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PC Model

PC Model (version for simulating global wheat potential yield)

The PC model was initially developed using data from sites in China where wheat was grown under optimal irrigation and fertilization, and has been well tested in irrigated sites of China (Qiao et al., 2020). In the current version, we extended the original version of PC model including a scheme to account for water limitation, hence succeeded in simulating wheat potential yield for rainfed regions.

The version includes two scripts (PC_model.R and leaf_area_index.R). The fundamental functions to calculate light use efficiency (LUE), gross primary productivity (GPP), aboveground biomass (AB) and grain yield (yield) are shown in the script “PC_model.R”. The functions for calculating leaf area index based on mass-balance scheme are shown in the script “leaf_area_index.R”. More detailed information about PC model is introduced in Qiao et al. (AFM, 2020; ERL, 2021).

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PC Model

PCmodel (the Productivity model for Crop) is a novel, simply formulated crop model with quantified uncertainties. This model starts with predicting crop GPP from Pmodel (Wang et al. 2017). Then two observation-based allocation relationships from gpp to aboveground biomass, and from aboveground biomass to yield are applied to predict crop yield from Pmodel-based GPP prediction. PCmodel successfully predicts wheat yields at agricultural sites in China. Detailed information about model theory could be found in Qiao et al., Agricultural and Forest Meteorology 2020.

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P Model

P Model (Theory)

The R script below corresponds to the Pmodel version used in Wang et al. Nature Plants (2017) paper. The script includes three sections: (1) specifying the values of two parameters in Pmodel; (2) defining the used functions such as calculating air pressure in the unit of Pascal as a function of elevation; (3) reading the input data of temperature, elevation, photosynthetic photon flux density, vapor pressure deficit, fractional absorbed photosynthetic active radiation and atmospheric CO2 concentration. Here using the standard values as example; (4) the Pmodel code for estimating GPP from inputs data

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P Model V1.0

Pmodel V 1.0 is buildt on the original version of Pmodel proposed by Wang et al. (2017). The version further includes temperature effect on the intrinsic quantum yield and an empirical effect of soil moisture on GPP. More detailed information about this model is introduced in Stocker et al., Geoscientific Model Development 2020.

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