Climate-change scenarios predict increased water scarcity for agriculture in irrigated regions. Ta design and assess arable cropping system adaptations ta more frequent droughts, soil-crop models are useful and efficient. Here we explore and assess performances of a large range of interacting crop management practices that are likely ta induce changes in crop water use. The soil crop mode! STICS (Brisson et al., 2003) was used ta simulate the impacts of management practices for 4 crops (maize, spring pea, winter wheat, sunflower) in 10 contrasted French pedoclimatic conditions under climate change, Climate scenarios (2006-2050) are based on the RCP 8.5 (Moss et al., 2010). Two ta 3 levels for each tested crop management practice (irrigation calendar and level, sowing date and density, cultivar earliness, N fertilization, management of harvest residues, previous crop) were chosen, and ail combinations were simulated using the simulation platform RECORD (Bergez et al., 2013). Interventions dates were annually adapted ta fit climatic conditions using decision rules. Output variables range from yield ta water fluxes, stress indices and greenhouse gases emissions (GHG). Ta this day, only simulation on maize has been analyzed. Ali tested crop management practices have significant impact on yield. Irrigation management is the strongest driver, explaining between 60 and 86% of variation depending on pedoclimate. Other important drivers are cultivar earliness and sowing conditions in interaction. Water fluxes (drainage, evapotranspiration) and GHG emissions are also driven by residue management. Interventions dates become earlier along the considered period. However, no other significant trend over time was found on STICS outputs for maize. Management effects depend on pedoclimates, suggesting that adaptation of crop management practices will have to be locally specified.