Post on 10-Aug-2020
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
Source: IFPRI, IMPACT version 3.2, September 2015
Maize demand composition (SSP2, NoCC)
Source: IFPRI, IMPACT version 3.2, September 2015
Source: IFPRI, IMPACT version 3.2, November 2015
Sorghum demand composition (SSP2, NoCC)
Groundnut demand composition (SSP2, NoCC)
Source: IFPRI, IMPACT version 3.2, November 2015
Growth in global cereal production (SSP2, NoCC)
Source: IFPRI, IMPACT version 3.2, November 2015
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)
Source: IFPRI, IMPACT version 3.2, September 2015
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)
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
Cereals
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;
Maize Wheat
Climate change impacts on yields after economic responses (SSP2)
Rice
Sorghum Groundnut
Impacts of socioeconomic and climate drivers on cereal prices
Source: IFPRI, IMPACT version 3.2, September 2015
Climate change Population and income
Net cereal trade and climate change (SSP2)
Source: IFPRI, IMPACT version 3.2, November 2015
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)
Source: IFPRI, IMPACT version 3.2, November 2015
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 groundnut trade and climate change (SSP2)
Source: IFPRI, IMPACT version 3.2, November 2015
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
Population at risk of hunger (SSP2, RCP8.5)
Source: IFPRI, IMPACT version 3.2, November 2015
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
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