Rights statement: This is the author’s version of a work that was accepted for publication in Science of the Total Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Science of the Total Environment, 651, 1, 2018 DOI: 10.1016/j.scitotenv.2018.09.254
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Global sensitivity analysis of the APSIM-Oryza rice growth model under different environmental conditions
AU - Liu, Junzhi
AU - Liu, Zhangcong
AU - Zhu, A-Xing
AU - Shen, Fang
AU - Lei, Qiuliang
AU - Duan, Zheng
N1 - This is the author’s version of a work that was accepted for publication in Science of the Total Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Science of the Total Environment, 651, 1, 2018 DOI: 10.1016/j.scitotenv.2018.09.254
PY - 2019/2/15
Y1 - 2019/2/15
N2 - 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.
AB - 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.
KW - Parameter sensitivity
KW - Extended FAST
KW - Range of parameter variation
KW - Climate condition
KW - CO2 level
UR - https://doi.org/10.1016/j.scitotenv.2018.09.254
U2 - 10.1016/j.scitotenv.2018.09.254
DO - 10.1016/j.scitotenv.2018.09.254
M3 - Journal article
SP - 953
EP - 968
JO - Science of the Total Environment
JF - Science of the Total Environment
SN - 0048-9697
ER -