A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation

被引：20

作者：

Confalonieri, Roberto ^{[1
]}

Bregaglio, Simone ^{[1
]}

Adam, Myriam ^{[2
]}

Ruget, Francoise ^{[3
]}

Li, Tao ^{[4
,21
]}

Hasegawa, Toshihiro ^{[5
]}

Yin, Xinyou ^{[6
]}

Zhu, Yan ^{[7
]}

Boote, Kenneth ^{[8
]}

Buis, Samuel ^{[3
]}

Fumoto, Tamon ^{[5
]}

Gaydon, Donald ^{[9
]}

Lafarge, Tanguy ^{[2
]}

Marcaida, Manuel ^{[4
]}

Nakagawa, Hiroshi ^{[10
]}

Ruane, Alex C. ^{[11
]}

Singh, Balwinder ^{[19
]}

Singh, Upendra ^{[12
]}

Tang, Liang ^{[7
]}

Tao, Fulu ^{[13
,20
]}

Fugice, Job ^{[12
]}

Yoshida, Hiroe ^{[10
]}

Zhang, Zhao ^{[14
]}

Wilson, Lloyd T. ^{[15
]}

Baker, Jeff ^{[16
]}

Yang, Yubin ^{[15
]}

Masutomi, Yuji ^{[17
]}

Wallach, Daniel ^{[18
]}

Acutis, Marco ^{[1
]}

Bouman, Bas ^{[4
]}

机构：

[1] Univ Milan, Cassandra Lab, I-20122 Milan, Italy

[2] CIRAD, UMR AGAP, F-34398 Montpellier, France

[3] INRA, EMMAH UMR1114, F-84914 Avignon, France

[4] Int Rice Res Inst, Los Banos, Philippines

[5] Natl Inst Agroenvironm Sci, Tsukuba, Ibaraki, Japan

[6] Wageningen Univ, Ctr Crop Syst Anal, NL-6700 AP Wageningen, Netherlands

[7] Nanjing Agr Univ, Natl Engn & Technol Ctr Informat Agr, Jiangsu Key Lab Informat Agr, Jiangsu Collaborat Innovat Ctr Modern Crop Prod, Nanjing, Jiangsu, Peoples R China

[8] Univ Florida, Gainesville, FL USA

[9] CSIRO Agr & Food, Brisbane, Qld, Australia

[10] Natl Agr & Food Res Org, Tsukuba, Ibaraki, Japan

[11] NASA, Goddard Inst Space Studies, New York, NY USA

[12] Int Fertilizer Dev Ctr, Muscle Shoals, AL 35662 USA

[13] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100864, Peoples R China

[14] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China

[15] Texas A&M AgriLife Res & Extens Ctr, Beaumont, TX USA

[16] ARS, USDA, Big Spring, TX USA

[17] Ibaraki Univ, Coll Agr, Mito, Ibaraki, Japan

[18] INRA, UMR1248, Agrosyst & Dev Terr, F-31326 Castanet Tolosan, France

[19] CIMMYT, CG Block,NASC Complex, New Delhi 110012, India

[20] Nat Resources Inst Finland Luke, Vantaa 01301, Finland

[21] AgMIP Rice Team, Tsukuba, Ibaraki, Japan

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2016年 / 85卷

基金：

芬兰科学院; 美国国家科学基金会;

关键词：

Model classification; Model parameterisation; Model ensemble; Model structure; Rice; Uncertainty; CROP MODEL; CALIBRATION; WHEAT; UNCERTAINTY; SENSITIVITY; YIELD; WATER; PLASTICITY; EVOLUTION; RESPONSES;

D O I：

10.1016/j.envsoft.2016.09.007

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

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.

引用

页码：332 / 341

页数：10

共 56 条

[1] POTENTIAL FOR USING LONG-TERM FIELD-RESEARCH DATA TO DEVELOP AND VALIDATE CROP SIMULATORS [J].