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Global Land Use Modeling for Analysis of the Food-Energy-
Water NexusThomas W. HertelPurdue UniversityBuilding on collaborations with
Uris Baldos, Keith Fuglie, Jing Liu, David Lobell, Farzad Taheripour and Nelson Villoria
Presentation to the NSF FEWS workshop, Iowa State University, October 12, 2015
Global scale analysis of FEWS is critical
• We grow food for people & most population growth will be in developing countries
• Projected growth in water demand and scarcity is also highest in developing countries
• Agricultural impacts of climate change will be most severe in tropics
• Environmental degradation is most severe in developing world; also lowest cost mitigation of global environmental externalities (e.g. GHGs)
• In the past we could analyze US agriculture largely isolation; no longer possible due to globalization
Outline
• Conceptualizing the nexus• Modeling cross-system linkages at global scale,
challenges, opportunities:– Water-Food linkages– Adding energy: FEWS– Adding Climate Change
• Knowledge gaps• Data and cyberinfrastructure needs
Biofuels
PumpingCosts
Power Generation
Conceptualizing the FEWS nexus Source: Liu et al. (2014)
Fracking!
Outline
• Conceptualizing the nexus• Modeling cross-system linkages: challenges,
opportunities:– Water-Food linkages– Adding energy: FEWS– Adding Climate Change
• Knowledge gaps• Data and cyberinfrastructure needs
Irrigated Agriculture: The Dominant Water Use
• Each calorie produced requires roughly 1 liter of water through crop evapotranspiration; feeding the world each year requires enough water to fill a canal 10m deep and 100m wide encircling the globe 193 times!
• Four-fifths is rainwater, one-fifth is irrigation water; accounts for 70% of global freshwater withdrawals
• Irrigated area accounts for nearly 20% of cropland and 40% of production
Groundwater irrigation has become increasingly important
• Accessible without large scale government initiatives at low capital cost (although high operating costs)
• Offers irrigation on demand• Reliability in time and space: low
transmission and storage losses• Drought resilience; surface water
not available during drought • If undertaken in areas with high
recharge rates, then it can be sustainable
• Unfortunately this is often not the case
Most rapid growth has been in arid areas with low recharge rates
8Source: cited in Burke and Villholth
What happens when water becomes scarce? The Australian experience
• Drought in 2002/3 led to a 29% drop in water usage in the Murray-Darling Basin
• However, water used in irrigated rice production dropped by 70%
• Early analysis predicted only modest declines in irrigation water usage; missed the potential for:
• Shifting land to rainfed production
• Importing rice from other regions
• Adaptation possible due to introduction of water trading 1980’s
“Flexibility facilitated by water trading: when water is available, produce rice. When it is scarce, sell water rights instead of growing rice!” (Will Fargher, National Water Commission)
Water scarcity
Scarcity at global scale is a larger challengeIndex of irrigation water availability
Year 2030
Increased water scarcity of water for irrigation – particularly in South Asia and China
Source: Liu et al. (2014)
Year 2000
Water scarcity leads to reductions in irrigated area in key producing regions – shortfalls in supply
Source: Liu et al. (2014)
…. Leading to more land conversions and GHGs
Food trade is a key adaptation to water scarcityIndex of irrigation water availability
Year 2030
Year 2000
Increasing water scarcity alters the geography of food trade
Regions facing the most severe water scarcity are most likely to increase net food imports
Source: Liu et al. (2014)
Outline
• Conceptualizing the nexus• Modeling cross-system linkages: challenges,
opportunities:– Water-Food linkages– Adding energy: FEWS– Adding Climate Change
• Knowledge gaps• Data and cyberinfrastructure needs
Biofuels
Predicting land use change and associated GHG emissions from US ethanol
• Estimate induced land use change owing to expansion of US ethanol production from 1.75 bgy to 15 bgy
• Distinguish irrigated and rainfed crop production, by Agro-Ecological Zone
• Unconstrained case: expand irrigation where profitable
Source: Taheripour et al. (2013)
Bulk of irrigated corn in US draws on High Plains aquifers
15Source: NRC report
Yet some of these aquifers are being overdrawn; others are restricting further draw-downs
16
FIGURE 5-13 Usable lifetime of the High Plains Aquifer in Kansas estimated on the basis ofgroundwater trends from 1996-2006 and the minimum saturated requirements to support wellyields of 400 gallons per minute. Source: NAS report, 2011, taken from DOE-EERE.
17
And Water Scarcity is a Global Problem
Source: IWMI website
Land use change and GHG emissions from US ethanol with irrigation constrained in areas of physical scarcity
• When constrain irrigation expansion in water scarce regions:– More expansion of cropland
area (rainfed yields are lower)– Tend to expand more in wetter,
more carbon rich AEZs
• For case of US ethanol-driven expansion we find that ILUC GHG emissions rise by 25% when accounting for future water constraints
Source: Taheripour et al. (2013)
Geography of international trade is also important When USA experiences a supply drop (drought/flooding) or a demand increase (biofuels); where does production respond in the rest of the world?
