coupling sustainable production analysis to field trial data dave muth, idaho national laboratory
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Coupling Sustainable Production Analysis to Field Trial Data Dave Muth, Idaho National Laboratory. U.S. Department of Energy Office of Biomass Program February 23, 2010. Sustainable Resource Access. Limiting factor models exist, We’re building a framework where models can plug together. - PowerPoint PPT PresentationTRANSCRIPT
Coupling Sustainable Production Analysis to Field Trial DataDave Muth, Idaho National Laboratory
U.S. Department of EnergyOffice of Biomass Program
February 23, 2010
Sustainable Resource Access
Limiting factor models exist,
We’re building a framework where models can plug together.
Technical Approach
Data Sources:Soils
WeatherProduction
Management
I-FARM:User InterfacesData Acquisition
Scenario Management
RUSLE2:Soil Erosion
CQESTR:Soil Organic
Carbon
I-FARM P,K,& N Routines:Nutrient
Management
FY09 Addition:Soil Water and Temperature
FY09 Addition:Environmental Degradation
VE-SuiteIntegrationFramework:Data Spec,Dynamic
Integration
Case Study Scenarios:Ames, IA
Lincoln, NE
FY09 Addition:Soil Compaction
Results
Analysis Framework Architecture
Case Study: Ames, IA 25 Acre Experiment
Current Analysis Approach: Erosion alone indicates that full
removal is sustainable
Managements:· Conventional Tillage – Chisel Plow· No Tillage· No Till with Rye Cover Crop· No Till with Interseeded legume and Clover Cover Crop
Erosion (T=5.0) (t/acre/yr)
Removal Rate Conv Till No Till
0% 1.3 0.11
50% 4.3 0.42
100% 4.7 2.3
Analysis with SOC: Conventional tillage does not
provide sustainable resource, limited availability through no till
SOC (lbs/acre/yr)
Removal Rate Conv Till No Till
0% -67.76 52.55
50% -101.95 21.69
100% -121.26 -15.02
Implementing Innovative Management Strategies:
Consistent sustainable resource available
SOC (lbs/acre/yr)
Removal Rate
NT w/Rye Cover
NT w/Legume +
Clover Cover
0% 116.82 204.99
50% 78.25 171.24
100% 39.12 130.25
Potential value added through other ecosystem services:• Carbon sequestration• Reduced nutrient runoff• Reduced erosion
Utilizing Field Trial Data Through the Residue Removal Tool
Data Sources:Soils
WeatherProduction
Management
I-FARM:User InterfacesData Acquisition
Scenario Management
RUSLE2:Soil Erosion
CQESTR:Soil Organic
Carbon
I-FARM P,K,& N Routines:Nutrient
Management
FY09 Addition:Soil Water and Temperature
FY09 Addition:Environmental Degradation
VE-SuiteIntegration
Framework:Data Spec,Dynamic
Integration
Case Study Scenarios:Ames, IA
Lincoln, NE
FY09 Addition:Soil Compaction
Results
NRCS Soil Data Access Queries by
State
NASS Based Crop Yields by County
NRCS Established Primary Rotations
by Crop Management Zone
NRCS Established Residue Removal
Techniques by Rotation
Scenario Assembly Data
Structures
Iterative Schema with
Integrated Model Set
Data Extraction
and Results Writing
RUSLE2 Databases
• Sustainable ag residue removal for national resource assessment
Implemented in a highly efficient iterative schema
CMZ 4 Rotations
• managements\CMZ 04\c.Other Local Mgt Records\Biomass Harvest\Continuous corn grain; NT
• managements\CMZ 04\c.Other Local Mgt Records\Biomass Harvest\Corn, grain; NT, SB NT, WW NT CMZ4
• managements\CMZ 04\c.Other Local Mgt Records\Biomass Harvest\corn grain;NT, corn grain;NT, Soybean, wr
• managements\CMZ 04\c.Other Local Mgt Records\Biomass Harvest\corn grain;NT,anhyd, Soybean, nr, NT Single disk z4
flail shredder/windrower
bar rake
wheel rake
Modeled Removal Rates - Corn Stover
1) No Stover Removal
2) Grain and Cobs: CCM on combine mix
3) Moderate Removal: Combine residue spreader disengaged, bale windrow left behind
4) Moderately High Removal: Bar rake run over standing stubble, bale windrow
5) High Residue Harvest: Flail shredder cutting standing stubble and collecting flat residue, bale windrow
Adair County, Iowa
212 Kennebec Silt Loam 0% to 2% Slope
Adair County, Iowa Example212 Kennebec Silt Loam 0% to 2% Slope
10 Year Average Yield:Management + Removal Rate
Calculated Erosion
SCI OM Subfactor
Annual Average Residue
(lbs)Corn Grain
Yield
Continuous corn grain; NT, Harvest grain and cobs 0.1660717 0.320423 1891.345 149.9
Continuous corn grain; NT, High residue Harvest 1.1931644 -0.60299 7070.866 149.9
Continuous corn grain; NT, Moderate Residue Harvest 0.2281336 0.13634 2905.457 149.9
Continuous corn grain; NT, Moderately High residue Harvest 0.5972384 -0.12565 4542.535 149.9
Continuous corn grain; NT no stover harvest 0.0889718 0.784717 0 149.9
USDA 10 Year Baseline Projection:
USDA 10 Year Baseline Projection plus 10%:
Continuous corn grain; NT, Harvest grain and cobs 0.1194257 0.498468 2180.272 174.3
Continuous corn grain; NT, High residue Harvest 1.0937827 -0.566 8151.033 174.3
Continuous corn grain; NT, Moderate Residue Harvest 0.1699904 0.286264 3349.304 174.3
Continuous corn grain; NT, Moderately High residue Harvest 0.5033516 -0.01575 5236.466 174.3
Continuous corn grain; NT no stover harvest 0.0675342 1.029399 0 174.3
Continuous corn grain; NT, Harvest grain and cobs 0.0975953 0.625653 2386.666 191.73
Continuous corn grain; NT, High residue Harvest 1.0297659 -0.53958 8922.644 191.73
Continuous corn grain; NT, Moderate Residue Harvest 0.1386611 0.393361 3666.363 191.73
Continuous corn grain; NT,Moderately High residue Harvest 0.4473739 0.062759 5732.172 191.73
Continuous corn grain;NT no stover harvest 0.0560973 1.204186 0 191.73
Results For RP Field Trial Counties
FIPS County StateAcres in Rotation
Annual Residue (lbs)
Annual Residue
(tons)
Annual Residue
(tons/acre)
Corn
YieldRet. Coeff
IA015 Boone County Iowa 269120
1,351,500,000
675,751 2.51097 193.4 0.18787
MN149 Stevens County Minnesota 187320
828,155,000
414,077 2.21054 164.5 0.173718
NE155Saunders
County Nebraska 258151
817,977,000
408,988 1.5843 149.1 0.352557
PA081Lycoming
County Pennsylvania 27440 14,504,500
7,252 0.264296 128.8 0.894568
SC041 Florence CountySouth
Carolina 48935 61,318,600 30,659 0.626532 101.1 0.589174
SD011Brookings
County South Dakota 141595
625,366,000
312,683 2.20829 152.3 0.157432
Other Notes and Future Plans
• National Assessment capabilities will be part of the core tool over the next few months
• Quantitative carbon will brought online and used to revise the national runs over the next year
• DAYCENT developers joining the team for quantitative carbon modeling
• Significant I-Farm enhancements will be utilized within the tool over the next 6-9 months
• Discussions and planning on moving sub-field will ramp up over the next year