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Rethinking water storage for climate change adaptation in Sub-Saharan Africa

GTZ project. Rethinking water storage for climate change adaptation in Sub-Saharan Africa. Project overview. Objective Guidance on storage options that ensure optimal adaptation to CC-induced impacts on water availability in SSA Partners Duration and focus

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Rethinking water storage for climate change adaptation in Sub-Saharan Africa

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  1. GTZ project Rethinking water storage for climate change adaptation in Sub-Saharan Africa

  2. Project overview Objective Guidance on storage options that ensure optimal adaptation to CC-induced impacts on water availability in SSA PartnersDuration and focus • Arba Minch University (AMU), Ethiopia 2008-2011, Nile and Volta • Ethiopian Economic Association (EEA) • Water Research Institute (WRI), Ghana • Institute of Statistical, Social and Economic Research (ISSER), Ghana • Center for Development Research (ZEF), Germany • Potsdam Institute for Climate Impact Research (PIK), Germany Research Questions • How can the need for water storage and the effectiveness and suitability of different storage options be evaluated and compared for different climate scenarios? • How can water resource planning and management processes be modified to better account for the uncertainties arising from climate change? Principal output Guidelines on how to build climate change into decision-making processes for the planning and management of agricultural water storage in sub-Saharan Africa

  3. Project Rationale • Water storage is widely advocated as a key mechanism for CC adaptation • Little analysis of how CC affects existing water storage or how to account for CC in the planning and management of new water storage

  4. Physical Storage Continuum

  5. Project Output Guidance on: “ …..storage options that ensure optimal adaptation to CC-induced impacts on water availability in SSA” Targeted at institutions that evaluate, design and implement water resource development projects and investment programs • International development agencies • State bodies • Public and private funding agencies

  6. Approach Basin scale analyses Evaluation of climate change impacts on storage at basin scale –effectiveness Site level analyses Understanding storage at the local (economic and socio-political aspects) – suitability • Evaluation framework • Metrics to determine: • The need for water storage • The effectiveness of different options • The suitability of different options Guidance

  7. Basin scale analyses (Nile and Volta) • Climate - rainfall, temperature, evaporation • Historic climate • CC scenarios (downscaled to the basins) Hydrological model (SWAT/SWIM) • Current and future storage plus water use in each basin • Evaluation of climate change impacts on storage at the basin scale Results: Flow at key locations (sub-catchments) • Water resource modeling (WEAP) • current water resource development • future water resource development Results: Water availability for irrigation/hydropower Effectiveness of existing and planned storage

  8. Climate Modeling • Approaches of downscaling • Dynamical climate models: CCLM and REMO (both for A1B) + bias correction • Statistical climate model: WettReg (for different scenarios and GCMs) • Resolution: 0.5° (attempt 10 km but not yet complete) • Further regionalization / interpolation to locations of interest Mean annual total precipitation (mm) 1971-2000

  9. CCLM output for the Nile (A1B scenario) GP_106_22 Mean Temperature (mm) GP_106_122 X GP_098_128 Annual Rainfall (mm) GP_098_128 X

  10. CCLM output for the Volta (A1B scenario) GP_095_052 Mean Temperature (oC) GP_110_047 X GP_110_047 Annual Rainfall (mm) GP_095_052 X

  11. RCM Scenarios – Rainfall (Nile) 2090s – 1990s 2030s – 1990s

  12. Hydrological Modeling • Rainfall-Runoff simulation to determine impacts of CC on flow regimes and groundwater recharge • Daily simulation to deduce impacts on extremes – floods and droughts

  13. Basin characteristics Topographic WI NDVI

  14. MWB: Model calibration and validation

  15. Water Resource Modeling (WEAP) • Water Evaluation and Planning (WEAP) Model • Water accounting model (mass balance) – optimizes water use (monthly time-step) • Data from:

  16. Scenarios + Planned development – feasibility studies conducted * Potential development – identified in Master Plans etc.

  17. WEAP configuration for the Volta Current situation Devaraj de Condappa et al (2008)

  18. WEAP configuration for the Nile Current situation Near future Distant future

  19. Blue Nile Ethiopia: Existing and Planned schemes Results (no climate change)

  20. Site Level Analyses • 3 locations in each of Nile and Volta • Nile = Koga, Gumera , GuderIdris • Volta = Vea (Yaragatna River), Golinga, Sata • Evaluation of socio-economic aspects of storage • What benefits accrue and who gets the benefits? • What are the costs and who has to pay? • Issues • availability; economic viability; uptake; access; equity; institutional arrangements; socio-political aspects etc.

  21. Approach Socio-economic survey – Quantitative • Conducted in all sub-basins • Information on benefits/costs people derive from different water storage options as well as perceptions of CC ZEF investigations – Qualitative • Gender aspects and the access to natural resources in a small-scale irrigation scheme (Shina dam), Gumara watershed. • Watershed and irrigation management in a large-scale irrigation scheme, Koga watershed. • Resettlement, social bonds and attachment to land in a large-scale irrigation scheme, Koga watershed. • Power relations and control over water resources. The case of Indris irrigation scheme. • Access to land and water management: Indris irrigation scheme. • Socio-economic and political impact of water storage facilities on rural household livelihood. A study of Gumera watershed, Abay River Basin, Ethiopia

  22. Impacts of small-scale water storage on rural household livelihoods in Gumera Benefits • 3 crops/year – sufficient food • Increased variety of crops (e.g. rice) • Increased income. Farmers can earn between 3,000 – 5,000 EB per vegetable garden • Increased size of land holdings. Some farmers can now rent land to expand their production • Reduced cases of water borne diseases • Stronger relationship with neighbors due to water sharing Constraints • Cracking of the soil • High material and construction costs • Labor shortage – common with FHHs, old age HHs • Limited skills in management of ponds

  23. Evaluation Framework Objective of water storage is to reduce climate vulnerability Increased adaptive capacity Present climate vulnerability (pre-adaptation) Water storage (adaptation strategy) Increased availability and access to water Increased agricultural productivity Future climate vulnerability (post adaptation) Increased water security Future climate vulnerability < Present climate vulnerability

  24. Steps No (stop evaluation) Is storage needed now and/or will it be in future? No (stop evaluation) Is it and will it in future be technically effective? Yes No (stop evaluation) Is it and will it in future be socio-economically suitable? Yes Continue with detailed planning Yes • As far as possible: • Objective /quantitative • The same for all storage types • Applicable across a range of scales • Applicable now and under climate change scenarios

  25. The need for agricultural water storage

  26. Technical effectiveness of the water storage system RRV for Koga and Gomit dams in the Nile Basin: Gomit Challenge = need to be able to compute these metrics for a number of storage types within a storage system Koga

  27. Suitability of the water storage system Most likely metrics through multi-criteria scoring systems rather than numerical data

  28. Capacity Building Capacity Building: • 3 MSc’s completed (Arba-Minch) • 12 Masters ongoing: • Arba Minch • ZEF • University of Accra • Humboldt University • 1 PhD student University of Berlin

  29. Project website • http://africastorage-cc.iwmi.org/ Photo Gallery Links to other sites Reports/Power points/Papers

  30. Thankyou

  31. Bias correction For each grid point, long-term (1961-90) observation (corrected) and long-term simulation by CCLM are compared on a monthly basis; The bias per month is calculated for each cell and month; The climate projections are corrected by this bias. Simulated by climate model Simulated and bias corrected Observation corrected by measurement error Observation

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