPWF 19/09/2009, Chaingmai
  • 78. Results- The FS Cereal based system dominate ed ifi nt de Single cropping si FS the largest of FS cereals 10 Livestock density changes with small cereals 78 Supported by: CPWF 19/09/2009, Chaingmai
  • 79. Results- the FS: Distribution and Productivity • Crop productivity too low regardless of the FS • Average grain yield < 1 T/ha • Maize and sorghum are high yielding - much less than the potential & national average Some reasons: • Low Soil Quality • Lack of improved technologies • AWM (SWC, irrigation, drainage) • Soil fertility management • Improved Crop varieties 79 Supported by: CPWF 19/09/2009, Chaingmai
  • 80. Characterization Supported by: CPWF 19/09/2009, Chaingmai
  • 81. The way-out: Multi-faceted Interventions Technological – Agricultural water management • Conservation, Irrigation, Drainage Integrate – Soil and Water Conservation Technologies: • Biological + mechanical – S+S+W – Soil fertility management • Fertilizers +Liming – IWSM – Improved crop varieties – Crop protection • Pre +Post harvest tech. 81 Supported by: CPWF 19/09/2009, Chaingmai
  • 82. 3.5 Some examples of Interventions 3 2.5 Yl ( h ) 1 i dt a - 2 e 1.5 1 0.5 0 Traditional Tied ridge Traditional Tied ridge Traditional Tied ridge Sorghum Mungbean Maize Location Variety Management practices Increment (%) Traditional Improved Crop verities and Mgt Jimma local 28.4 37.3 32 UCB 25.9 46.1 78 Beletech 26.3 39.8 51 BH_140 26.4 45.9 74 BH-660 25.8 57.6 124 kuleni 26.5 46.2 75 Adet BH-540 29.3 48.96 67 kuleni 50.6 81.8 61 Pawe BH-530 41.7 81.7 96 BH-140 41.7 76.7 84 Bako BH-140 29 34.2 82 18 Supported by: CPWF Beletech 29 38.2 32 19/09/2009, Chaingmai
  • 83. Inventory for AWM Ex-situ In-situ Well + Treadle Improved planting pits Trash lines pump + Drip kit Well+motorised pump Stone bunds Diversion Spate irrigation Large irrigation Micro dam + canal + furrow Supported by: CPWF 19/09/2009, Chaingmai
  • 84. List of promising AWM technologies Rank Tigray Amhara Oromia 1. River Diversion River diversion Wells 2. Micro dam Micro dams River diversion 3. Wells Wells Pond 4. Ponds Pond Spate 5. Tankers Terraces 6. Dams Supported by: CPWF 19/09/2009, Chaingmai
  • 85. Poverty, HFS, Institutions & Impacts Variables Incidence Depth Severity (α=0) (α=1) • Poverty (α=2) – 22% less poverty incidence for users Access to irrigation of AWMT Irrigators 0.585 0.322 0.226 – Treatment led to an increase in HH Non-irrigators 0.771 0.425 0.283 income - ca.ETB 670/ household – deep wells, river diversions and micro dams have led to 50, 32 and 25 % reduction in poverty levels compared to the reference, i.e. rain fed system. ∴The impacts of ponds and shallow wells are relatively modest compared to deep wells, diversions and small dams. • HH food security has significantly 50 improved % of sample farmers reporting 45 40 • Institutional: 35 30 Irrigators 25 – Traditional irrigators higher efficiency 20 Non-Irrigators 15 – Modern irrigators have higher 10 production frontiers 5 0 – Institutional stabilities considerably Sales of Cattle Sales of Small Animals Off-farm Employment Consump tion Credit affecting performance, . Supported by: CPWF Food shortage copping strategy 19/09/2009, Chaingmai
  • 86. Example 2: Integrated Basin Analysis Integrated basin-wide modeling to: •Assess the current and future large-scale intervention scenarios •Evaluate the impacts of these scenarios on water availability, access and productivity •Generate biophysical indicators of interventions for socio- economic and environmental assessments Supported by: CPWF 19/09/2009, Chaingmai
  • 87. Integrated Basin Analysis Infrastructural Interventions • Control and Management of Natural Lakes (2) • Large Dams/Reservoirs and Diversions (15) • Small dams • Ground Water Storage and Recharge • Non-Conventional Water Sources Technologies Supported by: CPWF 19/09/2009, Chaingmai
