Model calibration

To use ORYZA2000 to simulate your own experiments, a set of input files needs to be created as explained in Section 7.1 of the book, ORYZA2000: modelling lowland rice (Bouman et al. 2001). Example model data files (Download HERE) can be used as a start. The experimental data file needs to contain the experimental conditions and data as explained in Section 7.2 of Bouman et al. (2001). Users should go through this data file carefully and adapt each parameter to their own experimental conditions.

Crop parameters

The crop data file is always needed and contains parameters that describe the rice variety under consideration. Most of the crop parameters for rice are generic and can be used for all varieties (Section 7.3 in Bouman et al. 2001). However, some parameters and functions (development rates, assimilate partitioning factors, specific leaf area, relative leaf growth rate, leaf death rate, fraction of stem reserves) are best calibrated specifically for the variety and environment under consideration.

Development rate of the crop is calculated based on the daily increment in heat units for the different phenological stages: basic vegetative phase (from emergence to the start of the photoperiod-sensitive phase); photoperiod-sensitive phase (from the end of the basic vegetative phase to panicle initiation); panicle formation phase (from panicle initiation to flowering); grain-filling phase (from flowering to physiological maturity).

Any dry matter (assimilate) produced by the crop is partitioned between shoots and roots according to partitioning coefficients defined as a function of the phenological development stage. Any assimilate allocated to the shoot is partitioned to the various groups of plant organs: leaves, stems, and storage organs. 

Specific leaf area or leaf thickness is surface area of leaves per unit weight. Relative leaf growth rate is daily increase of leaf area of whole leaves per unit of ground area (leaf area index). Leaf death rate is the decline in leaf biomass due to senescence. Fraction of stem reserves is the amount of assimilates (starch and sugar) that accumulates in the stem (culms and leaf sheaths) and is remobilized or translocated to the storage organ (grains) during ripening. 

These crop parameters should be derived from well-designed and well-implemented field experiments under potential production conditions, i.e. with ample supply of water and nutrients and without insect, pathogen, or weed infestation. The effect of drought, low and high temperatures on spikelet sterility and photoperiod on phenological development may be variety-specific, but dedicated experiments are required to derive these parameter values. Section 7.3 in Bouman et al. (2001) details how to calculate these parameters.

Soil parameters

Under conditions of water or nutrient limitation, the water-stress or nutrient-stress relationships in ORYZA2000 also need to be parameterized. 

For the nitrogen balance of ORYZA2000, indigenous soil N supply needs empirical derivation and an estimate can be derived by comparing N uptake in fertilized and zero-N experiments. Soil N supply can be first estimated from crop N uptake in zero-N treatments, and subsequently fine-tuned by model fitting. Fine-tuning is usually accomplished within a +/- 20% range of first-estimated values. 

The soil data file is needed only when ORYZA2000 is run with a water balance (to simulate rainfed or irrigated conditions). In that case, soil physical parameters (e.g. hydraulic conductivity and soil water retention characteristics can be directly measured and the parameters of the Van Genuchten equations can be derived through curve fitting on the measured soil water retention and conductivity data) that characterize the soil under consideration are required, as explained in Section 7.4 ofBouman et al. (2001).

Water parameters

For each experiment, the soil percolation rate can be estimated from daily observations on field water depths, and then fine-tuned by model fitting (refining the parameter value until simulated field-water depths best agreed with measured field-water depths). Measured groundwater depth data can be entered as boundary conditions in PADDY.