Land Use Simulation in AgLU
AgLU::
Advanced Methods
Ron Sands
Man-Keun Kim
Man-KeunKim
Joint Global Change Research InstituteBattelle – PNNL – University of Marylandth AIM International Workshop
11thTsukuba, Japan
19 February 2006

Acknowledgements
PNNL Colleagues
z Jae Edmonds, Marshall Wisez Cesar Izaurralde, Allison Thomson

Kenny Gillingham
Geoff Blanford
z Statistics of land allocation mechanismz Data for U.S. land classes

U.S. Environmental Protection Agency

2

Overview
Energy Model Forum (EMF-22) Land UseSubgroup
Modeling Approaches
PNNL Agriculture and Land Use Model (AgLU)z Brief historyz Land allocation mechanismz AgLU treatment of forestsz Typical scenarios

Disaggregation into land classes
How can can we improve agriculture and forestry
representation in CGE models?
3EMF-22 Land Use Subgroup
EMF-22Meetingsz Stanford, May 2005: methodologyz Washington, February 2006: methodology and a few

scenarios

Intended Productsz 1st set of papers on methods and baseline scenarios
z 2nd set of papers on mitigation and impacts

Type of Models Participatingz Ag/Forestry (single country)z Global partial-equilibriumz Global general-equilibrium

4Approaches
Intertemporal Optimizationz

Typical for sector-specific models (e.g. forestry)

Intertemporal Equilibrium (perfect foresight)
Efficiency conditions (first order necessary conditions) fromintertemporal optimization model become system equationsz Allows integration with other types of economic systems (agriculturaland energy system)z

Recursive Equilibriumz

Absence of look-ahead capability makes it difficult to model forestry

Steady-State Equilibrium
Exploratory toolz Steady-state modeling of forestry may be able to inform recursivemodels
z5Brief History of AgLUFirst version completed in 1996
Designz Top-downz Partial equilibriumz Can be run stand-alone or as part of MiniCAM

Studiesz Role of biomass in carbon policyz Impact of ENSO on North Americaz U.S. climate impacts

6

Methodology Highlights
15-year Time Steps from 1990 through 2095
Land Allocationz Land owners compare economic returns acrosscrops, biomass, pasture, and future treesz Underlying probability distribution of yields per
hectareForest Dynamicsz Trees in AgLU grow for 45 yearsz Two forest markets (current and future) needed formodel stability

7

Products in AgLUCrops (calories)
z Rice and Wheatz Coarse Grainsz Oil Cropsz Other Crops

Processed Crops (calories)
z Vegetable Oilsz Sweeteners and Alcoholic Beverages

Animal Products (calories)
z Beef and other Ruminant Livestockz Pork and Poultry

Commercial Biomass (calories or metric tons)
Forest Products (cubic meters)
8

Food Consumption by AgLU Region
kcal per person per day
01,000Crops

Processed Crops

2,0003,000

United States
CanadaOECD EuropeJapan
Australia and New ZealandFormer Soviet Union
China and Centrally Planned Asia
Middle EastAfrica
Latin America
Other AsiaEastern Europe
Korea
India
Animal Products

4,000

AgLU Land Allocation

unmanaged

foodgrainscoarsegrainspastureoilcrops

othercrops

forestbiomasscrops

10Calculation of Land Shares

1λπi
si =1λ∑π kk

π i = y i (Pi − Gi )Land share for land use i
is an increasing functionof profit rate (lambda ispositive).
Profit rate equals
average yield times
price received lessnon-land cost ofproduction.
11

Efficiency Condition
Price received for forest at harvest time must coverland rent over lifetime of tree plus cost ofharvesting
All terms are discounted to the present forcomparison (intertemporal efficiency condition)
AgLU approximation

