Global sensitivity analysis of the APSIM-Oryza rice growth model under different environmental conditions

Junzhi Liu, Zhangcong Liu, A. Xing Zhu, Fang Shen, Qiuliang Lei, Zheng Duan

Research output: Contribution to journalArticlepeer-review

11 Citations (SciVal)

Abstract

This study conducted the global sensitivity analysis of the APSIM-Oryza rice growth model under eight climate conditions and two CO2 levels using the extended Fourier Amplitude Sensitivity Test method. Two output variables (i.e. total aboveground dry matter WAGT and dry weight of storage organs WSO) and twenty parameters were analyzed. The ±30% and ±50% perturbations of base values were used as the ranges of parameter variation, and local fertilization and irrigation managements were considered. Results showed that the influential parameters were the same under different environmental conditions, but their orders were often different. Climate conditions had obvious influence on the sensitivity index of several parameters (e.g. RGRLMX, WGRMX and SPGF). In particular, the sensitivity index of RGRLMX was larger under cold climate than under warm climate. Differences also exist for parameter sensitivity of early and late rice in the same site. The CO2 concentration did not have much influence on the results of sensitivity analysis. The range of parameter variation affected the stability of sensitivity analysis results, but the main conclusions were consistent between the results obtained from the ±30% perturbation and those obtained the ±50% perturbation in this study. Compared with existing studies, our study performed the sensitivity analysis of APSIM-Oryza under more environmental conditions, thereby providing more comprehensive insights into the model and its parameters.

Original languageEnglish
Pages (from-to)953-968
Number of pages16
JournalScience of the Total Environment
Volume651
DOIs
Publication statusPublished - 2019 Feb 15
Externally publishedYes

Subject classification (UKÄ)

  • Environmental Sciences

Keywords

  • Climate condition
  • CO level
  • Extended FAST
  • Parameter sensitivity
  • Range of parameter variation

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