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.

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

Estimating soil C changes at regional and national scales

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

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

Update on EPIC

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 http://csite.eshd.ornl.gov CASMGS (Consortium for Agricultural Soils Mitigation of Greenhouse GaSes) Supported by EPA and USDA Nine universities and one national lab http://www.casmgs.colostate.edu Century and EPIC used to model Agricultural productivity, Soil C sequestration, GHG emissions Environmental impacts

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

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

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)

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)

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

Linking EPIC to economic and IA models

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

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

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