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

Experimental field data are used at different levels of complexity to calibrate, validate and improve agro-ecosystem 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. A software is presented to classify and label data suitability for modelling.Data requirements for modelling are specific and vary with model purpose.Quantitative classification of data sets facilitates their use for modelling.Test of model and data consistency improves data usability.Guidelines for experimentalist to improve data suitability for modelling.

[1]  U. Meier,et al.  Growth stages of mono- and dicotyledonous plants , 1997 .

[2]  James W. Jones,et al.  Integrated description of agricultural field experiments and production: The ICASA Version 2.0 data standards , 2013 .

[3]  Kurt Christian Kersebaum,et al.  Modelling water and nutrient dynamics in soil-crop systems: a comparison of simulation models applied on common data sets. , 2007 .

[4]  Sander Bruun,et al.  Initialisation of the soil organic matter pools of the Daisy model , 2002 .

[5]  James W. Jones,et al.  Understanding rainfall spatial variability in southeast USA at different timescales , 2007 .

[6]  P. Shewry,et al.  Modelling predicts that heat stress, not drought, will increase vulnerability of wheat in Europe , 2011, Scientific reports.

[7]  L. A. Richards.  Capillary conduction of liquids through porous mediums , 1931 .

[8]  P. Aggarwal.  Uncertainties in crop, soil and weather inputs used in growth models: Implications for simulated outputs and their applications , 1995 .

[9]  Jørgen E. Olesen,et al.  Cereal yield and quality as affected by nitrogen availability in organic and conventional arable crop rotations: A combined modeling and experimental approach , 2011 .

[10]  Van Genuchten,et al.  A closed-form equation for predicting the hydraulic conductivity of unsaturated soils , 1980 .

[11]  James W. Jones,et al.  The DSSAT cropping system model , 2003 .

[12]  S. Long,et al.  Food for Thought: Lower-Than-Expected Crop Yield Stimulation with Rising CO2 Concentrations , 2006, Science.

[13]  H. J. van der Fels-Klerx,et al.  Changes in time of sowing, flowering and maturity of cereals in Europe under climate change , 2012, Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment.

[14]  Kurt Christian Kersebaum,et al.  Müncheberg field trial data set for agro-ecosystem model validation , 2007 .

[15]  F.W.T. Penning de Vries,et al.  Simulation of plant growth and crop production. , 1983 .

[16]  K. C. Kersebaum,et al.  Site-specific impacts of climate change on wheat production across regions of Germany using different CO2 response functions , 2014 .

[17]  S. Asseng,et al.  The impact of temperature variability on wheat yields , 2011 .

[18]  Doerthe Tetzlaff,et al.  Significance of spatial variability in precipitation for process-oriented modelling: results from two nested catchments using radar and ground station data , 2005 .

[19]  P. van der Voet,et al.  Application of simple interpolation methods in agrometeorology , 1998 .

[20]  H. Keulen,et al.  Simulation of Water Use, Nitrogen Nutrition and Growth of a Spring Wheat Crop , 1987, The Journal of Agricultural Science.

[21]  A. Richardson,et al.  Landscape controls on the timing of spring, autumn, and growing season length in mid‐Atlantic forests , 2012 .

[22]  J. Goudriaan,et al.  ON APPROACHES AND APPLICATIONS OF THE WAGENINGEN CROP MODELS , 2003 .

[23]  G. Y. Tsuji,et al.  Benefits of Models in Research and Decision Support: The IBSNAT Experience , 2002 .

[24]  Mirco Migliavacca,et al.  On the uncertainty of phenological responses to climate change, and implications for a terrestrial biosphere model , 2012 .

[25]  Jeffrey W. White,et al.  Agronomic data: advances in documentation and protocols for exchange and use , 2001 .

[26]  Miroslav Trnka,et al.  Global solar radiation in Central European lowlands estimated by various empirical formulae , 2005 .

[27]  Senthold Asseng,et al.  An overview of APSIM, a model designed for farming systems simulation , 2003 .

[28]  James W. Jones,et al.  The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies , 2013 .

[29]  Philippe C. Baveye,et al.  Moving away from the geostatistical lamppost: Why, where, and how does the spatial heterogeneity of soils matter? , 2015 .

[30]  J. Groot,et al.  Response of wheat to nitrogen fertilization, a data set to validate simulation models for nitrogen dynamics in crop and soil , 1991, Fertilizer research.

[31]  Horst Marschner.  Mechanisms of adaptation of plants to acid soils , 1991 .

[32]  Anthony J. Jakeman,et al.  Progress in integrated assessment and modelling , 2002, Environ. Model. Softw..

[33]  Y. Pachepsky,et al.  Stochastic imaging of soil parameters to assess variability and uncertainty of crop yield estimates , 1998 .

[34]  M. Trnka,et al.  Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models , 2011 .

[35]  M. Bindi,et al.  [Responses of agricultural crops of free-air CO2 enrichment]. , 2002, Ying yong sheng tai xue bao = The journal of applied ecology.

[36]  Jørgen E. Olesen,et al.  Cereal yield and quality as affected by N availability in organic and conventional crop rotations in Denmark: a combined modeling and experimental approach , 2011 .

[37]  A. McBratney,et al.  Soil spatial variability , 2000 .

[38]  H. van Keulen,et al.  Evaluation of models , 1976 .

[39]  S. Malyshev,et al.  Uncertainties in terrestrial carbon budgets related to spring phenology , 2012 .

[40]  F. Gérard,et al.  Soil pH controls the environmental availability of phosphorus: Experimental and mechanistic modelling approaches , 2009 .

[41]  Martin Wegehenkel,et al.  Validation of a soil water balance model using soil water content and pressure head data , 2005 .

[42]  Marion Schroedter-Homscheidt,et al.  Usage of Earth Observation for Solar Energy Market Development: Lessons Learned , 2006 .

[43]  C. T. de Wit,et al.  Simulation of living systems , 1982 .

[44]  Ginger B. Paige,et al.  Comparison of Field Performance of Multiple Soil Moisture Sensors in a Semi‐Arid Rangeland 1 , 2008 .

[45]  G. Fischer,et al.  Crop response to elevated CO2 and world food supply A comment on: Food for Thought... by Long et al., Science 312: 1918-1921, 2006 , 2007 .

[46]  K. C. Kersebaum,et al.  Special Features of the HERMES Model and Additional Procedures for Parameterization, Calibration, Validation, and Applications , 2015 .

[47]  Jesse H. Ausubel,et al.  Climate Impact Assessment , 1985 .

[48]  J. Vrugt,et al.  On the value of soil moisture measurements in vadose zone hydrology: A review , 2008 .

[49]  E. Weber,et al.  Phänologische Entwicklungsstadien der Weinrebe (Vitis vinifera L. ssp. vinifera). Codierung und Beschreibung nach der erweiterten BBCH-Skala , 1994 .

[50]  Klaus Kaiser,et al.  Exchange resin cores for the estimation of nutrient fluxes in highly permeable tropical soil , 2001 .

[51]  C. Stöckle,et al.  CropSyst, a cropping systems simulation model , 2003 .

[52]  Timothy B. Parkin,et al.  Soil Microsites as a Source of Denitrification Variability1 , 1987 .

[53]  R. Knight,et al.  Soil Moisture Measurement for Ecological and Hydrological Watershed‐Scale Observatories: A Review , 2008 .

[54]  H. van Keulen,et al.  Quantitative aspects of nitrogen nutrition in crops , 1991 .

[55]  H. Sinoquet,et al.  An overview of the crop model STICS , 2003 .

[56]  L. Ahuja,et al.  Agricultural System Models in Field Research and Technology Transfer , 2002 .

[57]  Reimund P. Rötter,et al.  Challenges for agro-ecosystem modelling in climate change risk assessment for major European crops and farming systems , 2013 .

[58]  J. Eitzinger,et al.  Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria , 2012, The Journal of Agricultural Science.

[59]  R. Perez,et al.  Effective Accuracy of Satellite-Derived Hourly Irradiances , 1999 .

[60]  James W. Jones,et al.  Uncertainty in Simulating Wheat Yields Under Climate Change , 2013 .

[61]  Graeme L. Hammer,et al.  Future contributions of crop modelling—from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement , 2002 .

[62]  Benoit Gabrielle,et al.  Simulation of carbon and nitrogen dynamics in arable soils: a comparison of approaches , 2002 .

[63]  Abraham Blum.  Crop responses to drought and the interpretation of adaptation , 1996 .

[64]  A. Venezia,et al.  Converting simulated total dry matter to fresh marketable yield for field vegetables at a range of nitrogen supply levels , 2009, Plant and Soil.

[65]  W. Mirschel,et al.  The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics , 2011 .

[66]  Kurt Christian Kersebaum,et al.  How representatively can we sample soil mineral nitrogen , 2006 .

[67]  Jeffrey W. White,et al.  Methodologies for simulating impacts of climate change on crop production , 2011 .

[68]  Kurt Christian Kersebaum,et al.  Operational use of agro-meteorological data and GIS to derive site specific nitrogen fertilizer recommendations based on the simulation of soil and crop growth processes , 2003 .

[69]  Thomas Gaiser,et al.  What role can crop models play in supporting climate change adaptation decisions to enhance food security in Sub-Saharan Africa? , 2014 .

