Adapt‐N: A Tool for Adaptive Nitrogen Management in Corn – Incorporating the Weather Component – Harold van Es, Jeff Melkonian, Bianca Moebius‐Clune, Art DeGaetano, Laura Joseph Cornell Adapt‐N Project Thank you to our Funders • New York Farm Viability Institute • USDA‐NRCS Conservation Innovation Grants program • USDA‐NIFA Agriculture and Food Research Initiative • USDA‐NIFA Special Grant on Computational Agriculture (Rep. Maurice Hinchey) • Hatch – Smith Lever Funds • Northern NY Agricultural Development Program • International Plant Nutrition Institute
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Adapt‐N: A Tool for Adaptive Nitrogen Management in Corn
– Incorporating the Weather Component –
Harold van Es, Jeff Melkonian, Bianca Moebius‐Clune,
Art DeGaetano, Laura Joseph
Cornell Adapt‐N Project
Thank you to our Funders
• New York Farm Viability Institute• USDA‐NRCS Conservation Innovation Grants program• USDA‐NIFA Agriculture and Food Research Initiative• USDA‐NIFA Special Grant on Computational Agriculture
(Rep. Maurice Hinchey)• Hatch – Smith Lever Funds• Northern NY Agricultural Development Program• International Plant Nutrition Institute
Part 2. The Adapt‐N tool: Its inner workings and upcoming changes
Adapt-N Infrastructure
High‐Resolution Climate Data (5x5 km)• Northeast and Iowa• Expanding to all of eastern USA in 2012• Daily updates• Enables field‐scale adaptation
High Resolution Weather Data*Northeast Regional Climate Center
• Meteorological forecast models have increasing finer spatial scales [temperature].
• Doppler weather estimates precipitation in 5x5 km pixels [rainfall].
• These platforms provide the basis for the spatial interpolation of climate data.
*DeGaetano and Belcher (2007), J. Appl. Meteorology and ClimatologyDeGaetano and Wilks (2009), Int. J. of Climatology
Temperature : Model Grid Density
40 km with 50 mbvertical resolution
13 km with 25 mbvertical resolution
Elevation Standardization
Grid to Station Interpolation
Bias at each Station
Bias Interp. Back to Grids
Model Adjusted Based on Bias
5 km
Precipitation
Radar Based
R = aZb
R = rainfall rateZ = radar reflectivitya,b = ‘optimized’ constants
Precipitation: Procedure• Already at 5 km resolution;
– No need for elevation adjustment;
• Compare amounts in pixels with co-located gauges;– No horizontal interpolation;
• Compute Bias;• Interpolate biases to 5 km radar grid and
adjust;– Uses optimized inverse distance weighting;– IDW improved estimates compared to other
interpolation methods;
• Now• Northeastern United States;
–July 2004 - present daily max and min temperature;
–2005 - present daily precipitation;
• Iowa 2010 – 2011;
• 1970 - present daily max and min temperature (NARR model);
• 2012 season - USA east of 100°W
Adapt-N Infrastructure
High‐Resolution Climate Data (5x5 km)• Northeast and Iowa• Expanding to all of eastern USA in 2012• Daily updates• Enables field‐scale adaptation
Key points:• What drives this system?
• Why use dynamic simulation models for N management?
• How does the crop grow?
• Water in soil
• Nitrogen in soil
PNM model
High resolution climate data
Why use dynamic simulation models?
• What are models?
• Represent the behavior of an object/process/system, usually expressed mathematically;
• The PNM model is a ‘dynamic mechanistic’ simulation model.
• Why ‘dynamic’?
• Why ‘mechanistic’?
Models in agriculture
• Irrigation scheduling: multiple models available
• Disease prediction: e.g., potato late blight
• Nutrient management
PNM model: The core of the Adapt-N tool
New model based on the linkage of two simulation models:
• Crop growth/N uptake model
• Soil processes model, LEACHNHutson, J.L., R.J. Wagenet, and M.E. Niederhofer. 2003. Leaching Estimation And Chemistry Model: a process‐based model of water and solute movement, transformations, plant uptake, and chemical reactions in the unsaturated zone. Version 4. Dept of Crop and Soil Sciences. Research Series No. R03‐1. Cornell University, Ithaca, NY, USA.
