1. On estimating soil C sequestration at national levels and tools for its projection
RC Izaurralde – JGCRI
With contributions from
NJ Rosenberg – JGCRI
JR Williams and D Goss – Texas A&M Univ.
WB McGill – Univ. of Northern British Columbia
PW Gassman – Iowa State Univ.

2. Talk Objectives
Comment on approaches and results of C changes in US agricultural soils
IPCC method
Century model
Two other examples
Update work on EPIC model
Soil C dynamics
Non-CO2 gases
Relate biophysical modeling work to economic modeling at national and global scales

3. Estimating soil C changes at regional and national scales

4. Comment on approaches and results of C changes in US agricultural soils
Comprehensive approach
Extensive use of databases
Two methods (models)
Included uncertainty analysis
Databases
Comprehensive, spatially explicit
IPCC method
Simple with results comparable to Century
Century
Widely used and tested – strength
Maps presented are comparable with some exceptions

5. Scaling up soil C sequestration – an example from Canada
Models tested against long term data
Century, DNDC, ecosys,
EPIC, RothC, SOCRATES
Used SOCRATES to model C fluxes in 2 Alberta ecodistricts
Climate (Env. Canada)
Soil (Agric. Canada)
Management (Agric. Census)
Three scaling-up procedures
All soils, every management
Dominant soil, every management
Dominant soil, average management
Simulated changes in soil C (Gg C y-1)
+29 – +35 in ecodistrict 727
-12 – +1 in ecodistrict 828
Limitations
Spatial variability and soil survey data
Ecodistricts
727
Izaurralde et al., 2001
828
U.S. Department of Energy
Pacific Northwest National Laboratory

6. Update on EPIC

7. Climate change mitigation is a complex problem—a coordinated research approach is needed
CSiTE (Carbon Sequestration in Terrestrial Ecosystems) Research Consortium
Supported by DOE
Three national labs and several universities
CASMGS (Consortium for Agricultural Soils Mitigation of Greenhouse GaSes)
Supported by EPA and USDA
Nine universities and one national lab
Century and EPIC used to model
Agricultural productivity,
Soil C sequestration, GHG emissions
Environmental impacts

8. The EPIC model – a quick overview
Widely Tested And Adapted
Multiple Crops
100 crops, up to 12 plant species in a field
Complex rotations and tillage operations
CO2 fertilization effects on plant growth and water use
Soil Density Changes
Tillage, Erosion, Leaching
Tillage model
Mixes nutrients and crop residues within plow depth
Simulates changes in bulk density
Converts standing residue to flat residue
Determines ridge height and surface roughness

9. Erosion dynamics in EPIC – a special feature
Water erosion model: caused by rainfall and runoff. Six equations available. Green & Ampt equation can be used to estimate infiltration during individual storms
Potter et al., 1999 40 80
120
160
200 F i e l d n g t h ( m ) 20 60 E r o s / a
Simulated
Measured
Wind erosion model: calculated daily based on wind speed distribution and adjusted according to soil properties, surface roughness, vegetative cover and distance across wind path
Puurveen et al., 2000

10. The new soil organic C model in EPIC
SOC model built from concepts used in Century model (Parton et al., 1987, 1993, 1994; Vitousek et al., 1994)
Previously, C modeled as function of N
C and N algorithms were linked to dynamic simulation of wind and water erosion
Validated new model using experimental data from sites in USA and Canada
CRP land in TX, KS and NE (Gebhardt et al. 1994)
Long term experiment in Alberta, Canada (Izaurralde et al. 2001a)
Izaurralde et al. (2001b)

11. Changes of soil organic C with depth in EPIC
The amount of soil organic C stored at depth can be a significant fraction of the total carbon stored in soils
Many plant species have extensive and deep root systems
The new version of EPIC can account for changes of soil C with depth and thus can simulate
Agricultural management
Biomass crops
Land use change
Izaurralde et al. (2001)

12. Current and planned improvements in EPIC
A subroutine was added to simulate the diffusion of gases such as CO2, O2 and N2O across the soil profile
Subroutine based on continuity equation, Fick’s law, & Henry’s law
The diffusion coefficient of CO2 in soil is calculated from the binary diffusion of CO2 in air and adjusted for the amount of air in soil using the Millington-Quirck model
The amount of CO2 produced by microbial respiration at the end of each day is distributed hourly as a function of soil temperature
Model testing using data from short and long term experiments continues

13. Linking EPIC to economic and IA models

14. PNNL’s Global Change Assessment Model
Use of EPIC in Agricultural-Economic and Integrated Assessment Research
PNNL’s Global Change Assessment Model
Texas A&M Univ.
Extensive use of EPIC simulation results as input to ASM
National Assessment
JGCRI – PNNL
EPIC used to predict climate change and variability impacts on
Crop yields
Environmental variables

15. Towards a global EPIC Databases being assembled Modeling to include
Climate, soils, management
Modeling to include
Management impacts on crop yield, soil C, erosion and water quality
Role of biomass
Climate change impacts
Non-CO2 gases and Global Warming Potentials

16. Summary
Comprehensive approach used to estimate C changes in US agricultural soils
Simulations with IPCC method and Century model produced comparable results
Questions:
International application of methods
Verification of estimates
The soil C model in EPIC will allow for comprehensive evaluation of climate, soil, and management impacts on C sequestration and environmental quality
Improvements needed on how to link biophysical models with economic-energy models, especially at global scales