Predictions (95% CI) of additional harvested area due to 1993 crop shortfall in USA
Naïve, integrated world markets overstates land-based GHG emissions due to US ethanol production by 2x by stimulating too much output in regions with low emissions efficiencies
Source: Villoria and Hertel (2011)
Outline
• Conceptualizing the nexus• Modeling cross-system linkages: challenges,
opportunities:– Water-Food linkages– Adding energy: FEWS– Adding Climate Change
• Knowledge gaps• Data and cyberinfrastructure needs
Climate change is already reducing yields of some crops
Source: AR5, as presented by CSIRO/Mark Howden for the IPCC Food Security Summit, Dublin, May 2015
Impacts vary greatly by crop, location and adaptation actions, but become predominantly negative by 2100
Source: AR5, Fig. SPM.7
Tropics will be hit hardest, agronomic adaptation could play important role
Source: AR5-WGII, Fig. 7-4. Dots show CO2 effects included; X’s ignore this effect.Shaded area represents 95% CI from non-parametric regressions. Adaptation = solelyagronomic adaptation
Adaptation depends on R&D investments: proven means of boosting productivity, but take time to have impact
From year 1 to 24, the contribution of an outlay in year 0 to stock is increasing so incremental TFP index is rising
After the peak year, the contribution of expenditure in year 0 is falling so the growth rate of the incremental TFP is negative, TFP index returns to zero in year 50
Calibrated using best fit model from given U.S. experience from Alston et al. (2011)
Costs of adaptation inherit uncertainty and reflect magnitude of CC impacts…
LPJmL Crop Model
pDDSAT Crop Model
HADGEM IPSL MIROC GFDL NORESM
Global Circulation Models
in B
20
05
US
D$
in B
20
05
US
D$
Source: Baldos et al. (2015)
… which also influence economic returns to adaptation.Bulk of the benefits accrue after 2050.
LPJmL Crop Model
pDDSAT Crop Model
HADGEM IPSL MIROC GFDL NORESM
Global Circulation Models
in B
20
05
US
D$
in B
20
05
US
D$
Source: Baldos et al. (2015)
Climate adaptation also providesenvironmental and food security co-benefits
Climate adaptation generally reducesGHG emissions from cropland conversion
Market integration tends to lead to more extreme outcomes; GHGs
actually rise in two cases
Source: Baldos et al. (2015)
Climate adaptation improves food security
Climate adaptation also providesenvironmental and food security co-benefits (cont’d)
CC adaptation is even more important for food security if market barriers persists
Source: Baldos et al. (2015)
Cost of achieving mitigation through adaptation
All Regions Adapt: $16.7/tCO2e
LAmer and SS_Afr Only Adapt: $36.2/tCO2e
Lobell, Baldos & Hertel, ERL (2013)
Which parameters drive this uncertainty?
(distribution reflects parameter uncertainty)
Top three parameters:- TFP elasticity wrt R&D- Terrestrial carbon factor- Land supply elasticity
Outline
• Conceptualizing the nexus• Modeling cross-system linkages: challenges,
opportunities:– Water-Food linkages– Adding energy: FEWS– Adding Climate Change
• Knowledge gaps• Data and cyberinfrastructure needs
FEWS knowledge gaps• Understanding current institutions and potential for revision of
water allocation rules; crises can precipitate reform!• Current valuation of water, by sector: prices are largely unknown • Analytical frameworks to identify key parameters / econometric
investigations of those parameters– Key parameters depend on the problem being addressed– Contribution to uncertainty depends on current state of
knowledge about the parameter distribution – parameter could be very influential, but distribution is relatively tight so further research is a lower priority
FEWS data needs
• Consistent global, gridded data on rainfed and irrigated areas, yields, and water use, by sector (GEOSHARE)
IWMI (113 Mha)(2001-2003)
Based on remote sensing
FAO (66 Mha)(2008)
Based on census/surveys
Estimates ofirrigated area
in India differ by a factor of two!
Data Workflows on GEOSHARE HUB
• Gridded source data on land cover & use, water, poverty and environment - flows into:
• Data reconciliation ‘models’, which produce usable data - for use in….
• Biophysical and economic models (e.g., DSSAT, IMPACT, SIMPLE, GTAP)Sensitivity of results at final stage determines value of improving quality of source data
Source DataLand Cover
Data Reconciliation:Data Fusion
Water
Poverty
Land Use
Environment
DSSAT IMPACT
1048 stations with at least 3-yrs daily weather data
706 stations with at least 15-yrs daily weather data
126 stations with 15-yrs daily weather data, <10% missing days, and no gaps with >consecutive days
Source: World Meteorological Organization and NOAA Global Summary of the Day database
FEWS data needs
References
