Challenges of Integrating Biophysical Challenges of Integrating Biophysical Information into Agricultural Sector ModelsInformation into Agricultural Sector Models

Linking Biophysical and Economic Models of Biofuel Production and Environmental ImpactsNovember 13-14, 2008

Gleacher Center, Chicago IL.

Daniel G. De La Torre Ugarte, Lixia Lambert, Burton English, Brad Wilson

POLYSYS Modules and InteractionPOLYSYS Modules and Interaction

Expected Returns & Available Acreage

Acreage Allocation Based on Expected ReturnsAcreage, Production, Expenditures

Export UseDomestic use

Production PriceAvailable for Domestic Consumption

Food UseFeed UseBioenery UseTotal UsePrice

Value of Exports & ProductionGov’t Payments Cash ReceiptsGross & Net Realized Income Production Expenses

(U.S.) Crop Demand

Livestock(U.S.)

Crop Supply(7 /305/3110 Regions)

(U.S.) Ag Income

Our Initial MotivationOur Initial Motivation

• Analysis of economic and environmental tradeoffs

• Sustainability context: erosion, N,P,K, chemical• Economic tradeoffs: net returns, net farm

income, government cost, price changes• National and regional policy instruments• Several sector models have integrated

biophysical models since the mid 1980’s

Connection between economic and Connection between economic and environmental analysis level environmental analysis level

Net Farm IncomeNet ReturnsGovernment CostsPricesVariability

ErosionN, P, K LeachingChemical RiskWater useCarbonEmbodied Energy

LINKS

Interaction with Environmental ModuleInteraction with Environmental Module

Crop SupplyCrop Supply (305 Regions)(305 Regions)

Crop DemandCrop Demand (U.S.)(U.S.)

LivestockLivestock (U.S.)(U.S.)

Ag IncomeAg Income (U.S.)(U.S.)

Environmental (305 Regions)

Nitrogen Runoff, LeachingNitrogen Runoff, Leaching

Phosphorus Runoff, LeachingPhosphorus Runoff, Leaching

Chemical Risk Index*Chemical Risk Index*

Other Environmental VariablesOther Environmental Variables

Soil ErosionSoil Erosion

Yield ImpactsYield Impacts

* Chemical Risk Index from Kovach, J., C. Petzoldt, J. Degni, and J. Tette (1992).

Integration of EPICIntegration of EPIC

Rotations

• AP AC Budgeting System

POLYSYS

• Land Allocation by Soil Type

• Rotations

Soils

• ST ATSGOEPIC Environmental

Indicators

POLYSYS Regions (305) ASDsPOLYSYS Regions (305) ASDs

Levels of AggregationLevels of Aggregation

Nation

StateFarm

AgriculturalStatisticDistrict

USDA Region

Changes in Chemical RiskChanges in Chemical Risk

Environmental Impacts from Maximizing Environmental Impacts from Maximizing Alternative Practices (ACE)Alternative Practices (ACE)

Main Challenges and decisionsMain Challenges and decisions

• Geographic aggregation analytical level• What to include: Crops, rotations, practices,

land, soils, etc.• Diverse resolution for economic and

environmental data• Average environmental impacts vs. dynamic

environmental impacts• Shrinking agricultural economic databases

Analytical ResolutionAnalytical Resolution• Economic:

– Lower resolution better economic data more reliable output– High resolution lower reliability of economic output

• Environmental:– Lower resolution, too much aggregation, less significance of

environmental impacts– Higher resolution better significance of environmental output

• Compromise: objectives, data, computer power, $$$

Changes in Soil Carbon*: Changes in Soil Carbon*: No LANDSAT - LANDSATNo LANDSAT - LANDSAT

*POLYSYS estimates Carbon changes based on West, Marland, King, Post, Jain, and K Andrasko (2003)

ComprehensivenessComprehensiveness• Land: cropland, pasture, idle, forest

– Begins with research objectives, driven by complexity of the forthcoming issues and availability of biophysical data

• Crops, rotations, livestock activities, forest– Economically/environmentally meaningful for resources, region, nation,

market. Biophysical parameters ?• Agricultural practices

– Current practices, and alternative practices from more likely to less likely. Biophysical parameters ?

• Soils and landscapes– Extensive representation, study objectives. Biophysical parameters ?