Sinclair, T.R., and R.C. Muchow. 1995. Effect of nitrogen supply on maize yield: I. modeling physiological responses. Agronomy Journal 87:632‐641.
Crop ModelHow does the crop grow?
• Solar radiation Biomass
• Biomass partitioning: Leaves/stems/grain
• Phenology: Crop development
• Limitations? : Water and nitrogen
Solar Radiation to Biomass
Sinclair and Muchow (1999); Advances in Agronomy
• Close linkage between the amount of light intercepted by the crop canopy and crop growth
• Equations describing this linkage are used in many crop growth models to estimate biomass accumulation over time
Potential C and N mineralizedChange in organic C = [organic C] * (1-exp(- K))
Actual C and N mineralized under temperature and moisture conditions in the field
Manure added on 4/10C:N ratio : 7.5
Non-microbial soil N processes represented in the model
• Ammonia volatilization
• N leaching
• Crop N uptake
Soil Water (and associated N fluxes in
the soil)
‘Tipping Bucket’/ ‘Mobile’ N
(Jones and Kiniry (1986); Addiscott and Wagenet, 1985)
Rain
Runoff
Infiltration
Step 1 : Infiltration into the soil following a rainfall
Wnew = Wprevious + Infiltration Layer 1
Layer 2
Rain
Runoff
Infiltration
Step 2 : Redistribution among layers:Wnew ≤ Wfc : No water movement
If Wnew ≤ Wfc : No downward water movement
Layer 1
Layer 2
WWn
Rain
Runoff
Infiltration
Step 3a : Redistribution among layers:Wnew > Wfc and Wnew ≤ Wsaturation
If Wnew > Wfc and ≤ Wsaturation : Layer 1
Layer 2Wnew = Wprevious + GainLayer 2
GainLayer 2
WWn
Rain
Runoff
Infiltration
Step 3a : Redistribution among layers:Wnew > Wfc and Wnew ≤ Wsaturation
If Wnew > Wfc and ≤ Wsaturation : Layer 1
Layer 2Wnew = Wprevious + GainLayer 2
GainLayer 2
Rain
Runoff
Infiltration
Step 3b : Redistribution among layers:Wnew > Wsaturation
If Wnew > Wsaturation : Layer 1
Layer 2
GainLayer 2 = Gainrapid + Gainslow
Wnew = Wprevious + GainLayer 2
Rain
Runoff
Infiltration
Step 3b : Redistribution among layers:Wnew > Wsaturation
If Wnew > Wsaturation : Layer 1
Layer 2
GainLayer 2 = Gainrapid + Gainslow
Wnew = Wprevious + GainLayer 2
Soil water losses following infiltration
Layer 1
Bottom layer
TranspirationSoil
Evaporation
Drainage out of root zone
If Wnew > Wfc :
Soil N Redistribution / LeachingCrop N uptake
Drainage + N out of root zone
Crop N uptake
N in infiltrating water
Incoming N mixes with N in the soil solution
New solution N of water
Model Calibrations and ValidationsSoil Component
Fertilizer and Sod Incorporation• Sogbedji, J.M., H.M. van Es, J.L. Hutson, and L.D. Geohring. 2001. Fate of N fertilizer
and green manure in clay loam and loamy sand soils: I Calibration of the LEACHM model. Plant and Soil 229(1): 57‐70.
• Sogbedji, J.M., H.M. van Es, J.L. Hutson, and L.D. Geohring. 2001. N rate and transport under variable cropping history and fertilizer rate on loamy sand and clay loam soils: II. Performance of LEACHMN using different calibration scenarios. Plant and Soil 229:71‐82.
• Sogbedji, J.M., H.M. van Es, S.D. Klausner, D.R. Bouldin, and W.J. Cox. 2001. Spatial and temporal processes affecting nitrogen availability at the landscape scale. Soil & Tillage Research 58 (3‐4) 233‐244.
Manure• Sogbedji, J.M., H.M. van Es, J. Melkonian, and R.R. Schindelbeck. 2006. Evaluation of
the PNM model for simulating drain flow nitrate‐N concentrations under manure‐fertilized maize. Plant and Soil 282: 343‐360.
