gerald nelson senior research fellow, ifpri theme leader, ccafs
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Gerald NelsonSenior Research Fellow, IFPRI
Theme leader, CCAFS
Forestry and Agriculture Greenhouse Gas Modeling ForumWednesday, September 27, 2011
Food Security and Climate Change: Current IMPACT Results and Future
Plans
OverviewFood Security and climate change
results from IMPACTHow we got themHow do we compare with othersShould you believe any of us
Page 2
FOOD SECURITY AND CLIMATE CHANGE RESULTS
Page 3
Nelson, Gerald C., Mark W. Rosegrant, et al. 2010. Food Security, Farming, and Climate Change to 2050: Scenarios, Results, Policy Options. Washington, D.C.: International Food Policy Research Institute.
Food security challenges are unprecedentedMany more people in developing
countries◦Between 2000 and 2050, 50 percent
globally; almost all in developing countriesWith higher incomes comes more
demand for quantity and qualityClimate change – a threat multiplier
with uncertain outcomes◦Reduced productivity of existing varieties
and cropping systems
Page 4
Page 5
Income and population growth drive prices higher(price increase (%), 2010 – 2050, Baseline economy and demography)
Nelson et al, 2010
Page 6
Climate change increases prices even more(price increase (%), 2010 – 2050, Baseline economy and demography)
Minimum and maximum effect from four climate
scenarios
Nelson et al, 2010
Developed Country, Change in Net Exports of Cereals, 2010-2050 (million mt)
Page 7
With climate change, DC net cereal exports grow less or decline.
With perfect mitigation, DC net cereal exports change little between 2010 and 2050.
Countries with more than 1 million hectares of crop area increase, 2010–2050 (000 hectares)
Page 8
Countries with more than 1 million ha of crop area decline, 2010–2050 (000 hectares)
Page 9
2010
2015
2020
2025
2030
2035
2040
2045
2050
Pessimistic scenario
Perfect miti-gation
2010
2015
2020
2025
2030
2035
2040
2045
2050
1,800
2,000
2,200
2,400
2,600
2,800
3,000
3,200
3,400
3,600
Optimistic scenarioKc
als/
day
Developedcountries
All developingcountries
Low-income developing countries
Assessing food security and climate change outcomes
WHERE DO THE RESULTS COME FROM:THE IMPACT MODELING SUITE
Page 11
The IMPACT Modeling Environment
Page 12
Hydrology and Water Supply Demand Models
Climate Scenarios
Crop Models
Partial equilibrium economic model
Supply Side Spatial Resolution:281 Food Production Units
Page 13
Global Food Production Units (281 FPUs)
Change in average annual precipitation, 2000-2050, CSIRO GCM, A1B (mm)
Page 14
Page 15
Change in average annual precipitation, 2000-2050, MIROC GCM, A1B (mm)
Current process for incorporating climate effects on crops into IMPACT
FPU level yield and area projections
FPU boundaries
GCM/SRES scenario climate results are down scaled to 0.5 degree/5 minute resolution
FPU level yield and area projections
FPU boundaries
2000 June average minimum temperature
2050 CSIRO/A2 June average rainfall
Planting months are chosen based on current and future climate conditions
FPU level yield and area projections
FPU boundaries
2000 Rainfed planting month
2050 CSIRO/A2 Rainfed planting month
Soils are represented by 27 generic soil profiles based on the harmonized FAO soil datasets
FPU level yield and area projections
FPU boundaries
Soil profiles color coded by location
The remaining inputs fall under management practices
FPU level yield and area projections
FPU boundaries
Choice of crop variety
Rainfed versus irrigated sources of water
Planting densities, row spacing, and transplanting details
Fertilizer types, amounts, and application dates
DSSAT generates projected yields for each location
FPU level yield and area projections
FPU boundaries
2000 Rainfed maize yield
2050 CSIRO/A2 Rainfed maize yield
SPAM 2000 areas are used to weight the projected yields when aggregating to FPUs
FPU level yield and area projections
FPU boundaries
Rainfed maize physical area in 2000
FPU boundaries and crop model pixel results
FPU level yield and area projections
FPU boundaries
2000 Rainfed maize yield with FPU boundariesin South Asia
Projected yields from DSSAT are aggregated up to the FPU-level for use in IMPACT
FPU level yield and area projections
FPU boundaries
By crop and rainfed/irrigated...
