Analysis and classification of data sets for calibration and validation of agro-ecosystem models

被引：113

作者：

Kersebaum, K. C. ^{[1
]}

Boote, K. J. ^{[2
]}

Jorgenson, J. S. ^{[3
]}

Nendel, C. ^{[1
]}

Bindi, M. ^{[4
]}

Fruehauf, C. ^{[5
]}

Gaiser, T. ^{[6
]}

Hoogenboom, G. ^{[7
]}

Kollas, C. ^{[1
]}

Olesen, J. E. ^{[8
]}

Rotter, R. P. ^{[9
]}

Ruget, F. ^{[10
]}

Thorburn, P. J. ^{[11
]}

Trnka, M. ^{[12
]}

Wegehenkel, M. ^{[1
]}

机构：

[1] Leibniz Ctr Agr Landscape Res, Inst Landscape Syst Anal, D-15374 Muncheberg, Germany

[2] Univ Florida, Dept Agron, Gainesville, FL 32611 USA

[3] Univ Reading, Sch Agr Policy & Dev, Reading RG6 6AR, Berks, England

[4] Univ Florence, Dept Agri Food Prod & Environm Sci, I-50144 Florence, Italy

[5] Deutsch Wetterdienst DWD, Ctr Agrometeorol Res, D-38116 Braunschweig, Germany

[6] Univ Bonn, Inst Crop Sci & Resource Conservat, D-53115 Bonn, Germany

[7] Washington State Univ, AgWeatherNet, Prosser, WA 99350 USA

[8] Aarhus Univ, Dept Agroecol, DK-8830 Tjele, Denmark

[9] Nat Resources Inst Finland Luke, FI-50100 Mikkeli, Finland

[10] INRA, Environm Mediterraneen & Modelisat Agrohydrosyst, F-84914 Avignon 9, France

[11] CSIRO Ecosyst Sci, Townsville, Qld 4102, Australia

[12] Mendel Univ Brno, Inst Agr Syst & Bioclimatol, CZ-61300 Brno, Czech Republic

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2015年 / 72卷

关键词：

Field experiments; Data quality; Crop modelling; Data requirement; Minimum data; Software; DIFFERENT CLIMATIC ZONES; SOIL-MOISTURE SENSORS; SPATIAL VARIABILITY; CROP YIELD; NITROGEN DYNAMICS; ELEVATED CO2; WHEAT; SIMULATION; GROWTH; FIELD;

D O I：

10.1016/j.envsoft.2015.05.009

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Experimental field data are used at different levels of complexity to calibrate, validate and improve agroecosystem models to enhance their reliability for regional impact assessment. A methodological framework and software are presented to evaluate and classify data sets into four classes regarding their suitability for different modelling purposes. Weighting of inputs and variables for testing was set from the aspect of crop modelling. The software allows users to adjust weights according to their specific requirements. Background information is given for the variables with respect to their relevance for modelling and possible uncertainties. Examples are given for data sets of the different classes. The framework helps to assemble high quality data bases, to select data from data bases according to modellers requirements and gives guidelines to experimentalists for experimental design and decide on the most effective measurements to improve the usefulness of their data for modelling, statistical analysis and data assimilation. (C) 2015 Elsevier Ltd. All rights reserved.

引用

页码：402 / 417

页数：16

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