Comparing the site sensitivity of crop models using spatially variable field data from precision agriculture

Impacts of climate change on crop production depend strongly on the site conditions and properties. 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 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 modelers. 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. Only key phenological stages and the highest crop yield within the field for one year were provided for a basic calibration. Modelers were asked to run their models a) using the model specific standard procedure to estimate soil hydraulic properties from texture and b) using fixed values for field capacity and wilting point derived from soil taxonomy and c) using information for all grid points of the first year (yield, soil water and mineral N content for Germany, yield, biomass and LAI for Italy). Results of twelve models are compared against measured state variables analyzing their site response and consistency across crop and soil variables.