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Atmospheric Modeling and Analysis Research

EPIC Capabilities

Model Components include:  Weather, surface runoff, return flow, percolation, evapotranspiration, lateral subsurface flow and snow melt; water erosion; wind erosion; nitrogen (N) & phosphorus (P) loss in runoff, nitrogen leaching; organic N & P transport by sediment; N & P mineralization, immobilization and uptake; denitrification; mineral P cycling, N fixation; pesticide fate and transport: soil temperature; crop growth and yield; crop rotations; tillage, plant environmental control (drainage, irrigation, fertilization, furrow diking, liming); economic accounting; waste management (feed yards dairies with or without lagoons).

Model Operation:

  • Daily time step – long term simulations (1-4,000 years)
  • Soil, weather, tillage and crop parameter data supplied with model
  • Soil profile can be divided into ten layers
  • Weather generation is optional
  • Homogeneous areas up to large fields

 EPA Application: EPIC is used directly at ORD to support development and application of the bidirectional version of the Community Multi-Scale Air Quality (CMAQ) model.  This CMAQ version requires daily information regarding fertilizer application rate and depth to support compensation point and flux calculations.  Bidirectional CMAQ also includes basic internal tracking of the soil ammonium pool including nitrification.  The algorithms to do this come directly from the EPIC biogeochemical modules.

The USDA Agricultural Resource Management Survey (ARMS) database provides the number and type of field operations by USDA farm production area.  EPIC then used heat unit scheduling and plant nutrient stress to assign these operations in time.

Grain Corn Management Schedule

Crops Modeled in each Farm Proudction Area
(irrigated and rainfed)

Grass Hay
Alfafa Hay
Other Grasses
Barley
Canola
Edible Beans
Edible Peas
Grain Corn
Corn for Silage
Cotton
Oats

Peanuts
Potatoes
Rice
Rye
Grain Sorghum
Sorghum for silage
Soybeans
Winter Wheat
Spring Wheat
Other Crops

 

Management scenarios were developed for each crop across the CAMQ 12km domain; ~ 250,000 management scenarios and EPIC simulations.  The Fertilizer Emissions Scenario Tool for CMAQ (FESTC) was developed to assist with the creation of these scenarios, simulation submission and transformation of EPIC results into CMAQ-ready input files.

EPIC V0509 has been modified to use the same gridded weather data (aggregated to a daily time step) as CMAQ, and to accept preliminary estimates of daily wet and dry deposition.  Oxidized wet and dry atmospheric N deposition is added to the soil nitrate pool, and reduced wet and dry run atmospheric N deposition is added to the soil ammonium pools. 

EPIC is run for a 25-year spin-up period using statistically generated weather to ensure an initial biogeochemical balance and soil structure that represents the defined management scenario. These initial conditions are then used to begin a year-specific simulation.  The national-scale “spinup” conditions have been evaluated against observation.  Results of this evaluation are then used to further refine regional management scenarios.

Timing
Since most crops receive a fertilizer application at planting, planting date estimation skill is used as an indicator of fertilizer application timing skill.


Reported = USDA Weekly Crop and Weather Report 5 year average
EPIC = 5 year cumulative grid cell area on which planting is predicted to occur.

The management scenario on the left simulates corn planting activity correctly, but the scenario on the right suggests the winter wheat scenario requires further refinement.  Winter wheat is cultivated for grain production, is grazed or supports a combination of both uses.  In our application, we model winter wheat as supporting grain production exclusively.  Our planting date evaluation results are similar to those shown for corn in all USDA farm production areas except the Southern Plains (Texas and Oklahoma).  The USDA extension literature indicates that when winter wheat is intended to be grazed, it is planted about 6 weeks earlier than when it is cultivated for grain production alone.  The graph to the right tells us that production for grazing use dominates in the Southern Plains, and our management scenario for this production area needs to reflect this behavior. 

Annual inorganic fertilizer application (kg/county)
Annual inorganic fertilizer application

 

Yield
This comparison indicates that the EPIC simulations are doing a good job picking up important large-scale geographic patterns, but that we overpredict application rates in the eastern U.S. and underestimate them in the western U.S.  Management scenarios are currently being refined to address these differences.

2002 irrigated grain corn yields are comparable to 5 year EPIC average. Regional drought during 2002 reuced some rainfed grain corn yields as comparable to 5 year EPIC average.

 

Research regarding EPIC for bidirectional CMAQ, including biofuels applications is conducted under the ACE program.  An anticipated DOE sponsored “new release” of EPIC will be used to support Air Climate and Energy (ACE) research to refine soil NO emissions.  Results of the integrated bidirectional CMAQ model are being used to support Future Midwestern Landscapes (FML) research under the Sustainable and Healthy Communtiies (SHC) program.  EPIC management scenarios to explore edge-of-field hydrologic yield are being refined and future climate scenarios will be explored under the Safe and Sustainable Water (SSW) program.  Finally, several ORD research projects that use the USDA Soil and Water Assessment Tool (SWAT) for water quality exploration.   EPIC is the field component of another USDA model, the Agricultural Policy/Environmental Extender (APEX) model, which routes water across multiple agricultural fields.  APEX is the source of the SWAT field component, and APEX results can be used to drive SWAT.

ORD EPIC research is closely coordinated with current and previous USDA research staff responsible for EPIC development (Jimmy Williams, Senior Research Scientist, Texas AgriLife Blackland Research and Extension Center, Temple, TX and Verel Benson, Benson Consulting, Columbia, Missouri).  We are also coordinating EPA EPIC model applications with the Office of Water Hydrologic and Water Quality system (HAWQS) project.

Non-EPA Users:

  • Natural Resources Conservation Service (NRCS, Temple TX and other locations)
  • Universities – Iowa State University, University of Missouri,
  • Texas A & M, Washington State and others
  • The French National Institute for Agricultural Research  (INRA, Toulouse, France)
  • Other Countries – Australia, Syria, Jordan, Canada, Germany, Taiwan (other locations over ¾ of the world)
  • USDA, Agricultural Research Service (ARS) and other research and extension agencies

USDA Applications:

  • 1985 Resource Conservation Act (RCA) analysis
  • 1988 Drought assessment
  • Soil loss tolerance tool
  • Australian sugarcane model (AUSCANE)
  • Pine tree growth simulator
  • Global climate change analysis
  • Farm level planning
  • Drought impacts on residue cover
  • Nutrient and pesticide movement estimates for alternative farming systems for water quality analysis

Code Availability:

  • EPIC is a USDA community model.  Code and user’s guides for the standard distribution version is available online.
  • The EPA application requires modification of the standard EPIC code to meet the needs of the EPA air quality community.  The revised EPIC model and FEST-C interface is currently under development but will eventually be available from CMAS

References
Cooter, E., Bash, J., Benson, V. and Ran, L., 2012.  Linking Agricultural Crop Management and Air Quality Models for Regional to National-Scale Nitrogen Assessments.  Biogeosciences Discussions, 9: 6095-6127.

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