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

文献类型： 外文期刊

第一作者： Liu, Junzhi

作者： Liu, Junzhi;Liu, Zhangcong;Zhu, A-Xing;Shen, Fang;Liu, Junzhi;Lei, Qiuliang;Liu, Junzhi;Liu, Zhangcong;Zhu, A-Xing;Shen, Fang;Liu, Junzhi;Liu, Zhangcong;Zhu, A-Xing;Shen, Fang;Zhu, A-Xing;Duan, Zheng

作者机构：

关键词： Parameter sensitivity; Extended FAST; Range of parameter variation; Climate condition; CO2 level

期刊名称：SCIENCE OF THE TOTAL ENVIRONMENT （ 影响因子：7.963； 五年影响因子：7.842 ）

ISSN： 0048-9697

年卷期： 2019 年 651 卷

页码：

收录情况： SCI

摘要： 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. (c) 2018 Elsevier B.V. All rights reserved.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序