global futures & strategic foresight -...

Global Futures & Strategic Foresight Quantitative modeling to inform decision making

in the CGIAR and its partners

Keith Wiebe (IFPRI) and S. Nedumaran (ICRISAT)

ICRISAT, Patancheru, 1 February 2016

Outline

• Introduce the Global Futures & Strategic Foresight (GFSF) program

• Share some recent projections from the IMPACT model

• Describe some of the work that ICRISAT is doing as part of GFSF

• Reflect on how we might help inform decision making in the CGIAR

Drivers of change

• Today, this season, this year • Weather, pests, markets, conflict, migration…

• Medium term • Agricultural policies, trade policies, markets…

• Long term • Population, income, resources, climate, preferences,

technology…

Socioeconomic and climate drivers

Shared

Socioeconomic

Pathways (SSPs)

Representative

Concentration

Pathways (RCPs)

Source: Downloaded from the RCP Database version 2.0.5 (2015). RCP 2.6: van Vuuren et al. 2006; van Vuuren et al. 2007. RCP 4.5: Clark et al. 2007; Smith and Wigley 2006; Wise et al 2009. RCP 6.0: Fujino et al 2006; Hijioka et al 2008. RCP 8.5: Riahi and Nakicenovic, 2007.

CO2 equiv. (ppm) Radiative forcing (W/m2)

Population (billion) GDP (trillion USD, 2005 ppp)

Global Futures & Strategic Foresight

1. Improved tools for biophysical and economic modeling

2. Stronger community of practice for scenario analysis and ex ante impact assessment

3. Improved assessments of alternative global futures

4. To inform research, investment and policy decisions in the CGIAR and its partners

1. Improved modeling tools • Complete recoding of IMPACT v3

• Disaggregation geographically and by commodity

• Improved water & crop models

• New data management system

• Modular framework

• Training

2. Stronger community of practice

• All 15 CGIAR centers now participate in GFSF • AfricaRice, Bioversity, CIAT, CIFOR,

CIMMYT, CIP, ICARDA, ICRAF, ICRISAT, IFPRI, IITA, ILRI, IRRI, IWMI, WorldFish

• Collaboration with other global economic modeling groups through AgMIP • PIK, GTAP, Wageningen, IIASA, UFL,

FAO, OECD, EC/JRC, USDA/ERS, …

• Role of agricultural technologies

• Africa regional reports

• CCAFS regional studies

• Analyses by CGIAR centers

• AgMIP global economic assessments

• Private sector

Rainfed Maize (Africa)

Irrigated Wheat (S. Asia)

Rainfed Rice (S. + SE. Asia)

Rainfed Potato (Asia)

Rainfed Sorghum (Africa + India)

Rainfed Groundnut (Africa + SE Asia)

Rainfed Cassava (E. + S. + SE. Asia)

3. Improved assessments

4. Informing decisions

• National partners • Regional organizations • International organizations

and donors • CGIAR

• Centers • CRPs • System level?

Impacts of socioeconomic drivers to 2050 Average of 5 global economic models for coarse grains, rice, wheat, oilseeds & sugar

0

10

20

30

40

50

60

70

80

90

100

Yields Area Production Prices Trade

Perc

ent

chan

ge f

rom

20

05

to

20

50

SSP1 SSP2 SSP3

Source: Wiebe et al., Environmental Research Letters (2015)

Climate change impacts in 2050 Average of 5 global economic models for coarse grains, rice, wheat, oilseeds & sugar

-10

-5

0

5

10

15

20

Yields Area Production Prices Trade

Perc

ent

chan

ge in

20

50

SSP1-RCP4.5 SSP2-RCP6.0 SSP3-RCP8.5

Source: Wiebe et al., Environmental Research Letters (2015)

IMPACT model: selected results

• Food demand

• Yields

• Prices

• Trade

• Food security

Changing composition of diets (SSP2, NoCC)

Source: IFPRI, IMPACT version 3.2, November 2015

WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean; MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa

Growth in total global demand (SSP2, NoCC)

20

10

= 1

.0

Source: IFPRI, IMPACT version 3.2, September 2015

Growth in total global demand for cereals (SSP2, NoCC)

20

10

= 1

.00


Maize demand composition (SSP2, NoCC)



Sorghum demand composition (SSP2, NoCC)

Groundnut demand composition (SSP2, NoCC)


Growth in global cereal production (SSP2, NoCC)


Growth in cereal production by region (SSP2, NoCC)

World Latin Am & Caribbean

South Asia Sub-Saharan Africa Source: IFPRI, IMPACT version 3.2, September 2015

Growth in global production of pulses and oilseeds (SSP2, NoCC)


Pulses Oilseeds

Modeling climate impacts on agriculture: biophysical and economic effects

General

circulation models (GCMs)

Global

gridded crop models

(GGCMs)

Global

economic models

Δ Temp Δ Precip

…

Δ Yield (biophys)

Δ Area Δ Yield Δ Cons. Δ Trade

Climate Biophysical Economic

Source: Nelson et al., Proceedings of the National Academy of Sciences (2014)

Climate change and yields in 2050 before economic responses (HadGEM2, RCP 8.5, no CO2 fert)

Source: IFPRI DSSAT simulations

Rainfed sorghum

Irrigated sorghum

Rainfed groundnut

Irrigated groundnut

Climate change impacts on cereal yields after economic responses (SSP2)


WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean; MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa

Cereals


WLD = World; EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean; MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa;

Maize Wheat

Climate change impacts on yields after economic responses (SSP2)

Rice

Sorghum Groundnut

Impacts of socioeconomic and climate drivers on cereal prices


Climate change Population and income

Net cereal trade and climate change (SSP2)


