Impact model: PEGASUS

PEGASUS 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

ISIMIP2a
ISIMIP Fast Track

Person responsible for model simulations in this simulation round

Delphine Deryng: delphine.deryng@mail.mcgill.ca, 0000-0001-6214-7241, NewClimate Institute / Humboldt-Universität zu Berlin (Germany)

Rachel F. Warren: r.warren@uea.ac.uk, 0000-0002-0122-1599, University of East Anglia (UK)

Output Data

Experiments: historical
Climate Drivers: None
Date: 2016-02-11

Basic information

Model Version: V1.1

Model Output License: CC BY 4.0

Reference Paper: Main Reference: Global crop yield response to extreme heat stress under multiple climate change futures.

Reference Paper: Other References: Simulating the effects of climate and agricultural management practices on global crop yield.
Müller, C., Elliott, J., Kelly, D. et al. et al. The Global Gridded Crop Model Intercomparison phase 1 simulation dataset. Sci Data,6,50,2019

Resolution

Spatial aggregation: regular grid

Horizontal resolution: 0.5°x0.5°

Input data

Observed atmospheric climate data sets used: WATCH (WFD), WATCH-WFDEI

Additional input data sets: GGCMI harmonized planting, maturity and fertlizer dataset.

Climate variables: tasmax, tas, rlds, rsds, pr

Spin-up

Was a spin-up performed?: Yes

Spin-up design: 4-years based on 1971

Management & Adaptation Measures

Management: Prescribed planting window; fully irrigation assumes water is available to reduce water stress; fix fertiliser inputs from Ag-GRID harmonised dataset

Extreme Events & Disturbances

Key challenges: PEGASUS simulates crop responses to extreme temperature events occuring around anthesis

Key input and Management

Crops: mai, whe(s), soy

Land cover: potential suitable cropland area according to climatic conditions, current harvested areas (Monfreda et al., 2008)

Planting date decision: Simulate planting dates according to climatic conditions or fixed planting dates (Sacks et al., 2010)

Planting density: planting density=0.95

Crop cultivars: Simulate crop Growing Degree Days (GDDs) requirement according to estimated annual GDDs from daily temperature; Number of cultivars

Fertilizer application: NPK (national stat. IFA) Annual application

Irrigation: no restriction on actual water availability, irrigated water applied when water stress, limited water availability, MIRCA 2000: crop specific irrigated area (Portmann et al., 2010)

Initial soil water: 4 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: partitioning during reproductive stages

Crop phenology: temperature (heat unit index)

Root distribution over depth: no roots-just soil depth zone

Stresses involved: Water stress, Nitrogen stress, heat stress

Type of water stress: ratio of supply to demand of water

Type of heat stress: vegetative, number of grain (pod) set during the flowering period

Water dynamics: soil water capacity approach with 2 soil layers

Evapo-transpiration: Priestley -Taylor

Co2 effects: Radiation use efficiency, Transpiration efficiency

Methods for model calibration and validation

Parameters, number and description: 1: light-use efficiency factor (beta factor)

Calibrated values: Specific for each crop

Output variable and dataset for calibration validation: Yield (M3 yield data - gridded dataset of crop specific yields and harvested areas for the year 2000 (Monfreda et al., 2008))

Spatial scale of calibration/validation: Calibration at gridcell level (0.5º resolution)/validation at national level

Temporal scale of calibration/validation: Average for 1997-2004

Criteria for evaluation (validation): Wilmott

Person responsible for model simulations in this simulation round

Delphine Deryng: delphine.deryng@mail.mcgill.ca, 0000-0001-6214-7241, NewClimate Institute / Humboldt-Universität zu Berlin (Germany)

Rachel F. Warren: r.warren@uea.ac.uk, 0000-0002-0122-1599, University of East Anglia (UK)

Output Data

Experiments: historical, rcp26, rcp45, rcp60, rcp85
Climate Drivers: None
Date: 2013-12-17