Comparison of site sensitivity of crop models using spatially variable field data from Precision Agriculture

Kurt-Christian Kersebaum, Evelyn Wallor, Domenico Ventrella, Davide Cammarano, Elsa Choucheney, Frank Ewert, Roberto Ferrise, Thomas Gaiser, Pasquale Garofalo, Luisa Giglio, Pietro Giola, Munir Hoffmann, Marcos Laan, Elisabeth Lewan, Ganga Ram Maharjan, Marco Moriondo, Laura Mula, Claas Nendel, Eva Pohankova, Pier Paolo Roggero, Miroslav Trnka, Giacomo Trombi


Site conditions and soil properties have a strong influence on impacts of climate change on crop production. Vulnerability of crop production to changing climate conditions is highly determined by the ability of the site to buffer periods of adverse climatic situations like water scarcity or excessive rainfall.  Therefore, the capability of models to reflect crop responses and water and nutrient dynamics under different site conditions is essential to assess climate impact even on a regional scale. To test and improve sensitivity of models to various site properties such as soil variability and hydrological boundary conditions, spatial variable data sets from precision farming of two fields in Germany and Italy were provided to modellers. For the German 20 ha field soil and management data for 60 grid points for 3 years (2 years wheat, 1 year triticale) were provided. For the Italian field (12 ha) information for 100 grid points were available for three growing seasons of durum wheat. Modellers were asked to run their models using a) the model specific procedure to estimate soil hydraulic properties from texture using their standard procedure and use in step b) fixed values for field capacity and wilting point derived from soil taxonomy. Only the phenology and crop yield of one grid point provided for a basic calibration. In step c) information for all grid points of the first year (yield, soil water and mineral N content for Germany, yield, biomass and LAI for Italy) were provided. First results of five out of twelve participating models are compared against measured state variables analysing their site specific response and consistency across crop and soil variables.

(Main text to be published in a peer-reviewed journal)

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