  • 88. Large-scale Interventions and Scenarios • Large-scale interventions considered: – Water control and storage infrastructures (single or multi- purpose) – Irrigation schemes – Hydropower plants – Environment and wetlands • Simulation Scenarios: – Current large-scale developments (Baseline) – Medium-term intervention plans (2015) – Long-term intervention plans (2025) Supported by: CPWF 19/09/2009, Chaingmai
  • 89. Modeling Framework • WEAP water resources simulation model applied at monthly time-step • Monthly river flows are extended from rainfall and ET using monthly water balance model • Annual irrigation demands are disaggregated according to ET • Wetland consumptions are treated as sinks (environmental flow requirements) • Storage release rules are represented as stream flow requirements {Q = f(storage head)} Supported by: CPWF 19/09/2009, Chaingmai
  • 90. Integrated Analysis: River Schematization and Flows Khartoum Hawata 1,102 Rahad 2,797 Dinder Giwasi Lake Tana Sennar Bosheilo SUDAN 3,809 Roseires 3,920 Beles Outlet Lake Tana Border 4,345 Welaka North Gojam 2,072 Wonbera South Gojam Jemma ETHIOPIA 4,798 3,874 5,012 4,389 Kessie Muger 2,440 6,246 Anger 2,355 1,719 2,187 Dabus Flow gauging station 5,673 Reservoir Guder Mean annual Didessa 4,345 Finchaa discharge (Mm3) Supported by: CPWF 19/09/2009, Chaingmai
  • 91. All plans: -Country specific -SAP projects Supported by: CPWF 19/09/2009, Chaingmai
  • 92. Preliminary Results – Lake Victoria ð ($ # Supported by: CPWF 19/09/2009, Chaingmai
  • 93. Preliminary Results – Wetlands Supported by: CPWF 19/09/2009, Chaingmai
  • 94. Aggregated Basin Conclusions and Outlook • The topology of the basin is configured for WEAP simulation model • Reliable information and data relevant to the integrated modeling are almost collated • Basin-wide simulations of large-scale intervention scenarios are being conducted • Finally, the integrated modeling experiment shall generate biophysical indicators for impact assessment and identification of potential interventions Supported by: CPWF 19/09/2009, Chaingmai
  • 95. WP5 Example: Capacity Building • Tewdros : Water Resources Allocation of the Nile River Basin: A cooperative Game Theoretic Approach – Integrated economic-hydrologic-institutional modeling at the River Basin Scale • George: Developing Optimal Economic Incentives for Managing Transboundary Water Externalities in the Blue Nile River Basin – Application of economic instruments to review the past and present legal documents on the Blue Nile and treaties governing the entire Nile River Basin – Modeling optimal allocation of water for maximizing use benefits among the countries established • Binyam: Equitable Distribution of Benefits in Transboundary Waters – Irrigation and Hydropower Benefits Sharing – From Water Allocation and Cost Sharing to Benefit-Sharing: Implications for Transboundary Rivers in the Nile Basin • M.Sc. students Supported by: CPWF 19/09/2009, Chaingmai
  • 96. 7. Conclusions • Poverty is prevalent in high population, rainfed, pastoral and agropstoral areas and less in irrigated systems and with access to AWM • Temporal and spatial variability of rainfall and runoff are high and not sufficient mechanisms for improving water access • Water productivity and productivity/ha are higher in managed water system part of the basins and significant opportunities to improve rainfed productivity • Regional bodies such as NBI and water institutions give low focus to rainfed production systems, livestock and fisheries. Establishing relevance is important • NBI Institutional Arrangement is progressing but the outcome is uncertain • Multiple interventions exist to improve rain fed productivity, reduce poverty and enhance negotiations and economic integration Supported by: CPWF 19/09/2009, Chaingmai
  • 97. Thank You Supported by: CPWF 19/09/2009, Chaingmai