Abstract
ORYZA (v3) model was assessed by four water and nitrogen treatments for variability and uncertainty analysis in rice biomass
accumulation and nitrogen assimilation simulation. It was accurate in simulating rice biomass accumulation and nitrogen
assimilation with treatment specific parameters and performed relatively better under flooded irrigation with limited nitrogen
conditions (FS). Variability in treatment specific calibrated parameters was low and fell within an acceptable range, with
highest CV of 11.08% for stem biomass and 18.5% for leaf nitrogen content. Weakness in ORYZA (v3) was exposed when
simulated by parameters from other treatments. Cross-validation errors for panicle biomass (WSO), total above-ground
biomass (WAGT), amount of nitrogen in leaf (ANLV) or panicle (ANSO) were acceptable. However, WAGT accumulation
for FS was identified better than others. For WSO, among all parameters datasets, it performed better for parameters of flooded
irrigation with full nitrogen (FF) and FS. Similarly, FS parameter was superior to others in simulating ANLV, whereas, under
limited water and nitrogen (NFS) was better for ANSO. The uncertainty index, standard deviation and range varied similarly
in different treatments where FS treatment showed lower uncertainty as compared to others. Findings of the current study
suggested that ORYZA (v3) model can efficiently be adapted under varying water and nitrogen limited conditions.
