Impact model: EPIC-TAMU

Sector
Agriculture
Region
global

EPIC-TAMU is one of the 14 models following the ISIMIP2a protocol which form the base of simulations for the ISIMIP2a agricultural sector outputs; for a full technical description of the ISIMIP2a Simulation Data from Agricultural Sector, see this DOI link: http://doi.org/10.5880/PIK.2017.006

Information for the model EPIC-TAMU is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Person responsible for model simulations in this simulation round
Roberto César Izaurralde: cizaurra@umd.edu, 0000-0002-8797-9500, Department of Geographical Sciences, University of Maryland, College Park; Texas AgriLife, Texas A&M University (USA)
Ashwan D. Reddy: areddy01@gmail.com, University of Maryland, Department of Geographical Sciences (USA)
Output Data
Experiments: historical
Climate Drivers: None
Date: 2016-02-11
Basic information
Model Version: EPIC1102
Reference Paper: Main Reference: Kiniry, J. et al. EPIC model parameters for cereal, oilseed, and forage crops in the northern Great Plains region. Canadian Journal of Plant Science,75,679-688,2011
Reference Paper: Other References:
Resolution
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
Input data
Observed atmospheric climate data sets used: WATCH (WFD), WATCH-WFDEI
Key input and Management
Crops: mai, whe(w,s)
Land cover: potential suitable cropland area according to climatic conditions, current harvested areas
Planting date decision: Simulate planting dates according to climatic conditions, planting delayed until 2 deg above base temp
Planting density: Crop-specific
Crop cultivars: Simulate crop Growing Degree Days (GDDs) requirement according to estimated annual GDDs from daily temperature, 2 cultivars for mai
Fertilizer application: NPK at planting
Irrigation: no restriction on actual water availability, irrigated water applied when water stress
Crop residue: No removal
Initial soil water: ISRIC-WISE, 10 year spin up
Initial soil nitrate and ammonia: ISRIC-WISE, 10 year spin up
Initial soil c and om: ISRIC-WISE, 10 year spin up
Initial crop residue: ISRIC-WISE, 10 year spin up
Key model processes
Leaf area development: Dynamic simulation based on development and growth processes
Light interception: Simple approach
Light utilization: Simple (descriptive) Radiation use efficiency approach
Yield formation: fixed harvest index modified by water stress, partitioning during reproductive stages, total (above-ground) biomass
Crop phenology: Temperature (Heat unit index)
Root distribution over depth: Exponential, actual water depends on water availability in each soil layer
Stresses involved: Water stress, Nitrogen stress, Oxygen stress, heat stress, phosphorus, bulk density, aluminum (based on pH and base saturation)
Type of water stress: ratio of supply to demand of water; soil available water in root zone (a balance of the two based on input of 0-1)
Type of heat stress: vegetative (source)
Water dynamics: soil water capacity approach with 3 soil layers
Evapo-transpiration: Penman-Monteith
Soil cn modeling: C model; N model; 3 organic matter pools; microbial biomass pool
Co2 effects: Radiation use efficiency, Transpiration efficiency
Methods for model calibration and validation
Parameters, number and description: Default EPIC parameters; Potential harvest index (maize)
Calibrated values: harvest index=0.35 or 0.55
Output variable and dataset for calibration validation: Yield (SPAM 2000)
Spatial scale of calibration/validation: 0.5º resolution
Temporal scale of calibration/validation: M3 dataset corresponds to the year 2000 (average for years 1997-2004)