EAP = East Asia and Pacific; EUR = Europe; FSU = Former Soviet Union; LAC = Latin America and Caribbean; MEN = Middle East and North Africa; NAM = North America; SAS = South Asia; SSA = Sub-Saharan Africa

Net sorghum trade and climate change (SSP2)



Net groundnut trade and climate change (SSP2)



Population at risk of hunger (SSP2, RCP8.5)



Exploring the impacts of improved technologies and practices on…

-40.0

-35.0

-30.0

-25.0

-20.0

-15.0

-10.0

-5.0

0.0

Malnourished Children Pop. at-risk-of-hunger

No till Drought tolerance Heat tolerance

Nitrogen use efficiency Integrated soil fertility mgt Precision agriculture

Water harvesting Sprinkler irrigation Drip irrigation

Crop Protection - insects

Source: Rosegrant et al. (2014)

Food security (Percent difference from 2050 CC baseline)

Source: Islam et al. (draft)

Crop yields (Percent difference from 2050 CC baseline)

Global Futures & Strategic Foresight

in ICRISAT

GFP activities integrated in CRP-PIM

Multidisciplinary team created and institutionalized (14 member team)

Supporting priority setting, foresight and scenarios analysis for CRP DC and GL

Promising technologies were identified and prioritized for evaluation

Collaboration with other CRPs and Global Projects like AgMIP (data sharing, model enhancement, capacity building)

Global Futures and Strategic Foresight @ ICRISAT

Multi-disciplinary team @ ICRISAT

• Cynthia Bantilan, Nedumaran, Kai Mausch

• R Padmaja Economists

• Ashok Kumar, SK Gupta, CT Hash, PM Gaur, P Janila, Ganga Rao, Jana Kholova

Breeders and Physiologists

• Dakshina Murthy

• Gumma Murali Krishna Crop Modelers/GIS/RS

Imp

act

Ass

ess

me

nt

Effects of Promising Technologies on the Impact of Climate Change on Yields in 2050

Rainfed Maize (Africa)

Irrigated Wheat (S. Asia)

Rainfed Rice (S. + SE. Asia)

Rainfed Potato (Asia)

Rainfed Sorghum (Africa + India)

Rainfed Groundnut (Africa + SE Asia)

Rainfed Cassava (E. + S. + SE. Asia)

Robinson et al. 2015

Technology Development and Adoption Pathway Framework

2012 2018 2035

India 60%

Nigeria 40%

2037 2020

Research lag Adoption lag

Promising Technologies of Groundnut development

Technology development Technology dissemination and

adoption Outcomes and

Impacts

• Change in Production

• Change in prices • Change in

consumption • Poverty level

Nedumaran et al. (2013)

Target countries

Target countries Production share (%)

Burkina Faso 1.2

Ghana 1.62

India 12.99

Malawi 0.7

Mali 1.01

Myanmar 3.84

Niger 0.51

Nigeria 10.72

Tanzania 1.73

Uganda 0.76

Vietnam 1.84

Total 36.92

Potential Welfare Benefits and IRR (M US$)

Technologies Net Benefits

(M US$) IRR (%)

Heat Tolerant 302.39 30

Drought Tolerant 784.08 38

Heat + Drought + Yield

Potential 1519.76 42

Nedumaran et al. (2013)

0

50

100

150

200

250

300

350

Malawi Tanzania Uganda BurkinaFaso

Ghana Mali Nigeria Niger India Myanmar Vietnam

ESA WCA SSEA

M U

S$

Heat Tolerance Drought Tolerance Heat+Drought+yield potential

Ongoing Work - Spatial Modeling for better targeting and impact evaluation

Updating of soil and precise sowing window raster to improve better yield simulations and to identify vulnerable areas

Simulation of impacts of drought, heat tolerance, and yield boost virtual cultivars under climate change using the updated soil and sowing window raster

Collection of grid wise daily weather data from India meteorological department (IMD) to further improve the precision of simulations

Way forward

Evaluate the additional promising technologies (biotic stress tolerant and management options) with current GF/PIM Strategic foresight tool

Provide scenario analysis and evidence to better targeting of technology and inform priority setting for CRP – DCL AFS

Consider linking results from global models with household data for ex ante impact assessment at lower scales

Engage with regional and country level stakeholders and support them in scenario analysis and country strategies

Gender lens in foresight analysis and technology evaluation

4. Informing decision making

• National partners

• Regional organizations

• International organizations and donors

• CGIAR • Center work planning • CRP Phase 2 proposals

• PIM, Maize, Rice et al. • System level?

• ISPC and donor interest

The CGIAR Research Agenda

System Level Outcomes (SLOs) and Intermediate Development Objectives (IDOs)

Increased resilience of the poor to

climate change and

other shocks

Enhanced smallholder

market access

Increased incomes

and employment

Increased productivity

Improved diets for poor and

vulnerable people

Improved food safety

Improved human and

animal health

through better

agricultural practices

Natural capital

enhanced and

protected, especially

from climate change

Enhanced benefits

from ecosystem goods and

services

More sustainably managed

agro-ecosystems

Reduced Poverty

Improved natural resource systems

and ecosystem services

Improved food and nutrition security

for health

Model improvements under way

• Livestock and fish

• Nutrition and health

• Land use

• Environmental impacts

• Variability

• Gender

• Poverty

Concluding thoughts

• Opportunity to inform decision making in the CGIAR and its partners • Quantitative model results as one input among several

• Collective effort, involving all 15 CGIAR centers (and other partners)

• Multiple scales of analysis

• On-going effort to build capacity and a community of practice to assess options over time

• Looking forward to collaboration with IRRI

Thank you

[email protected]

mailto:[email protected]

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