East Africa

 

 

Overview of Initiative

 

The East Africa research region targets study areas within Tanzania, Uganda, and Kenya. East Africa is susceptible to climate change implications that include: the warming of sea surface temperatures and subsequent droughts; changes in precipitation frequency and amount; more extreme events; and increased food insecurity. Focusing attention on region specific adaptation and mitigation methods is vital for projecting future climate impacts.

The overall goal of Phase 2 (2015-2017) was to assist East African countries in managing climate change and variability related vulnerabilities through the integration of science based knowledge. This knowledge will be used to assist in national and local climate change adaptation strategies and action plans. East Africa built on Phase 1 research by developing full Regional Integrated Assessments (RIAs) based on sound scientific knowledge, integrating new knowledge into national and sub-national adaptation plans, and building capacity and robustness of analytical frameworks and tools. These assessments were co-developed through scientific sources and stakeholder engagement for the purpose of finding and presenting relevant findings to decision makers. This integration helped promote the usefulness of AgMIP’s tools and protocols for other applications, including food security, seasonal forecasting, and early warning systems.

Team members from Kenya, Tanzania, Uganda and Ethiopia comprise the East Africa Team. The project assessed impacts of climate variability and change on smallholder agricultural systems using calibrated climate, crop, livestock, and economic models. These impacts are assessed through comprehensive RIAs of climate change impacts on both the local and national scale with socio-economic scenario analysis. The East Africa team further advanced regional assessments for Uganda and Ethiopia (from Phase 1), while also upscaled its approach to a national level for Kenya and Tanzania.
Collaboration with stakeholders was made possible through the existing CCASA East-Africa network. Key stakeholders were engaged regularly throughout the project. Through CCASA East-Africa network engagement, the project expanded, and will continue to expand, stakeholder uptake and utilization of project outputs.

 

Impacts Explorer – Kenya

Small maize farms in varied agro-ecological zones

View the Regional Summary for Kenya here.  

View the Spatial Dashboard for Kenya here.  

East Africa Team members

Lieven Claessens: Lead PI

Siza Tumbo: Co-PI

Gummadi Sridhar: Co-PI

Anthony Esilaba: Kenya coordinator

Moses Tenywa: Uganda coordinator

Caleb Dickson: Economic modeling; ARP

Fikadu Getachew: Crop modeling

Jemal Seid: Climate modeling

Adam Bekele: Economic modeling

Mary Kilavi: Climate modeling

Joseph Miriti: Crop modeling

Anthony Oyoo: Economic modeling; stakeholder interaction

Khamaldin: Mutabazi Economic modeling; TOA-MD

Ibrahim Kadigi: Economic modeling; TOA-MD

Barnabas M. Msongaleli: Crop modeling

Peter Mlonganile: Climate

David D. Maleko: Livestock

Majaliwa Mwanjalolo: Crop modeling

Patrick Musinguzi: Crop modeling

Josephine Nampiija: Crop Modeling

Carol Nandozi: Climate

Jackline Bonabana-Wabbi: Economics modeling; TOA

Kelvin Shikuku: RIA, TOA, economics

Caroline Mwongera: RIA, TOA, bio-physical

John Recha: Stakeholder liaison

Maren Radeny: Stakeholder liaison

 

Research Summary:

 

KENYA, NATIONAL

Crops: Maize
Models: DSSAT, APSIM, LivSim
Farm System: Maize based
Economic Strata: High potential-low potential, AEZ
Possible Adaptation: Improved maize and bean varieties; alternative crops (e.g. sorghum, legumes, etc)

WOTE, EASTERN KENYA

Crops: Maize, cowpea/beans, sorghum, pigeon pea
Models: DSSAT, APSIM, LivSim
Farm System: Mixed crop-livestock system using crop residue as livestock feed
Economic Strata: Farms with livestock integration, Farms without livestock integration
Possible Adaptation: Climate smart agriculture practices including: high grain and residue yielding sorghum for improved feeding, tightening of Nitrogen cycle, dryland crop and cultivar choices

RAKAI, KAGERA BASIN, UGANDA

Crops: Maize
Models: DSSAT and APSIM
Farm System: Maize, beans, banana
Economic Strata: To Be Determined
Possible Adaptation: CSA adaptation package

LUSHUTO, WEST USAMBARA, TANZANIA

Crops: Maize
Models: DSSAT, APSIM, LivSim
Farm System: Maize, bean, horticulture, livestock
Economic Strata: Livestock
Possible Adaptation: CSA adaptation packages

WAMI BASIN, TANZANIA

Crops: Maize
Models: DSSAT, APSIM, LivSim
Farm System: Maize, rice, sesame, sorghum, millets, legumes
Economic Strata: 2 livelihood zones
Possible Adaptation: Fertilization and plant population changes

ALBERTEN RIFT (HOIMA & MASINDI, UGANDA

Crops: Maize
Models: DSSAT and APSIM
Farm System: Maize-beans-groundnuts-cassava-banana
Economic Strata: 3 soil types
Possible Adaptation: Agronomic practices; short and long maturing varieties; stakeholder workshop planned to elicit near-term adaptation options

KEY PARTICIPATING INSTITUTIONS

 The International Crops Research Institute for Semi-Arid Tropics (ICRISAT) – Kenya 
The Ethiopian Institute of Agricultural  Research 
The Kenya Meteorological Society 
Kenya Agriculture and Livestock Research Organization 
Sokoine University of Agriculture, Tanzania 
Makerere University, Uganda 
International Center for Tropical Agriculture  (CIAT) 
Climate Change, Agriculture, and Food Security (CCAFS) Research Program – Kenya