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	A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation
	Confalonieri R.; Bregaglio, S.; Adam, M.; Ruget, F.; Li, T.; Hasegawa, T.; Yin, X. Y.; Zhu, Y.; Boote, K.; Buis, S.
	2016
关键词	Model classification Model parameterisation Model ensemble Model structure Rice Uncertainty crop models sensitivity-analysis climate-change calibration yield wheat uncertainty water plasticity evolution
英文摘要	For most biophysical domains, differences in model structures are seldom quantified. Here, we used a taxonomy-based approach to characterise thirteen rice models. Classification keys and binary attributes for each key were identified, and models were categorised into five clusters using a binary similarity measure and the unweighted pair-group method with arithmetic mean. Principal component analysis was performed on model outputs at four sites. Results indicated that (i) differences in structure often resulted in similar predictions and (ii) similar structures can lead to large differences in model outputs. User subjectivity during calibration may have hidden expected relationships between model structure and behaviour. This explanation, if confirmed, highlights the need for shared protocols to reduce the degrees of freedom during calibration, and to limit, in turn, the risk that user subjectivity influences model performance. (C) 2016 Elsevier Ltd. All rights reserved.
出处	Environmental Modelling & Software
卷	85
页	332-341
语种	英语
ISSN号	1364-8152
DOI标识	10.1016/j.envsoft.2016.09.007
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/42900]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Confalonieri R.,Bregaglio, S.,Adam, M.,et al. A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation. 2016.

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