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Challenges of Integrating Biophysical Information into Agricultural Sector Models

The University of Tennessee. Agricultural Economics. Challenges of Integrating Biophysical Information into Agricultural Sector Models. Daniel G. De La Torre Ugarte, Lixia Lambert, Burton English, Brad Wilson.

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Challenges of Integrating Biophysical Information into Agricultural Sector Models

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  1. The University of Tennessee Agricultural Economics Challenges of Integrating Biophysical Information into Agricultural Sector Models Daniel G. De La Torre Ugarte, Lixia Lambert, Burton English, Brad Wilson Linking Biophysical and Economic Models of Biofuel Production and Environmental Impacts November 13-14, 2008 Gleacher Center, Chicago IL.

  2. The University of Tennessee Agricultural Economics POLYSYS Modules and Interaction Crop Supply (7 /305/ 3110 Regions) Livestock (U.S.) Expected Returns & Available Acreage Acreage Allocation Based on Expected Returns Acreage, Production, Expenditures Production Price Available for Domestic Consumption Export Use Domestic use Value of Exports & Production Gov’t Payments Cash Receipts Gross & Net Realized Income Production Expenses Food Use Feed Use Bioenery Use Total Use Price (U.S.) Ag Income (U.S.) Crop Demand

  3. The University of Tennessee Agricultural Economics Our 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

  4. The University of Tennessee Agricultural Economics Connection between economic and environmental analysis level Net Farm Income Net Returns Government Costs Prices Variability LINKS Erosion N, P, K Leaching Chemical Risk Water use Carbon Embodied Energy

  5. The University of Tennessee Agricultural Economics Interaction with Environmental Module Environmental Soil Erosion (305 Regions) Yield Impacts Nitrogen Runoff, Leaching Phosphorus Runoff, Leaching Chemical Risk Index* Other Environmental Variables Crop Supply Livestock (305 Regions) (U.S.) * Chemical Risk Index from Kovach, J., C. Petzoldt, J. Degni, and J. Tette (1992). Crop Demand Ag Income (U.S.) (U.S.)

  6. The University of Tennessee Agricultural Economics Integration of EPIC Soils Environmental EPIC Indicators • ST A TSGO POLYSYS Rotations • Land Allocation by • AP AC Soil Type Budgeting System • Rotations

  7. The University of Tennessee Agricultural Economics POLYSYS Regions (305) ASDs

  8. The University of Tennessee Agricultural Economics Levels of Aggregation State Farm Nation USDA Region Agricultural Statistic District

  9. The University of Tennessee Agricultural Economics Changes in Chemical Risk

  10. The University of Tennessee Agricultural Economics Environmental Impacts from Maximizing Alternative Practices (ACE)

  11. The University of Tennessee Agricultural Economics Main 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

  12. The University of Tennessee Agricultural Economics Analytical 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, $$$

  13. The University of Tennessee Agricultural Economics Changes in Soil Carbon*: No LANDSAT - LANDSAT *POLYSYS estimates Carbon changes based on West, Marland, King, Post, Jain, and K Andrasko (2003)

  14. The University of Tennessee Agricultural Economics Comprehensiveness • 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 ?

  15. The University of Tennessee Agricultural Economics Data 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,

  16. APAC 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

  17. ABS Databases Fertilizer Machinery Irrigation Composition Prices *** Specifications Prices *** USDAFarm & Ranch Irrigation Survey Costs Yield Impacts USDA NASS USDA ERS Chemical Wage Rates Other USDANASS Prices Compatability *** Seed Costs *** By Region USDA NASS,Others DRPA Inc. Meister Publishing

  18. ABS 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

  19. A P A C ABS Output

  20. The University of Tennessee Agricultural Economics Static 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

  21. The University of Tennessee Agricultural Economics POLYSYS Regions (3110 Counties)

  22. The University of Tennessee Agricultural Economics ALMANAC • 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)

  23. The University of Tennessee Agricultural Economics ALMANAC • 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).

  24. The University of Tennessee Agricultural Economics ALMANAC Geodatabase PRISM weather data • ALMANAC Output: • Yield • Water: • -Precipitation • -Transpiration & ET • -Potential plant water • evaporation • -Surface runoff • Fertilizer • -Loss • -Uptake • -Mineralize • -Fixed • Soil erosion • Temperature Soil layer, landform, and acreage data (SSURGO) ALMANAC ALMANAC Input File Tillage, fertilizer and other management data (ABS)

  25. The University of Tennessee Agricultural Economics Where Does ALMANAC Fit ? Geodatabase Daily and monthly weather data (Weather Data) Crop Supply (7 /305/ 3110 Regions) Livestock (U.S.) Soil layer, landform, and acreage data (SSURGO) Environmental indicators Land Allocation Decisions Expected Returns & Available Acreage Acreage Allocation Based on Expected Returns Acreage, Production, Expenditures Production Price Available for Domestic Consumption ALMANAC ALMANAC Output File ALMANAC Input File Tillage, fertilizer and other management data (ABS) Environmental Effects (7/305/3110 Regions) Crop parameters (USDA-ARS) Export Use Domestic use Value of Exports & Production Gov’t Payments Cash Receipts Gross & Net Realized Income Production Expenses Food Use Feed Use Bioenery Use Total Use Price (U.S.) Crop Demand (U.S.) Ag Income

  26. The University of Tennessee Agricultural Economics Final 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

  27. The University of Tennessee Agricultural Economics Bio-based Energy Analysis Group http://beag.ag.utk.edu/ Agricultural Policy Analysis Center http://agpolicy.org/ Thanks ! Department of Agricultural Economics, Institute of Agriculture University of Tennessee http://www.agriculture.utk.edu/

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