Data Sources ResolutionData Sources Resolution• Economic

– Cost of production: ERS Resource Regions– Crop Price: NASS state

• Environmental– SSURGO: MUID– Land use history: county, NRI point (1992)

• Link– Yield: NASS county– Practices: Tillage (CTIC county), ARMS (ERS Regions)

• Shrinking agricultural economic databases availability and/or resolution: cost of production, NRI,

APAC Budgeting SystemAPAC Budgeting System• Provides Consistent,

Crop- System Budgets For Research– Critical in Assessing

Policy & Environmental Changes

• Much of The Data Required Comes From Databases Built Into The System

Sample Screen From ABSSample Screen From ABS

ABS DatabasesABS Databases

MachinerySpecifications

Prices***

USDA ERS

FertilizerComposition

Prices***

USDA NASS

ChemicalPrices

Compatability***

DRPA Inc.Meister Publishing

OtherSeed Costs

***USDA NASS,

Others

IrrigationCosts

Yield Impacts

USDAFarm & RanchIrrigation Survey

Wage RatesBy Region

USDANASS

ABS FlexibilityABS Flexibility• ABS Supplies The Needs of Several Different

Models:

– POLYSYS, FLIPSIM, EPIC

– ABS Data Are Readily Incorporated Into These Models

• Has Supported a Range of Research Projects– Sustainable Agriculture, Biomass, Various

Biotechnologies, Boll Weevil Eradication

Corn-Moldboard PlowCOMMODITY:Corn TILLAGE:Moldboard Plow

PREVIOUS CROP:Corn FARM SIZE:Large IRRIGATION:DryREGION TYPE:POLYSYS PRACTICES:N.A. SOIL TYPE:0

REGION I.D.:CT-1 N.A. E.I. INDEX:0PRODUCTION REGION:Northeast N.A. ALT. NUTRIENTS:None

400001D0.C01ITEM CATEGORY UNITS PRICE QUANTITYAMOUNTCODE CODE NATIONAL INDEX

REVENUE2053 8 Corn, Grain BU 2.7000 1 92.34 249.33

VARIABLE EXPENSES1 SEED

2655 1 Corn Seed, Hybrid 1,000 kernels0.9713 1 25.33 24.60SUBTOTAL 24.60

2 FERTILIZER & LIME109 2 Urea (44%-46% N) LB 0.1569 1 281.00 44.08200 2 P2O5 * LB 0.3016 1 41.00 12.37300 2 K20 * LB 0.1275 1 50.00 6.38

NAME

ABS Output

CAAP

Static vs Dynamic ImpactsStatic vs Dynamic Impacts• Most implementations imply fix static environmental

parameters into economic models• While most physical processes occur in the mid or

long term, annual/seasonal impacts maybe critical: yield, water

• However when looking 10, 25 or more years into the future this could be critical

• Full integration should not be a problem with current computer power

POLYSYS Regions (3110 Counties)POLYSYS Regions (3110 Counties)POLYSYS County Regions (3111)

ALMANACALMANAC

• Developed by ARS-USDA in 1992 to simulate the impact of agronomic decisions on crop biomass production

• Compiles soil erosion, economic, hydrological, weather, nutrient, plant growth dynamics, and crop management information

• Simulates plant competition up to 10 crops growing at the same time (unique from EPIC)

ALMANACALMANAC• Does not require local calibration of plant

parameters or hydrological components it is ideal for regional-level analyses

• Has been widely used to estimate yield response to climate and differences in land and water management at a specific location

• The most recent version of ALMANAC has incorporated additional parameters including evapotranspiration rates and water table information (Kiniry et al., 2005).

ALMANACALMANAC

PRISM weather data

Soil layer, landform, and acreage data (SSURGO)

Tillage, fertilizer and other management data (ABS)

ALMANAC Input File ALMANAC

Geodatabase

ALMANAC Output:

•Yield•Water:

-Precipitation-Transpiration & ET

-Potential plant water evaporation

-Surface runoff•Fertilizer

-Loss-Uptake

-Mineralize-Fixed

•Soil erosion•Temperature

WWhheerree

DDooeess

AALLMMAANNAACC

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Expected Returns & Available Acreage

Acreage Allocation Based on Expected ReturnsAcreage, Production, Expenditures

Export UseDomestic use

Production PriceAvailable for Domestic Consumption

Food UseFeed UseBioenery UseTotal UsePrice

Value of Exports & ProductionGov’t Payments Cash ReceiptsGross & Net Realized Income Production Expenses(U.S.)

Crop Demand

Livestock(U.S.)

Crop Supply(7 /305/3110 Regions)

(U.S.) Ag Income

Environmental indicators

Land Allocation Decisions

Environmental Effects(7/305/3110 Regions)

Daily and monthly weather data (Weather Data)

Soil layer, landform, and acreage data (SSURGO)

Tillage, fertilizer and other management data (ABS)

Crop parameters (USDA-ARS)

ALMANAC Input File ALMANAC ALMANAC

Output File

Geodatabase

Final RemarksFinal Remarks

• Data availability and compatibility is one of the major challenges

• Remote sensing and GIS systems developing new sources of data

• Use alternative biophysical data based on need, strength, simplicity

• Processing power, usually not a limiting factor

Department of Agricultural Economics, Institute of AgricultureUniversity of Tennessee http://www.agriculture.utk.edu/

Agricultural Policy Analysis Centerhttp://agpolicy.org/

ThanksThanks ! !

Bio-based Energy Analysis Grouphttp://beag.ag.utk.edu/