Household modeling for ex-ante

evaluation and targeting of climate

smart agriculture

Mario Herrero

CCAFS Science Meeting, Copenhagen, May 2012

At ILRI: Mariana Rufino, Mark van Wijk, Carlos Quiros

CCAFS theme leaders: Philip Thornton (funding/strategy),

Jim Hansen, Lini Wollenberg, Andy Jarvis

CCAFS Regional Coordinators (funding): James Kinyangi

(EA), Robert Zougmore (WA), Pramod Aggarwal (SA)

CG centres: IWMI, ICRISAT, CIMMYT, ICRAF (for now)

Universities and Research Centres: Wageningen,

Hohenheim, Tasmania, Oregon, Washington State (for now)

This work involves many others

CCAFS engaged heavily in analysing regional and global

impacts on agriculture and exploring future pathways of

agricultural development through scenario analysis

Considerable work on adaptation and mitigation practices at a

local level

Ex-ante assessment and targeting: what might work where

and how this might change depending on the notions of the

future

Household modelling: offers the possibility of helping with

these issues.

A well established area, large community of scientists

Not widely used in climate change activities yet.

Background

W. Africa 1966 – pastoral system 2004 – crop-livestock system

Systems and livelihoods in transition: the target is moving! Can we ensure that the next transition is sustainable, equitable and helps

feed the world?

National

Production

Mixed

rainfed

temperate

Mixed

rainfed

humid

Mixed

rainfed

arid

2030 2050 2030 2050 2030 2050 2030 2050

Burundi 9.1 9.1 14.4 18.1 -1.8 -8.8 - -

Kenya 15.0 17.8 33.3 46.5 -4.6 -9.8 -1.1 -8.4

Rwanda 10.8 14.9 13.4 18.8 5.4 3.6 1.1 2.7

Tanzania -3.1 -8.1 7.5 8.7 -1.6 -6.4 -5.1 -11.1

Uganda -2.2 -8.6 4.9 3.1 -4.6 -12.9 -1.1 -6.3

A game of winners and losers…at all scales Simulated percentage maize production changes to 2030 and 2050, by

country and system

Mean of 4 combinations of GCM and emissions scenario

Thornton et al. (2010)

Winners

Losers

Understanding complex systems

Herrero et al, Science (2010)

J F M A M J J A S O N D

Rainy Dry Dry

Groundnuts

Yams

Sorghum

Grazing Critical Crop

residue

Cut &

Carry

Prot. & Ene.

deficit Food security

Energy

deficit Family’s

nutrition

Feeding calendar

Cropping calendar

Weather calendar

Monthly calendar of different activities of the system

Cash demands Very

high Low High High Low Lo

w

High High

Wa, Upper West, Ghana

Gonzalez-Estrada et al. 2006

0

0.5

1income

food security

GHGwater use

external inputs

mixed

pastoral

There are always trade-offs Different practices…

Different farming systems….

Plot Crop

Homestead Enset, coffee, kale, sweet potato, maize

Plot1 Maize

Plot 2 Sweet potato, wheat

Plot 3 Maize

Plot 4 Sweet potato

Plot 5 Barley

Plot 6 Maize

Plot 7 Unimproved pasture

What’s the likely impact of alternative

interventions?

Site: Sodo, Ethiopia

Profit: Birr 2,381/yr Livestock: 1 cow, 1 ox

Site: Sodo, Ethiopia

Critical Adequate

Current

management

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Site: Sodo, Ethiopia

Critical Adequate

Intervention 1

Food crop Application of fertilizer to

maize plots.

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Site: Sodo, Ethiopia

Critical Adequate

Intervention 2

Feed crop Replace native grassland

with improved pasture.

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Site: Sodo, Ethiopia

Critical Adequate

Intervention 3

Food/feed crop Introduction of cowpea in

the system.

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Site: Sodo, Ethiopia

Critical Adequate

Intervention 4

Food crop Subsidy for barley

production

Adaptation, risk management and

mitigation options will depend largely

on how we shape the world

• Several options exist though largely dependent on our vision of world development and how it plays out in different regions

• essential to link household modelling to scenarios of change

• Different paradigms of agricultural development (industrial vs pro-poor smallholders, large vs family farms)

• Globalisation and trade patterns

• Consumption patterns

• Carbon constraints

• Roles and incentives for technology adoption

• Growth in other sectors

• Power relationships

Global Scenarios

Regional Scenarios

Farmer/village

perspectives Action research

Participatory

scenario building

Global visioning

activities

Global impacts

modelling

Regional impacts

modelling

Household &

community

impacts modelling

Linking research at different levels

Thornton et al 2012

Ex-ante analysis and targeting of

options

• Studying livelihoods transitions

• Targeting the vulnerable (winners and losers)

• Which options could fit in which systems under which conditions?

• How upscalable to broader recommendation domains/regions?

• How robust are options across scenarios and farming systems

• Priority setting for investments (how many farmers, what areas, how much?)

• Mitigation / adaptation synergies

CCAFS activities in relation to

household modelling

Household data collection in the CCAFS sites

• Development of simplified, but robust and standard data collection protocols

• Collecting detailed information from representative farming systems from the CCAFS sites

• 150-200 households per site: approx 3000 surveys

• Data collection during 2012

• Statistical analysis and modelling of adaptation, risk management and mitigation options from 2012 (with input from centres and themes)

• Funded by Theme 4 and the regions

All survey materials and data at ccafs.cgiar.org/resources/baseline-surveys Dataverse at dvn.iq.harvard.edu Adaptation and Mitigation Knowledge Network at amkn.org

CCAFS sites in West Africa, East Africa and South Asia

Data collection + household modeling protocol :

Climate

Family structure/gender

Land management

Livestock management

Labour allocation

Family’s dietary pattern

Farm’s sales and expenses, income

Herrero et al 2007

A review of farm household modelling with a focus on climate change

• A systematic review of 16000 thousand references

• Covered long term adaptation, risk mangement and mitigation

• Covered diverse modelling techniques (LP, agent based models, simulation, others)

• Identification of useful tools for CCAFS work

• Integrated models using more than one modelling technique more suitable for CC questions

• Engagement with other modellers

Workshop: Farm-household Modeling with a focus on Food security, Climate change adaptation, Risk management and Mitigation: a way forward

• Goal: to identify current potential of and weaknesses in farm- and household-level models, and laying out practical pathways to improve these models to address CCFAS systems questions

Amsterdam, The Netherlands 23 to 25 April 2012

Conclusions from the workshop • Modelling approaches are available to address household-level

questions. This needs to include higher levels of integration to capture key drivers.

• It is possible to analyze household-level questions related to climate change in a reasonable short time (6 months to 1 year) span with the existing tools.

• Activities to develop repositories for models and data are urgently needed to increase further development of models and make better use of existing knowledge.

• A team of modellers with different expertise is needed to address questions related to climate change agriculture and food security.

• The research questions must lead to the suite of models and expertise needed. Not much model development is needed.

Next steps

• Continue the data collection in the regions

• Develop suitable databases and repositories for the information for open access by CCAFS and partners

• Data analyses

• Linking with the international household modelling teams to prepare potential tools for analysis

• Extensions to community-level modelling

• Maybe fund some additional development as needed

Conclusions

• Household modelling can play a key role in the ex-ante evaluation and targeting of adaptation and mitigation work of CCAFS

• It can help link work at multiple-scales: for example the scenarios work in the regions to impacts and options in different types of farming systems

• It can lead to robust multi-centre and multi-theme work by exploiting complementary skills to solve complex problems

• ….and provide realistic, sometimes simplified, answers

Thank you