π forest =r(1 + r ) − 145(~y forest Pforest − G forest)
12

Land Use (without carbon policy)
1098

billion hectares

7

Unmanaged

65
Managed Forest

43Pasture2101990

Crop Land
2005

2020

2035

2050

2065

2080

2095

Land Use (with carbon policy)
10
98
Unmanaged

billion hectares

765

Biomass

4

Managed Forest

3
Pasture2101990

Crop Land

2005

2020

2035

2050

2065

2080

2095

Land Classification
Alternative Definition of Land Usesz Arable Land
 Crops: food grains, coarse grains, oil crops, other food crops,

hay, biofuel crops
 Managed forest land
 Unmanaged: unmanaged forest, other arable landz Non-arable land: grazing

Approaches to Defining Land Classesz Hydrologic Unit Areas: allows future link to water supply
z Agroecological Zones: based on climate variables

15

US Land Classes
Why Disaggregate?
zzz

Capture geographical heterogeneity
Terrestrial mitigation opportunities vary by land class
Climate impacts will vary by land class

Hydrologic Unit Areas (HUAs)zzzz

18 two-digit water basins in US
Fixed location
Useful for climate impact studies
Link to water supply will be important for future work on water and potential
for biofuels

Base-Year Calibrationzzz

No unique way to calibrate base year (calibration is something of an art)
Not easy to calibrate all of the following: land area by product and landclass, output by product and land class, prices, costs of production
Exact calibration doesn’t tell you where your model structure can beimproved16

Major Water Resource Regions

Forest Area
New England
Mid-AtlanticS. Atlantic-Gulf
Great Lakes
Ohio
Tennessee
Upper Mississippi
Lower Mississippi
Souris-Red-Rainy

historical

Missourisimulated

Arkansas-White-Red
Texas Gulf
Rio GrandeUpper Colorado
Lower Colorado
Great Basin
Pacific NW
California
0.0

10.0

20.0

30.0
million hectares

40.0

50.0

60.0

Coarse Grains Area
New England
Mid-Atlantic
S. Atlantic-Gulf
Great Lakes
Ohio
Tennessee
Upper Mississippi
Lower Mississippi
Souris-Red-Rainy

historical

Missourisimulated

Arkansas-White-Red
Texas Gulf
Rio GrandeUpper Colorado
Lower Colorado
Great Basin
Pacific NW
California0.0

2.0

4.0

6.0

8.0

million hectares

10.0

12.0

14.0

Hay Area
New England
Mid-Atlantic
S. Atlantic-Gulf
Great Lakes
OhioTennessee
Upper Mississippi
Lower Mississippi

historicalsimulated

Souris-Red-Rainy
MissouriArkansas-White-Red
Texas Gulf
Rio GrandeUpper Colorado
Lower Colorado
Great Basin
Pacific NW
California

0.0

1.0

2.0

3.0
million hectares

4.0

5.0

6.0

U.S. Examples
Land Use Change over Time (+ 50 years)
z Population growth at 1% per yearz Agricultural and forestry productivity growth at 0.5% peryearz Economic growth in “everything else” sectorz Trade in agricultural and forestry products held constantat base-year levels

Climate Impacts
z UIUC general circulation model with 2.5 degree climatesensitivity
z With and without CO2 fertilization effect21

Historical Land Use
New England
Mid-Atlantic
S. Atlantic-Gulf
Great Lakes
Ohio
Tennessee
Upper Mississippi

unmanaged

Lower Mississippi

forestfood grains

Souris-Red-Rainycoarse grains
Missouri

oil crops

Arkansas-White-Redother crops
hayTexas Gulf
Rio GrandeUpper Colorado
Lower Colorado
Great Basin
Pacific NW
California0.0

10.0

20.0

30.0

40.0

50.0

million hectares

60.0

70.0

80.0

Simulated Land Use (base year)
New England
Mid-Atlantic
S. Atlantic-Gulf
Great Lakes
OhioTennessee
Upper Mississippi

unmanaged

Lower Mississippi

forestfood grains

Souris-Red-Rainycoarse grains
Missouri

oil crops

Arkansas-White-Redother crops
hayTexas Gulf
Rio GrandeUpper Colorado
Lower Colorado
Great Basin
Pacific NW
California
0.0

