A novel methodology for ex ante assessment of

climate change adaptation strategies: examples

from East Africa

Lieven Claessens

John Antle, Jetse Stoorvogel, Roberto Valdivia,

Philip Thornton, Mario Herrero

Research methodology:

Tradeoff Analysis model for Multi Dimensional Impact Assessment (TOA-MD)

Bio-economic model for integrated assessment of agricultural systems

Assessing environmental and economic sustainability of technologies and policies.

Linking stakeholders with research teams.

Using quantitative impact assessment tools and models.

Population of farms (variation), not a ‘representative farm’

Simulates CC impacts and benefits of adaptation.

• Public stakeholders

• Policy makers

• Scientists

Identify indicators and scenariosIdentify indicators and scenarios

Coordinated Disciplinary ResearchCoordinated Disciplinary Research

Evaluate results with stakeholdersEvaluate results with stakeholders

• Downscale GCM and RCM output

• Prepare crop and livestock models

• Prepare economic data and models

• Prepare environmental data and models

• Set up scenarios for simulation

• Implement analysis using TOA software

TOA-MD for climate change impact assessment

farmers, extension workers, local community leaders

Technologies: e.g. dual-purpose sweet potato,

drought resistant potato,

improved livestock breeds/management,…

Policies: e.g. investment in irrigation, infrastructure,

fertilizer subsidies, greenhouse gas mitigation

policies,..

Income (poverty)

Malnutrition

Disciplinary research:

Global Circulation Models (GCM) and Regional Climate Model (RCM) data

Downscaled GCM + emission scenarios (150 - 300 km to 25 - 10 km)

RCM: REMO model for East Africa (Max Planck Institute for Meteorology Hamburg)

Daily data,1950 – 2050, 2 IPCC emission scenarios (A1B and B1)

Downscaled data as inputs for crop growth, livestock and pest models

Disciplinary research:

Crop and livestock models

Crop growth simulation models for simulating CC impacts

Parameterization of crop models with existing or prospective technologies

Development and inclusion of pest related model components (late blight, potato

tuber moth,..) + vector population parameters sensitive to CC

CC effects on livestock productivity

Disciplinary research:

Economic models

Economic model uses distribution (variability) of economic data from the farm

population (resource and land allocation, prices of inputs and outputs, net returns,…)

Changes in crop and livestock productivity drive economic models, ‘adoption’

(economic feasibility) and poverty rates.

Disciplinary research:

Scenario construction and TOA-MD software

Scenarios: current system with perturbed climate and adaptation strategies

Evaluation of stakeholder defined impact indicators - changes in farm income

- poverty measures

- nutrition and food security indicators

- environmental indicators

Results from completed and ongoing work

Project study sites in East Africa:

Kenya: Embu, Mbeere,

Machakos, Makueni,

Vihiga

Uganda: Soroti, Kabale, Pallisa,

Nakaseke

Ethiopia: Holetta, Shashemene

Results from completed and ongoing work

Some results for Kenya:

Mixed (crop-livestock) semi-subsistence agricultural systems, high poverty rates:

VIHIGA, western province Kenya

MACHAKOS-MAKUENI, eastern province Kenya

Study areas

Materials and Methods:

SURVEY DATA

- Survey data (quantities and prices) on inputs (such as seeds, labor, fertilizer,

manure), outputs (crop yields, milk production and land areas), and farm management.

- 120 farms for each study area.

CLIMATE PROJECTIONS & EFFECTS ON PRODUCTIVITY

- 2050, IPCC 4AR, WorldCLIM, combinations of GCMs HadCM3 & ECHam4 with

SRES scenarios A1FI & B1 (very high and low emissions).

- Projections from RCM (REMO, MPI-M) currently being analyzed.

- DSSAT crop growth models for maize and beans. Estimations for other crops.

- Livestock: decline in milk yield due to increased heat stress and decreased farm

produced feed.

Materials and Methods:

EXAMPLES OF ADAPTATION STRATEGIES TESTED

- Improved, drought tolerant maize variety.

- Introduction of dual-purpose sweet potato with varying yield levels.

- Improved livestock breeds and feed quality (high crude protein content sweet potato

vines).

TOA-MD Model setup:

• Stratify population if useful (e.g. dairy, farm size, irrigation,…)

• Systems characterized by different activities (crops, livestock, aquaculture)

• Parameterize base and alternative systems with survey and simulation results

• CC effects on productivity in alternative system

• Simulate impacts of different adaptation strategies

• Socio-economic scenarios: Representative Agricultural Pathways (RAPs)

TOA-MD Model setup:

TOA-MD results: CC impact and adaptation

TOA-MD results: CC impact and adaptation

Some TOA-MD results for Vihiga and Machakos:

• 82% of farms in Vihiga and 60% in Machakos negatively impacted by CC

• Poverty rates from 62% to 69% for Vihiga, from 73% to 78% for Machakos

• Introduction of improved maize very limited effect in Vihiga but reducing

negatively affected farms to 49% in Machakos

• Low yielding DP sweet potato offsets CC effects in Machakos

• Vihiga needs high yielding DP sweet potato and improved livestock breeds

to offset CC effects

• Dairy farmers have highest incomes and benefit most from adaptation

Discussion & Conclusion

• Assumptions had to be made in climate change and adaptation scenarios.

• Uncertainty in GCMs, SRES scenarios, downscaling and crop growth and

livestock simulation models.

• Climate variability and pests and diseases not yet included in analysis.

• Adoption rates based on economic feasibility, providing upper bound for real

adoption.

• The TOA-MD approach offers a rapid integrative analysis for exploring options

and timely advice to farmers and policymakers.

THANK YOU!

www.tradeoffs.oregonstate.edu