Impact model: pAPSIM-PM


pAPSIM-PM is the run of the pAPSIM model using the Penman-Monteith estimation method for potential evapotranspiration (PET). pAPSIM 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:

Information for the model pAPSIM-PM 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
James Chryssanthacopoulos:, Climate Systems Research, Columbia University (USA)
Joshua W. Elliott:, 0000-0003-0258-9886, Computation Institute, University of Chicago (USA)
Basic information
Spatial aggregation: regular grid
Horizontal resolution: 0.5°x0.5°
Temporal resolution of input data: climate variables: daily
Temporal resolution of input data: co2: annual
Temporal resolution of input data: soil: constant
Input data
Additional input data sets: GGCMI harmonized planting, maturity and fertlizer dataset.
Management & Adaptation Measures
Management: Fixed planting date; harvest at maturity.
Key input and Management
Crops: mai, soy, whe, sor
Planting date decision: fixed planting dates; source of planting date data if applicable
Planting density: Crop specific, default input
Crop cultivars: For cereal crops, we simulate crop Growing Degree Days (GDDs) requirement according to estimated annual GDDs from daily temperature. For soybean, we choose cultivar based on a range of latitude (which determines daylength), simulating 2-3 cultivars for each cell and taking the best performing variant.
Fertilizer application: GGCMI
Irrigation: no restriction on actual water availability, irrigated water applied when water stress
Crop residue: Yes
Initial soil water: Initial conditions (IC) for soil water are reset to full capacity (FC) each season, ~90 days before planting.
Initial soil nitrate and ammonia: Season
Initial soil c and om: Season
Initial crop residue: 1000kg
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, Detailed (explanatory) Gross photosynthesis – respiration, (for more details, see e.g. Adam et al. (2011)) (pasture only)
Yield formation: number of grains and grain growth rate, partitioning during reproductive stages, harvest index modified by water stress (soy)
Crop phenology: temperature, photoperiod (day length), other water/nutrient stress effects considered, vernalization
Root distribution over depth: exponential
Stresses involved: Water stress, Nitrogen stress, Oxygen stress, heat stress
Type of water stress: ratio of soil available water in the root zone to demand of water
Type of heat stress: vegetative , reporductive organ (sink), number of grain (pod) set during the flowering period
Water dynamics: soil water capacity approach with 5 soil layers, Richards approach
Evapo-transpiration: transpiration efficiency
Soil cn modeling: C model, N model, 3 organic matter pools, microbial biomass pool
Co2 effects: Radiation use efficiency, Transpiration efficiency, nutrient use efficiency
Methods for model calibration and validation
Parameters, number and description: Default parameters from site-specific analyses
Spatial scale of calibration/validation: Field scale?