• Melkonian, J. L.D. Geohring, H.M. van Es, P.E. Wright, T.S. Steenhuis and C. Graham. 2010. Subsurface drainage discharges following manure application: Measurements and model analyses. Proc. XVIIth World Congress of the Intern. Commission of Agric. Engineering, Quebec City, Canada.
Maize component / PNM Model Calibrations and Validations
• Cox WJ, Cherney DJR (2001) Row spacing, plant density and nitrogen effects on corn silage Agron. J. 93:597-602.
• Cox WJ, Kalonge S, Cherney DJR, Reid WS. 1993. Growth, yield, and quality of forage maize under different nitrogen management practices. Agron. J. 85:341 – 347.
• Cox WJ, Zobel RW, van Es HM, Otis DJ (1990) Growth, development and yield of maize under three tillage systems in the northeastern U.S.A. Soil and Tillage Research 18: 295 –310.
• Cox WJ, Zobel RW, van Es HM, Otis DJ (1990) Tillage effects on some soil physical and corn physiological characteristics. Agron. J. 82: 806 – 812.
• Stone PJ, Sorensen IB, Jamieson PD (1999) Effect of soil temperature on phenology, canopy development, biomass and yield of maize in a cool-temperature climate. Field Crops Res 63:169 – 178.
PNM Model Performance:Root zone drainage
fall manure application
fall manure application
PNM Model Performance:Nitrate-N Leaching
fall manure application
fall manure application
fall manure application
fall manure application
PNM Model Performance:Nitrate-N Concentration (mg L-1 ) in Drainage Discharge
Adapt-N: Changes from June 2011 - present.
• Updating changes to the interface without having to submit;
• ‘Set Up New Location’ support on ‘Manage Locations’ page:
• Directly adding a location to a group in the ‘Set Up New Location’ support on ‘Manage Locations’ page;
• Map feature for obtaining location lat/long;
• Appropriate units for ‘Select Expected Yield’ for selected corn productions system (grain/silage/sweet corn);
• Multiple fertilizer and manure inputs for the current year;
Adapt-N: Changes from June 2011 - present.
• Clarified wording for current year manure applications;
• Range for recommendation based on analysis of post-application N losses from the Adapt-N recommendation;
Adapt-N 2012
‘Irrigation’ tab/page:
• Up to 8 irrigations;
• Range of selections: 0.25” – 2.00” in 0.25” increments;
‘Alerts Settings’ and ‘N Rec Alerts’ tabs/pages;
Mineral Nitrogen/Cultivar page :
• ‘Edit’ function for fertilizer table;
• Additional grain cultivar selections for the Midwest;
Adapt-N 2012
Soil/Tillage page:
• Northeast: Expanded selection of textural classes;
• NY: Soil series selections under each textural class;
• Iowa: Textural classes with soil series selections under each textural class;
• Similar approach for Minnesota, Illinois, Indiana and Wisconsin;
Textural Classes – New York (NE)*:
*Zia Ahmed and Peter Woodbury, Crop and Soil Sciences Dept., Cornell Univ.
• Silt loam (755,000 acres);
• Loam (635,000 acres);
• Sandy loam (150,000 acres);
• Silty clay loam (55,000 acres);
• Loamy sand (25,000 acres);
• Clay (10,000 acres);
Textural Classes – Iowa*:
• Loam (1,020,000 acres);
• Silty clay loam (1,020,000 acres);
• Silt loam (860,000 acres);
• Silty clay (740,000 acres);
• Clay loam (490,000 acres);
• Sandy loam/Loamy sand (60,000 acres);
*Zia Ahmed and Peter Woodbury, Crop and Soil Sciences Dept., Cornell Univ.
Adapt-N 2012
Manure/Sod/Soybean page:
• Renaming to ‘Manure/Rotations’;
• ‘Edit’ button for manure inputs table;
• Option to enter manure in tons/acre;
• Add ‘>10% solids’ option;
Adapt-N 2012
Manure/Sod/Soybean page (contd):
• Cover crops ‘N credit’ option;
• Replacing ‘Previous soybean crop’ with ‘Previous crop’: