Using expert knowledge data to validate crop models on local situation data

Cropping system models are widely used tools for simulating the growth and development of crops at field scale. However, it is often difficult to satisfy their detailed input and output data requirements for a proper evaluation of model. In this study, expert knowledge data were used as alternative source to fulfil these data requirements. The model was first calibrated for major crops of the studied area and then evaluated for the same crops by using expert knowledge data. Results showed that the model accurately simulated above-ground biomass and grain yield with a relative root mean square error (RRMSE) of 20% and 17%, respectively. On the other hand, simulated results were less satisfactory for N uptake and cumulated evapotranspiration with RRMSE of 27% and 31%, respectively. The model simulated cumulative variables more accurately than dynamic variables. The results of this study suggest that expert knowledge can be used to get data for intermediate variables rarely measured in experiments used for calibration (green leaf area index, actual evapotranspiration, rooting depth) in typical crop management conditions in the region. This approach enables a global and dynamic evaluation of cropping system models when experimental data is unavailable for large heterogeneous areas in a region.

[1]  Howard T. Odum,et al.  Systems ecology : an introduction , 1984 .

[2]  H. Shugart.  A Theory of Forest Dynamics , 1984 .

[3]  D. L. Scarnecchia,et al.  Fundamentals of Ecological Modelling , 1995 .

[4]  John R. Williams,et al.  The EPIC crop growth model , 1989 .

[5]  L. Mermet.  Participation, strategies and ethics: roles of people in wetland management , 1991 .

[6]  L. Janssen,et al.  Implementation of temporal relationships in knowledge based classification of satellite images. , 1991 .

[7]  K. Loague,et al.  Statistical and graphical methods for evaluating solute transport models: Overview and application , 1991 .

[8]  Michael Power,et al.  The predictive validation of ecological and environmental models , 1993 .

[9]  N Oreskes,et al.  Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences , 1994, Science.

[10]  H. van Keulen,et al.  The 'School of de Wit' crop growth simulation models: a pedigree and historical overview. , 1996 .

[11]  Graeme L. Hammer,et al.  APSIM: a novel software system for model development, model testing and simulation in agricultural systems research , 1996 .

[12]  J. Mailhol,et al.  Sorghum and sunflower evapotranspiration and yield from simulated leaf area index , 1997 .

[13]  Parameter estimation in crop models: exploring the possibility of estimating linear combinations of parameters , 2002 .

[14]  M. Donatelli,et al.  Modelling cropping systems¿highlights of the symposium and preface to the special issues , 2002 .

[15]  James W. Jones,et al.  Adaptation and evaluation of the CROPGRO-soybean model to predict regional yield and production ☆ , 2002 .

[16]  R. Delécolle,et al.  Sensitivity analysis of a crop simulation model, STICS, in order to choose the main parameters to be estimated , 2002 .

[17]  J. Nolot,et al.  Principes et outils de conception, conduite et évaluation de systèmes de culture , 2003 .

[18]  M. Donatelli,et al.  SOILPAR 2.00: software to estimate soil hydrological parameters and functions , 2003 .

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

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

[21]  J. Cavero,et al.  Comparing Penman-Monteith and Priestley-Taylor approaches as reference-evapotranspiration inputs for modeling maize water-use under Mediterranean conditions , 2004 .

[22]  A. Biarnès,et al.  Analyzing the determinants of spatial distribution of weed control practices in a Languedoc vineyard catchment , 2004 .

[23]  Robert Faivre,et al.  Spatialising crop models , 2004 .

[24]  M. Guérif,et al.  Assimilating remote sensing data into a crop model to improve predictive performance for spatial applications , 2005 .

[25]  Nicolas Bécu.  Identification et modélisation des représentations des acteurs locaux pour la gestion des bassins versants , 2006 .

[26]  M. Guérif,et al.  Using crop models for multiple fields , 2006 .

[27]  T. Koontz,et al.  Citizen Participation in Collaborative Watershed Partnerships , 2008, Environmental management.

[28]  Ph. Le Grusseb.  Use of a decision support system and a simulation game to help collective decision-making in water management , 2008 .

[29]  J. Alcamo.  Environmental futures : the practice of environmental scenario analysis , 2008 .

[30]  Rabi H. Mohtar,et al.  Integrating Spatial Soil Organization Data with a Regional Agricultural Management Simulation Model: A Case Study in Northern Tunisia , 2008 .

[31]  M. Donatelli,et al.  Integrated assessment of agricultural systems: a component - based framework for the European Union (Seamless) , 2008 .

[32]  N. Brisson,et al.  Adaptation of the STICS intercrop model to simulate crop growth and N accumulation in pea-barley intercrops , 2009 .

[33]  J. Wery,et al.  APES, an agricultural production and externalities simulator evaluated for two main crops in Midi-Pyrenees , 2009 .

[34]  A. Bégué,et al.  Integrating SPOT-5 time series, crop growth modeling and expert knowledge for monitoring agricultural practices — The case of sugarcane harvest on Reunion Island , 2009 .

[35]  Herman Van Keulen,et al.  CROSPAL, software that uses agronomic expert knowledge to assist modules selection for crop growth simulation , 2010, Environ. Model. Softw..

[36]  G. Bellocchi,et al.  A Component-Based Framework for Simulating Agricultural Production and Externalities , 2010 .

[37]  Martin K. van Ittersum,et al.  Using a cropping system model at regional scale: Low-data approaches for crop management information and model calibration , 2011 .

[38]  Delphine Leenhardt,et al.  Integrating expert knowledge and quantitative information for mapping cropping systems , 2011 .

[39]  M. Ittersum,et al.  Assessing the impact of the Nitrate Directive on farming systems using a bio-economic modelling chain , 2011 .

[40]  Myriam Adam,et al.  Protocol to support model selection and evaluation in a modular crop modelling framework: An application for simulating crop response to nitrogen supply , 2012 .

[41]  Myriam Adam,et al.  A protocol for the conceptualisation of an agro-ecosystem to guide data acquisition and analysis and expert knowledge integration , 2012 .

[42]  H. van Keulen,et al.  A systematic approach for re-assembly of crop models: An example to simulate pea growth from wheat growth , 2013 .