This report shows the results of the first multi-year spatially distributed sensitivity analysis carried out on two complex agroecological models. Wheat is the staple food of 1.5 billion people worldwide. Projected trends in wheat global demand reveal risks of food security over the next decades. Systems for large-area crop monitoring and yield forecasting are needed to support agricultural policies, especially in developing countries. Among those crop sys-tems, the most sophisticated ones are based on crop simu-lation models. Published reports of sensitivity analyses performed on different crop models show that parameters related to leaf area expansion are often considered as the most important. Here we show that, on the contrary, photo-synthesis parameters are more relevant under the conditions explored. We carried out the sensitivity analysis on the models WOFOST and CropSyst for wheat simulation in Morocco. Due to the high number of model runs to be performed, a two-step procedure was adopted: The Morris method was used to identify parameters with a negligible effect, and then the Sobol method was applied on remaining parameters. Environmental and management information were obtained from the European Commission MARS da-tabase. Our results show that photosynthesis parameters explained more than 75 % of the total output variance for CropSyst and more than 70 % for WOFOST. On the con-trary, parameters related to leaf area expansion were less relevant. Geographical patterns shown by sensitivity analy-sis results under heterogeneous conditions can help breeders to select specific plant traits, in order to develop phenotypes suitable for specific conditions, e.g., varieties with a higher level of thermal adaptation in the Southern regions.