Using a cropping system model at regional scale: low-data approaches for crop management information and model calibration
Therond, Olivier | Hengsdijk, H. | Casellas, E. | Wallach, D. | Adam, M. | Belhouchette, Hatem | Oomen, R. | Russel, G. | Ewert, D. | Bergez, J.-E. | Janssen, S. | Wery, J. | van Ittersum, M.K. | Institut National de la Recherche Agronomique (INRA) | AGroécologie, Innovations, teRritoires (AGIR) ; Institut National de la Recherche Agronomique (INRA)-Institut National Polytechnique (Toulouse) (Toulouse INP) ; Université de Toulouse (UT)-Université de Toulouse (UT) | Wageningen University and Research [Wageningen] (WUR) | Fonctionnement et conduite des systèmes de culture tropicaux et méditerranéens (UMR SYSTEM) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM) ; Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM) ; Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM) | Universität Bonn = University of Bonn | The University of Edinburgh | SEAMLESS; EU; European Commission [010036-2]
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Показать больше [+] Меньше [-]Английский. Cropping system models are powerful tools for regional impact assessment, but their input data requirements for large heterogeneous areas are difficult to fulfil. Hence, the objectives of this paper are to present low-data approaches for specifying detailed management data required by cropping system models, and for calibrating default crop parameters applied to 12 regions in the European Union (EU). Various downscaling and upscaling procedures for different data types are applied to address both objectives. The Agricultural Production and Externalities Simulator (APES) model is used for illustrative purposes. Combining easy-to-collect regional crop management information and expert knowledge enables to develop generic, expert-based rules for specifying crop management. Effects of these expert-based management rules on simulated yields and nitrogen leaching are illustrated using APES. Simulated yields of grain maize, soft wheat and durum wheat using default crop parameters for phenology are compared with crop yields observed in 12 EU regions. The accuracy of the simulated yields was variable, but generally poor. A regional calibration factor Kpheno is developed based on the temperature sum of the average sowing and harvest dates of the three crops in each region. Applying this calibration factor improved the simulated yields in all cases. Results suggest that it is possible to develop expert-based management rules and to capture yield variation across the EU by using the presented low-data approaches.
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