Increasingly frequent extreme weather events borne by intensification of the global water cycle threaten food security and long-term sustainability. Breeding climate-resilient wheat (Triticum aestivum L.) genotypes may mitigate adverse effects of extreme events on crop productivity. Process-based eco-physiological modelling offers a powerful means to better target and accelerate development of new crop genotypes. To reveal crop traits conductive to long-term yield improvement in the target population of environments, we constructed hypothetical genotypes underpinned by step-wise variation in parameters regulating phenology, yield and waterlogging tolerance. We then conducted a genotype by environment by management factorial analysis using locations distributed across the entire cereal cropping zone in mid-China under shared socioeconomic pathways SSP5-8.5, with a time horizon centered on 2080. Our results showed that when incident solar radiation was not limiting carbon assimilation in regions (e.g. Jiangsu and Anhui), ideotypes with higher grain yields were characterised by earlier flowering, higher radiation-use efficiency and larger maximum kernel size. At sites with limited solar radiation (e.g. around 1300 MJ m-2 during the growing season in Sichuan and Hubei), crops required longer growing periods to realise genetic yield potential, although higher radiation-use efficiency and larger maximum kernel size were again prospective traits enabling higher rates of yield gains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity (-20%). Ideotypes with optimal G×M could mitigate yield penalty caused by waterlogging by up to 15% under future climates. These results help distil promising crop trait by best management practice combinations that enable higher yields and robust adaptation to future climates and more frequent extreme climatic events, including flash flooding and soil waterlogging.