Climate Smart Village: Futuristic multi-model approach

Customizing adaptation packages to reduce vulnerability to climate change

Using a multi-model framework for climate, crop, livestock and socio-economic simulation, customized climate change adaptation packages were developed for farmers in Nkayi, Zimbabwe. The computer-simulated scenarios are helping policy makers to make crucial decision to support farmers.

The challenge

Hit by two consecutive droughts, farmers in Zimbabwe are reeling under the impact of unpredictable climate. The situation is much worse in Nkayi district, one of the sites of this project. Statistics show that this district has the highest poverty prevalence in Zimbabwe.

Future scenarios predict that 60% of farming households will be exposed to greater vulnerability due to an estimated 2 -3.°5C* rise in temperature. Researchers say that the time to begin equipping Nkayi farmers to face a grim 2050 climate scenario is now.

Building on the lessons learnt from Phase I of the project, the Phase II interventions aimed at tailoring drastic adaptation packages to suit farm types. To substantiate the benefits of this package over the blanket technology packages in use, the following interventions were made.


Assessing vulnerability to Climate Change
Researchers modeled scenarios for

  1. Incremental Change package 
  2. Radical Change package for three farm types

A multi-model framework with climate, crop, livestock and socio-economic components was used to create scenarios.

Climate data - GCMs3
Historical (1980-2010) Mid century
Projected changes in temperature, precipitation

Crop model - APSIM 4 & DSSAT5
Crop management: fertilizer, rotation, varieties,…
Effects on on-farm crop production;
rangeland grass production

Livestock model - LivSim
On-farm feed production; rangeland biomass
Effects on livestock production
(milk, off-take, mortality rates)

Economic model - TOA-MD6
Household characteristics, agricultural production prices, costs
Economic effects of climate change and adaptations on entire farms

(Left picture) In the face of climate change, the most appropriate and profitable crops, based on robust researchinformation, must be promoted at the local and national scale. (Right picture) Some farmers have already shifted from maize to more drought tolerant sorghum. Photos: Sabine H, ICRISAT

Establishing stakeholder networks

Stakeholder networks were mapped to bring together expertise on crops, livestock, markets, environment, climate change, agricultural extension and rural development.

Communication channels were designed at national and sub-national scales for leveraging synergies from improved access to markets, technologies and subject expertise.

Co-designing pathways - define future scenarios

Information exchange among stakeholders and researchers was through AgMIP Impact Explorer, a web-based tool used for scenario and information visualization and documentation. Together they defined future biophysical and socio-economic conditions that were contrasted based on optimistic and pessimistic assumptions.

Scenarios were followed up with expert discussion, external review and stakeholder feedback to design the adaptation package.

Adaptation package

Adaptation packages were designed for the below

three categories:

  • Very poor: Farm size 1.3 ha; no cattle
  • Poor: Farm size 1.8 ha; 8 cattle or less
  • Better-off: Farm size 2.5 ha; more than 8 cattle

The key features of the packages are –

  • Crop diversification:
    • Less maize and more groundnuts for better soil
    • fertility, family nutrition and income
    • Drought-tolerant sorghum for ‘Very poor’
    • Dual purpose forage mucuna pruriens to
    • support livestock and improve soil fertility
    • Other crops: Common beans (for Very poor), Banagrass (for Better-off).
  • Fertilizer microdosing: For increased yields
  • Livestock: More cattle and small ruminants for economic gain
  • Milk production: Protein rich fodder from mucuna and groundnut haulms increases milk yield.

For incentivizing farmers for adoption of the adaptation package large-scale measures need to be taken by policy makers and key stakeholders for linking farmers to markets and integrating crop and livestock production.

Increase/decrease in adaptive package when compared to farmers' practice in three farm types

Drought and disease tolerant fodder legume mucuna pruriens enriches the soil in nitrogen and provides valuable protein-rich fodder resources for the farmer. Photo: P Masikati, ICRAF

AgMIP projections show that poverty will reduce significantly if climate smart technologies are adopted; yet many, especially those without livestock will remain poor. Photo: S Homann, ICRISAT

Evaluated impact of drastic adaptation packages on net returns:

Very Poor: Will double their returns

Poor & Better-off: Will increase by 50-75%

Entire community: Will see an 86% increase on net returns as compared to 72% for incremental technologies

Projected impact

  • Poverty levels might remain high, even after drastic economic changes and tailored investments.
  • Substantial change in poverty rates will be for those with large cattle herds.

2015 Impact

The impact of climate change is hard to quantify and policy makers find it difficult to estimate the cost of the interventions needed to combat it. In this case computer-simulated scenarios gave policy makers a picture of what was ahead helping them make necessary decisions.

Greater support for groundnut value chains

With the support of the Government of Zimbabwe, ICRISAT imported 20 tons of groundnut seed from Malawi, which was distributed to farmers for seed multiplication and testing.

This was in response to Nkayi farmers demand for quality certified seeds and also in line with scientists’ recommendations for reviving groundnut cultivation given its high market demand and its use as nutritious feed, fodder and soil enriching properties.

More at:

Promoting sorghum and millet

Recognizing the need to promote more drought tolerant crops, the Government of Zimbabwe has set the purchase price for sorghum and millet to equal maize.