[70]  Miroslav Trnka,et al.  Effect of Estimated Daily Global Solar Radiation Data on the Results of Crop Growth Models , 2007, Sensors.

[71]  Jörg Richter,et al.  Spatial variability of some nutrient constituents of an Alfisol from loess. I: Classical statistical analysis , 1984 .

[72]  Weixing Cao,et al.  Modelling phasic development in wheat: a conceptual integration of physiological components , 1997, The Journal of Agricultural Science.

[73]  Frank Ewert,et al.  Crop modelling for integrated assessment of risk to food production from climate change , 2015, Environ. Model. Softw..

[74]  C. M. Ashraf,et al.  Wheat Seed Germination under Low Temperature and Moisture Stress1 , 1978 .

[75]  Gary A. Peterson,et al.  Soil Attribute Prediction Using Terrain Analysis , 1993 .

[76]  M. Trnka,et al.  Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models , 2012 .

[77]  T. Carter,et al.  Crop-climate models need an overhaul , 2011 .

[78]  H. van Keulen,et al.  Modelling of agricultural production: Weather, soils, and crops , 1986 .

[79]  G. Lemaire,et al.  Relationships between dynamics of nitrogen uptake and dry matter accumulation in maize crops. Determination of critical N concentration , 1999, Plant and Soil.

[80]  Gerard B. M. Heuvelink,et al.  Error Propagation in Environmental Modelling with GIS , 1998 .

[81]  James W. Jones,et al.  Sentinel Site Data for Crop Model Improvement—Definition and Characterization , 2016 .

[82]  Gilles Lemaire,et al.  Decline in Percentage N of C3 and C4 Crops with Increasing Plant Mass , 1990 .

[83]  J. Zadoks.  A decimal code for the growth stages of cereals , 1974 .

[84]  S. Long,et al.  FACE-ing the facts: inconsistencies and interdependence among field, chamber and modeling studies of elevated [CO2] impacts on crop yield and food supply. , 2008, The New phytologist.

[85]  R. J. Wagenet,et al.  Scale issues in agroecological research chains , 1998, Nutrient Cycling in Agroecosystems.

[86]  Roxana Savin,et al.  Effects of timing of heat stress and drought on growth and quality of barley grains , 1999 .

[87]  Michael A. Fullen,et al.  Spatial variability in precipitation within the Hilton Experimental Site, Shropshire, UK (1982–2006) , 2009 .

[88]  A. Schaumberger,et al.  Simple snow cover model for agrometeorological applications , 2010 .

[89]  J. Grossmann,et al.  The extraction of soil water by the suction-cup method: a review , 1991 .

[90]  Sonia I. Seneviratne,et al.  Comparison of four soil moisture sensor types under field conditions in Switzerland , 2012 .

[91]  D. Lobell,et al.  The critical role of extreme heat for maize production in the United States , 2013 .

[92]  J. Bunce,et al.  Effects of pulses of elevated carbon dioxide concentration on stomatal conductance and photosynthesis in wheat and rice. , 2013, Physiologia plantarum.

[93]  A. Peter Annan,et al.  The Early Development of TDR for Soil Measurements , 2003 .

[94]  Sander Janssen,et al.  A database for integrated assessment of European agricultural systems. , 2009 .

[95]  H. Reuter,et al.  Chapter 27 Applications in Precision Agriculture , 2009 .

[96]  H. Reuter,et al.  Modeling Crop Growth and Nitrogen Dynamics for Advisory Purposes Regarding Spatial Variability , 2002 .

[97]  Ali Fares,et al.  Field Calibrations of Soil Moisture Sensors in a Forested Watershed , 2011, Sensors.

[98]  Fulu Tao,et al.  Modeling the response of rice phenology to climate change and variability in different climatic zones: Comparisons of five models , 2013 .

[99]  James W. Jones,et al.  Harmonization and translation of crop modeling data to ensure interoperability , 2014, Environ. Model. Softw..

[100]  Frank Ewert,et al.  Demand for multi-scale weather data for regional crop modeling , 2015 .

[101]  H. van Keulen,et al.  Modelling production of field crops and its requirements , 1987 .

[102]  Eric Justes,et al.  Accuracy, robustness and behavior of the STICS soil-crop model for plant, water and nitrogen outputs: Evaluation over a wide range of agro-environmental conditions in France , 2015, Environ. Model. Softw..

[103]  Valerie O. Snow,et al.  Agricultural production systems modelling and software: Current status and future prospects , 2015, Environ. Model. Softw..

[104]  Walter J. Rawls,et al.  Pedotransfer functions: bridging the gap between available basic soil data and missing soil hydraulic characteristics , 2001 .