10.0

20.0

30.0

40.0

50.0

million hectares

60.0

70.0

80.0

Simulated Land Use (+50 years)
New England
Mid-Atlantic
S. Atlantic-Gulf
Great Lakes
OhioTennessee
Upper Mississippi

unmanagedLower Mississippi

forestfood grains

Souris-Red-Rainycoarse grains
Missouri

oil crops

Arkansas-White-Redother crops
hayTexas Gulf
Rio GrandeUpper Colorado
Lower Colorado
Great Basin
Pacific NW
California
0.0

10.0

20.0

30.0

40.0

50.0

million hectares

60.0

70.0

80.0

Coarse Grains Area
New England

Mid Atlantic

S-Atlantic-Gulf

Great Lakes
no climate impacts
Ohio

10% productivity decrease
10% productivity increase
UIUC 2.5 (no CO2 effect on plants)

Tennessee

UIUC 2.5 (with CO2 effect)
Up Mississippi

Low Mississippi

Souris Red Rainy

Missouri
0.0

2.0

4.0

6.0

8.0

10.0

million hectares

12.0

14.0

16.0

Toward a CGE Framework
It is possible to embed partial-equilibrium AgLU in a CGEframework
This demonstration combines AgLU for the US with an
everything else (ETE) sector
Approach is to combine system equations for AgLU withCGE system equations
Market clearing for labor and capitalz Market clearing for ETEz Zero-profit condition for ETEzBenefits of CGE formulation
Consistent treatment of mitigation opportunities across energy,agricultural and forestry systemsz Utility-based consumer demand systemz Walras’ Law test helps find accounting errors
z26

AgLU-CGE: Equations that Solver must handle
Primary Agriculture
Crop1: Food Grains
Crop2: Coarse Grains
Crop3: Oil Crops
Crop4: Other Food Crops
Crop5: Hay
Forestry
Other Products
Processed Food
Feed1
Pork/Poultry
Feed2
Beef
Other Products
Processed Food
Feed1
Pork/Poultry
Feed2
Beef
ETE
Primary Factors
laborcapital
Dropped Equation (Walras' Law test)
ETE

Equation

Unknowns

market clearing
market clearing
market clearing
market clearingmarket clearing
market clearing

price
price
price
price
price
price

market clearing
market clearing
market clearing
market clearing
market clearing

price
price
price
price
price

zero-profit condition
zero-profit condition
zero-profit condition
zero-profit condition
zero-profit condition
zero-profit condition

output level
output level
output level
output level
output level
output levelmarket clearing
market clearing

factor rental
factor rental

market clearing

numeraire priceFinal input-output table in values (thousand US dollars)
Crop1

Crop2

Crop3

Crop4

Crop5

Proc. FoodCrop1: Food Grains

Feed1

Pork/Poultry

Feed2

BeefForestry

ETEvalue ofvalue ofconsumption

net exports
4,000,906

46,141

490,592

724,724

2,076,476

Crop2: Coarse Grains

1,094,790

2,002,028

2,957,481

172,560

2,089,959

Crop3: Oil Crops

4,462,393

107,146

158,280

152,649

2,814,694

Crop4: Other Food Crops

1,703,032

22,98633,9563,312,797

280,713

6,587,80500

7,156,757

149,599

Crop5: Hay
Processed Food
Feed1

2,622,752

Pork/Poultry
Feed2

10,462,245

BeefForestry
ETELand2,338,8393,316,818

2,695,163

353,483

1,587,805

Labor

5,000,000

5,000,000

5,000,000

5,000,000

5,000,000

0

0

00

0

0

3,750,000,061

0000000

0

0

0

0

600,000,010

Capital Stock
Interest

15,740,929

13,931,218

00

2,557,180

65,5720011,392,566-930,320

29,677,690-5,5434,350,000,071

0Model Development
Set up land classes in other world regions
Reflect carbon price in land allocation decision
Include water
Irrigated agriculture as a separate land use
z Water availability limits amount of irrigated agriculture withineach hydrologic unit areazEmbed AgLU in a computable general equilibrium
model (SGM)
Full set of inputs to productionz Land allocator replaces land market
z Biomass as a link between agricultural and energy systemsz Parameterize to reflect biomass response in FASOM-GHG
z29