Find total SPAM area within FPU
Find total production (SPAM area × DSSAT yield) within FPU
Compute area-weighted-average yield as total production / total area
Yield Effects, Rainfed Maize, CSIRO A1B (% change 2000 climate to 2050 climate)
Nelson et al, 2010
Yield Effects, Rainfed Maize, MIROC A1B (% change 2000 climate to 2050 climate)
Page 26 Nelson et al, 2010
Corn Yield Change, 2000-2050 (%)CNR GCM, A1 GHG Scenario
Page 27
Illinois -10.1 Indiana -4.1 Iowa -21.3 Minnesota -10.4 Ohio 2.2
Corn Yield Change, 2000-2050 (%)CSI GCM, A1 GHG Scenario
Page 28
Illinois -5.9 Indiana -12.1 Iowa -3.6 Minnesota 12.1 Ohio -10.3
Corn Yield Change, 2000-2050 (%)ECH GCM, A1 GHG Scenario
Page 29
Illinois -8.3 Indiana -12.0 Iowa -9.5 Minnesota -0.9 Ohio -12.0
Corn Yield Change, 2000-2050 (%)MIR GCM, A1 GHG Scenario
Page 30
Illinois -42.7 Indiana -41.3 Iowa -39.6 Minnesota -30.5 Ohio -43.1
HOW DO WE COMPARE WITH OTHERS: COMPARINGIMPACT, ENVISAGE, LEITAP
Page 31
Alternate Perspectives on Price Scenarios (perfect mitigation), 2004-2050
Page 32
IMPACT has substantially greater price increases
Alternate perspectives on agricultural area changes, 2004-2050
Page 33
IMPACT Area Response, at FPU Level
Atni = crop areaα = crop area interceptPStni = producer price ε = area price elasticityWATtni = water stress = exogenous area growth rate
( ) ( ) (1 ) ;ijniintni tni tni tnj tni tni tni
j iA PS PS ga A WAT
tniga
Selected CGE Area Supply Functions• Envisage (World Bank/FAO)
• LEITAP (Wageningen)
• - Asymptote• Ɛ - Price elasticity
Page 35
1 P
SSe
S S P
Aggregate land supply parameters for ENVISAGE and LEITAP
Page 36
Expansion potential
Initial supply elasticity
Region ENVISAGE
LEITAP ENVISAGE
LEITAP
China 1.298 1.174 0.250 0.100India 1.145 1.050 0.250 2.317Canada 2.446 7.870 1.000 1.384United States 2.244 1.843 1.000 1.384Brazil 8.657 3.045 1.000 2.000Russia 2.383 4.461 1.000 0.902Sub-Saharan Africa 5.624 1.893 1.000 1.162EU27 & EFTA 2.019 1.149 0.250 0.170Middle East & North Africa 1.079 1.020 0.250 0.000Australia & New Zealand 3.149 1.380 1.000 0.115High income countries 2.109 1.442 0.472 0.494Developing countries 2.410 1.698 0.537 1.316East Asia & Pacific 1.651 1.891 0.554 0.557Europe & Central Asia 1.896 2.800 1.000 0.968LAC less Brazil and Mexico 8.719 2.017 1.000 1.410World total 2.288 1.594 0.511 0.982
Ratio of all land rated very suitable, suitable, moderately suitable land and marginally suitable land to actual arable land in use
SHOULD YOU BELIEVE ANY OF US:EXAMPLES OF THE QUALITY OF DATA
Page 37
How much irrigated area in India?Intl. Water Management Inst.
113 M ha (net)Government of India
57-62 M ha
Source: Thenkabail 2009
Where do land cover maps disagree on forest and cropland? All colored areas below.
Source: FAO and ILRI (forthcoming 2011)
Where do MODIS v. 5 and GlobCover disagree on crop area globally? All colored areas below.
Source: FAO and ILRI (forthcoming 2011)
COMPARING LAND COVER DATA IN AFRICA
Page 41
Globcover 2005 – (300m)GLC2000 2000 – (1km)MODIS 2001 – (5km)Africover 1999-20 01 – (30m)
Globcover
MODIS
GLC2000
Africover
Kenya
Zhe Guo, HarvestChoice 2011 (unpublished).”
All maps use the same
legend
MODIS
GLC2000Globcover
Uganda Rwanda
Zhe Guo, HarvestChoice 2011 (unpublished).”
Africover
All maps use the same
legend
MODIS
GLC2000Globcover
Tanzania
Zhe Guo, HarvestChoice 2011 (unpublished).”
Africover
All maps use the same
legend
Ethiopia
MODIS
GLC2000Globcover
Zhe Guo, HarvestChoice 2011 (unpublished).”
All maps use the same
legend
What is needed?Regular observations
◦Observations year after yearRepeated observations
◦Multiple observations within a year and across years
Appropriate spatial resolution ◦Similar to field size
Discrimination◦Minimum spectral frequencies to detect
agricultural and natural resource changePage 46
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