Ag MIPEastern Africa Overview Eastern Africa Team Background
Ag. MIP-Eastern Africa Overview Eastern Africa Team
Background • Eastern Africa is one of the regions in Africa where production is lagging behind population growth • High dependence on rainfed agriculture and high variability in rainfall are the main reasons for the variability in food production in the region • Climate change is expected to further exacerbate the situation Data source: FAO
Cereal yields in Eastern Africa • Except for Ethiopia, Madagascar and Rwanda, cereal yields remained the same or declined during the past decade Data source: FAO
Maize yields in Kenya
2000 2050 Dry areas – Eastern Africa • More than a third of the region is semi-arid or dry sub-humid which are marginal environments for crop production • This area is expected to grow with the projected changes in climate by about 1. 71 m km 2 by 2050 • Major changes are expected in Tanzania, DR Congo and Madagascar
High uncertainty Expected change in Rainfall (%) Predic tion 2046 -2065 2081 -2100 Katu mani Mwin Muto Katu gi mo mani Kitui Min 23. 9 -10. 7 -4. 4 -4. 5 30. 9 -11. 5 -4. 8 9. 3 Med 41. 0 17. 0 -0. 1 9. 1 70. 9 24. 2 15. 5 13. 6 Max 57. 6 58. 2 22. 8 58. 2 96. 9 58. 8 33. 9 58. 1 Kitui A 2 SRES , summary of 11 GCM outputs Mwin Muto gi mo
Ag. MIP-Eastern Africa • Assessing the impacts of climate variability and change on agricultural systems in Eastern Africa while enhancing the region’s capacity to undertake integrated assessment of vulnerabilities to future changes in climate • Participating countries: o o Kenya Tanzania Uganda Ethiopia
Project Partners 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. International Crops Research Institute for Semi Arid Tropics (ICRISAT) Makerere University (MAK) National Agricultural Research Organization (NARO) Uganda Department of Meteorology (UDM) Kenya Agricultural Research Institute(KARI) Kenya Meteorological Department (KMD) University of Nairobi (Uo. N) Sokoine University of Agriculture (SUA) Tanzania Meteorlogical Agency (TMA) Institute of Rural Development and Planning (IRDP) Mekelle University (Mk. U) Ethiopian Institute of Agricultural Research (EIAR) National Meteorological Agency (NMA) Climate Change, Agriculture and Food Security (CCAFS) Association for Strengthening Agricultural Research n. In Eastern and Central Africa (ASARECA)
Project- Aims • Conduct a systematic, comprehensive, and quantitative assessment of impacts of climate variability and change on agricultural systems and their implications on income and food security • Assess the impacts at scales ranging from farm, local, agroecological and regional • Identify adaptation options with due consideration to the interactions between the key variables of climate, crop and socio-economics • Establish multi-disciplinary teams and enhance their capacity with skills and capabilities in validating and using climate, crop and economic models
Outputs • Databases and well tested tools and methodologies to assess biophysical and socio-economic implications of the effects of climate variability and change • A core team of climate, crop and economic modellers, with improved skills in the use of advanced models and sophisticated frameworks for integrated assessment of climate change impacts • New knowledge and information about impacts of climate variability and change on key agricultural systems and their biophysical and socio-economic implications at multiple scales • Increased sharing of relevant and timely knowledge and information about the impacts of climate variability on agricultural production and food security
Methodology • Four country teams work independently and a team environment • Uses agro-ecologies as base unit with additional subdivisions – Humid, sub-humid and semi-arid • • Focus on crops that are relevant to smallholder farmers Assemble data required for climate-crop-economic models Calibration, validation and testing of models Develop economic scenarios – Scenario 1: Climate change but no adaptation – Scenario 2: Climate change with adaptation – Scenario 3: Baseline scenario • Conduct simulations and assess impacts under current and future climatic conditions • Extrapolate the results to target agro-ecology
Target crops and locations Crop Maize Beans Sugar cane Sorghum Uganda Mt Elgon (H) Hoima (SH) Mbarara (SA) Kenya Kitale (H) Nakuru (SH) Machakos (SA) Tanzania Uyole (H) Morogoro (SH) Arusha (SA) Mt Elgon (H) Hoima (SH) Mbarara (SA) Jinja-Kakira (SH) Kitale (H) Nakuru (SH) Machakos (SA) S. Nyanza (H) Nyando (SH) Busia (H) Kitui (SA) Uyole (H) C. Rift valley. Morogoro (SH) Nazret&Awasa (SA) Arusha(SA) Wheat H=Humid, SH=Sub-humid, SA=Semi-arid Ethiopia Ambo (H) Bako (SH) Adgudon plains (SA) Hombolo and Dodoma (SA) Hagere Selam (H) Eteya Gonde (SH) Adgudon (SA)
Distribution of sites
Models to be used Area Model/tool Climate Instat modeling Mark. Sim-GCM Tamet Tav_amp Crop models Purpose Variability and trend analysis Future climate scenarios development Quality checks on climate data Calculating (TAV) and (AMP) required for crop models Weather translator Convert DSSAT climate files into APSIM format DSSAT Assessing climate impacts on crops and APSIM evaluating adaptation options Aquacrop R Script Economic To. A-MD modeling DREAM IMPACT IT Web tools Database GIS Data analysis and graphical representation Impact assessment of technologies Economic impacts of agriculture Examine alternative futures for global food supply Develop web pages, blogs Archiving and retrieving data Presenting results
Analytical Framework • Year 1: Collecting necessary data, calibrating and validating identified models for a range of conditions, conducting uncertainty analyses to address issues of model uncertainties and demonstrate a range of expected outcomes • Year 2: Large scale assessment of biophysical and economic impacts of climate change for a number of climate change scenarios using predictions based on different GCMs
Key aspects of the project • More holistic assessment of climate change impacts by integrating best of climate-crop-economic aspects of agricultural systems • Building on available data and information • Better understanding of model uncertainties and enhancing their skill • A platform to interact and work closely with global experts and share experiences nationally, regionally and globally • Developing a strong regional working group with skills in climate, crop and economic modelling
Progress to date • Inception workshop was held in August • Country teams proposed initially were strengthened • Methodology and work plans were developed • A blog was created for continuous interaction between team members • Sub-grants agreement are finalized • A training cum workshop planned for October/November 2012 with support from CCAFS
Some constraints • Availability and access to climatic data • Differences in available skills e. g. , no active aqua crop user in some countries • Availability of good quality crop and economic data as required by the crop and economic models • Financial, technical and time limitations
Thanks for your attention
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