Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 651, Issue -, Pages 953-968Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2018.09.254
Keywords
Parameter sensitivity; Extended FAST; Range of parameter variation; Climate condition; CO2 level
Categories
Funding
- Natural Science Foundation of Jiangsu Province [BK20150975]
- National Basic Research Program of China [2015CB954102]
- National Natural Science Foundation of China [41601413, 41431177, 31572208]
- Program of Innovative Research Team of Jiangsu Higher Education Institutions of China
- PAPD [164320H116]
- Vilas Associate Award
- Hammel Faculty Fellow Award
- Manasse Chair Professorship from the University of Wisconsin-Madison
- One-Thousand Talents Program of China
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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.
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