Use of Models to Simulate Agricultural Greenhouse Gas Emissions. Bill Parton Steve Del Grosso
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1 Use of Models to Simulate Agricultural Greenhouse Gas Emissions Bill Parton Steve Del Grosso
2 My Biases 1. Computer Models are the main tool for estimating Greenhouse Gas (N 2 O, CH 4, CO 2 ) emissions from ag soils 2. Expensive to measure Greenhouse Gas fluxes in the field 3. Multiple model Greenhouse Gas flux estimates are needed
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5 Outline 1. DayCent model description 2. Model validation/testing 3. Improved management options Fertilization timing and amounts Cover crops Slow release fertilization and nitrification inhibitors 4. Biofuel options Net Greenhouse Gas fluxes 5. Summary
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7 WATER FLOW SUBMODEL ATMOS PRECIP ATMOS T air SNOW PET Sublimation Evap PET BIOMASS INTERCEPTION T air PET ROOT PET Infiltration K SAT Melting H 2 O -1 cm K SAT K SAT h pot K SAT H 2 O 1-4 cm H 2 O 4-15 cm h pot OUTFLOW K SAT h pot H 2 O 15-3 cm K SAT h pot H 2 O cm K SAT
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9 Model Testing/Validation
10 Ontario corn MODEL TESTING Mean N2O Emissions measured DAYCENT MI forest CO dryland wheat NE dryland wheat MI corn/soy/alfalfa TN corn CO irrigated corn CO irrigated corn/barley CO short grass NE short grass gn ha -1 d -1
11 CO Irrigated Corn 14 N 2 O Emissios: Corn Hi-N, Conventional-Till gn ha -1 d simulated observed 3/11/5 9/1/5 3/12/6 9/11/6 14 N 2 O Emissios: Corn Hi N, No-Till gn ha -1 d simulated observed 3/11/5 9/1/5 3/12/6 9/11/6
12 16 12 ww/fal NE - N 2 O emissions observed sim gn ha -1 d /31/93 8/2/93 2/1/94 8/3/94 2/2/95 8/4/95 16 grass NE - N 2 O emissions 12 observed sim gn ha -1 d /31/93 8/2/93 2/1/94 8/3/94 2/2/95 8/4/95
13 8 Simulated vs. Observed N 2 O Emissions sim N 2 O (gnha-1 d-1) y =.9883x R 2 = obs N 2 O (gn ha-1 d-1)
14 simualted CH 4 gc ha -1 d intensive ag dryland ag short grass coniferous decidous tropical CH 4 Validaions observed CH 4 gc ha -1 d -1 ln(simualted N 2O - gn ha -1 d -1 ) deciduous forest dryland ag grassland intensive ag organic ag N 2 O Validations ln(observed N 2 O - gn ha -1 d -1 )
15 8 DAYCENT vs NASS County Level Yields simulated gc m -2 yr y =.967x R 2 = observed gc m -2 yr -1
16 4 KBS - Grain Yield gc m -2 yr corn/soy/wheat: r 2 = 88% sim obs 1 g C m CEF, ON - Annual Grain Yields daycent obs gc m Sterling, CO - Mean Crop Yields ww/f ww/ann corn millet
17 Compare Water Drainage Compare Nitrate Export year Observed Simulated year Observed Simulated kg N/ha/yr water yield cm
18 EPA Regional DayCent Model Results
19 Estimated Corn Yield from NASS
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22 Improvements in Agricultural Management
23 Best Agricultural Management Practices 1. Timing and amount of fertilizer application Winter vs. spring application 2. Time release and nitrification inhibitors 3. Winter cover crops
24 N Addition Simulations for Central Iowa 4 Mean Annual Corn Grain Yield 16 Mean Annual N losses g C m -2 3 first 1 years second 1 years g N m first 1 years second 1 years N fert g N m N fert g N m -2 6% Mean Annual N losses/n fert 5% 4% 3% 2% 1% % first 1 years second 1 years N fert g N m -2
25 Fertilizer Type and Tillage Intensity Study Colorado Irrigated Corn 25 N2O gn ha -1 d N CT N NT HI N CT urea HI N NT urea HI N CT time release HI N NT time release HI N CT inhibitor 25 N2O gn ha -1 d conventional till no till N Hi N urea Hi N time release Hi N inhibitor
26 How can we improve? Wind to H 2 to NH 3 Local renewable NH 3 Harvest grain and cobs Cobs for gasification UMM - WCROC NRCS Photo gallery USDA Photo center Manure back to soil NRCS Photo gallery Improved fertilizers: Slow release Nitrification inhibitors Grain for ethanol Dry distillers grain, feed NRCS Photo gallery
27 Biofuel Model Results 1. Existing Ag land 2. Conservation Reserve Program Land 3. Natural grassland
28 8 Cropland to Biofuels g CO2-C eq. m -2 yr -1 ANPP gc m -2 yr -1 * delta SOC N2O GHGnet ANPP CT corn/soy corn/soy to NT corn/soy corn/soy to cont. CT corn corn/soy to cont. NT corn corn/soy to switchgrass
29 8 CRP to Biofuels g CO2-C eq. m -2 yr -1 ANPP gc m -2 yr -1 * delta SOC N2O GHGnet ANPP CRP CRP to CT corn/soy CRP to NT corn/soy CRP to switchgrass
30 8 Prairie to Biofuels g CO2-C eq. m -2 yr -1 ANPP gc m -2 yr -1 * delta SOC N2O GHGnet ANPP prairie prairie harvested prairie harvested + N prairie to CT corn/soy prairie to NT corn/soy prairie to switchgrass
31 Summary 1. We need computer models to assess greenhouse gas fluxes from agriculture DayCent and DNDC 2. Best management practices can greatly reduce agricultural greenhouse gas fluxes Connection to biofuels 3. Need field measurement program to generate data for model testing
32 Summary 4. Extensive testing of computer models is essential Standard data sets used to test models Model comparisons are needed
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