The chaos in calibrating crop models: Lessons learned from a multi-model calibration exercise

被引：47

作者：

Wallach, Daniel ^{[1
]}

Palosuo, Taru ^{[2
]}

Thorburn, Peter ^{[3
]}

Hochman, Zvi ^{[3
]}

Gourdain, Emmanuelle ^{[4
]}

Andrianasolo, Fety ^{[4
]}

Asseng, Senthold ^{[37
]}

Basso, Bruno ^{[6
]}

Buis, Samuel ^{[7
]}

Crout, Neil ^{[8
]}

Dibari, Camilla ^{[9
]}

Dumont, Benjamin ^{[10
]}

Ferrise, Roberto ^{[9
]}

Gaiser, Thomas ^{[11
]}

Garcia, Cecile ^{[4
]}

Gayler, Sebastian ^{[12
]}

Ghahramani, Afshin ^{[13
]}

Hiremath, Santosh ^{[1
]}

Hoek, Steven ^{[15
]}

Horan, Heidi ^{[3
]}

Hoogenboom, Gerrit ^{[5
,16
]}

Huang, Mingxia ^{[17
]}

Jabloun, Mohamed ^{[8
]}

Jansson, Per-Erik ^{[18
]}

Jing, Qi ^{[19
]}

Justes, Eric ^{[20
]}

Kersebaum, Kurt Christian ^{[21
,22
]}

Klosterhalfen, Anne ^{[23
]}

Launay, Marie ^{[24
]}

Lewan, Elisabet ^{[25
]}

Luo, Qunying ^{[26
]}

Maestrini, Bernardo ^{[15
]}

Mielenz, Henrike ^{[27
]}

Moriondo, Marco ^{[28
]}

Zadeh, Hasti Nariman ^{[14
]}

Padovan, Gloria ^{[9
]}

Olesen, Jorgen Eivind ^{[29
]}

Poyda, Arne ^{[30
]}

Priesack, Eckart ^{[31
]}

Pullens, Johannes Wilhelmus Maria ^{[29
]}

Qian, Budong ^{[19
]}

Schuetze, Niels ^{[32
]}

Shelia, Vakhtang ^{[5
,16
]}

Souissi, Amir ^{[33
,34
]}

Specka, Xenia ^{[21
]}

Srivastava, Amit Kumar ^{[11
]}

Stella, Tommaso ^{[21
]}

Streck, Thilo ^{[12
]}

Trombi, Giacomo ^{[9
]}

Wallor, Evelyn ^{[21
]}

机构：

[1] INRAE, UMR AGIR, Castanet Tolosan, France

[2] Nat Resources Inst Finland Luke, Helsinki, Finland

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

[4] ARVALIS Inst Vegetal, Paris, France

[5] Univ Florida, Agr & Biol Engn Dept, Gainesville, FL USA

[6] Michigan State Univ, Dept Earth & Environm Sci, E Lansing, MI 48824 USA

[7] INRAE, EMMAH, UMR 1114, Avignon, France

[8] Univ Nottingham, Sch Biosci, Loughborough, Leics, England

[9] Univ Florence, Dept Agr Food Environm & Forestry DAGRI, Florence, Italy

[10] Univ Liege, Gembloux Agrobio Tech, Plant Sci & TERRA Teaching & Res Ctr, Gembloux, Belgium

[11] Univ Bonn, Inst Crop Sci & Resource Conservat, Bonn, Germany

[12] Univ Hohenheim, Inst Soil Sci & Land Evaluat, Biogeophys, Stuttgart, Germany

[13] Univ Southern Queensland, Inst Life Sci & Environm, Ctr Sustainable Agr Syst, Toowoomba, Qld, Australia

[14] Aalto Univ Sch Sci, Espoo, Finland

[15] Wageningen Univ & Res, Wageningen, Netherlands

[16] Univ Florida, Inst Sustainable Food Syst, Gainesville, FL USA

[17] China Agr Univ, Coll Resources & Environm Sci, Beijing, Peoples R China

[18] Royal Inst Technol KTH, Stockholm, Sweden

[19] Agr & Agri Food Canada, Ottawa Res & Dev Ctr, Ottawa, ON, Canada

[20] CIRAD, Persyst Dept, Montpellier, France

[21] Leibniz Ctr Agr Landscape Res, Muncheberg, Germany

[22] Global Change Res Inst CAS, Brno, Czech Republic

[23] Forschungszentrum Julich, Inst Bio & Geosci IBG 3, Agrosphere, Julich, Germany

[24] INRAE, US 1116, AgroClim, Avignon, France

[25] Swedish Univ Agr Sci SLU, Dept Soil & Environm, Uppsala, Sweden

[26] Hillridge Technol Pty Ltd, Sydney, NSW, Australia

[27] Inst Crop & Soil Sci, Fed Res Ctr Cultivated Plants, Julius Kuhn Inst JKI, Braunschweig, Germany

[28] CNR, IBE, Florence, Italy

[29] Aarhus Univ, Dept Agroecol, Tjele, Denmark

[30] Univ Kiel, Inst Crop Sci & Plant Breeding, Grass & Forage Sci Organ Agr, Kiel, Germany

[31] German Res Ctr Environm Hlth, Inst Biochem Plant Pathol, Helmholtz Zentrum Munchen, Neuherberg, Germany

[32] Tech Univ Dresden, Inst Hydrol & Meteorol, Chair Hydrol, Dresden, Germany

[33] Univ Carthage, Natl Inst Agron Res Tunisia INRAT, Agron Lab, Tunis, Tunisia

[34] Univ Carthage, Natl Agron Inst Tunisia INAT, Tunis, Tunisia

[35] Lincoln Agritech Ltd, Hamilton, New Zealand

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

[37] Tech Univ Munich, Dept Life Sci Engn, Freising Weihenstephan, Germany

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2021年 / 145卷

基金：

芬兰科学院; 美国食品与农业研究所; 美国国家科学基金会;

关键词：

Calibration recommendations; Process-based models; Parameter estimation; Phenology; MULTIOBJECTIVE CALIBRATION; PARAMETERIZATION; UNCERTAINTY; SYSTEMS; IDENTIFIABILITY; COEFFICIENTS; SIMULATION; PHENOLOGY; SOFTWARE; GENCALC;

D O I：

10.1016/j.envsoft.2021.105206

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of process-based models and has an important impact on simulated values. We propose a novel method of developing guidelines for calibration of process-based models, based on development of recommendations for calibration of the phenology component of crop models. The approach was based on a multi-model study, where all teams were provided with the same data and asked to return simulations for the same conditions. All teams were asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices.

引用

页数：11

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