Projected warming and drying trends over the Mediterranean region represent a substantial threat for wheat production. The present study assesses winter wheat yield response to potential climate change and estimates the quantitative effectiveness of using early flowering cultivars and early sowing dates as adaptation options for the major wheat production region of Portugal. A crop model (STICS) is used for this purpose, which is calibrated for yield simulations before projecting future yields. Climate projections over 2021–2050 and 2051–2080 under two emission scenarios (RCP4.5 and RCP8.5) are retrieved from bias-adjusted datasets, generated by a ten-member climate model ensemble. Projected intensification of water deficits and more frequent high-temperature events during late spring (April–June), coinciding with the sensitive grain filling stage, primarily result in continuous mean yield losses (relative to 1981–2010) by − 14% (both scenarios) during 2021–2050 and by − 17% (RCP4.5) or − 27% (RCP8.5) during 2051–2080, also accompanied by increased yield variabilities. Of evaluated adaptation options at various levels, using earlier flowering cultivars reveals higher yield gains (26–38%) than that of early sowings (6–10%), which are able to reverse the yield reductions. The adopted early flowering cultivars successfully advance the anthesis onset and grain filling period, which reduces or avoids the risks of exposure to enhanced drought and heat stresses in late spring. In contrast, winter warming during early sowing window could affect vernalization fulfillment by slowing effective chilling accumulation, thus increasing the pre-anthesis growth length with limited effects on advancing reproductive stage. Crop yield projections and explored adaptation options are essential to assess food security prospects (availability and stability) of dry Mediterranean areas, providing crucial insights for appropriate policymaking.

With global warming, grapevine is expected to be increasingly exposed to water deficits occurring at various development stages. In this study, we aimed to investigate the potential impacts of projected climate change on water deficits from the flowering to veraison period for two main white wine cultivars (Riesling and Müller-Thurgau) in Germany. A process-based soil-crop model adapted for grapevine was utilized to simulate the flowering-veraison crop water stress indicator (CWSI) of these two varieties between 1976–2005 (baseline) and 2041–2070 (future period) based on a suite of bias-adjusted regional climate model (RCM) simulations under RCP4.5 and RCP8.5. Our evaluation indicates that the model can capture the early-ripening (Müller-Thurgau) and late-ripening (Riesling) traits, with a mean bias of prediction of ≤2 days and a well-reproduced inter-annual variability for more than 60 years. Under climate projections, the flowering stage is advanced by 10–20 days (higher in RCP8.5) between the two varieties, whereas a slightly stronger advancement is found for Müller-Thurgau than for Riesling for the veraison stage. As a result, the flowering-veraison phenophase is mostly shortened for Müller-Thurgau, whereas it is extended by up to two weeks for Riesling in cool and high-elevation areas. The length of phenophase plays an important role in projected changes of flowering-veraison mean temperature and precipitation. The late-ripening trait of Riesling makes it more exposed to increased summer temperature (mainly in August), resulting in a higher mean temperature increase for Riesling (1.5–2.5 °C) than for Müller-Thurgau (1–2 °C). As a result, an overall increased CWSI by up to 15% (ensemble median) is obtained for both varieties, whereas the upper (95th) percentile of simulations shows a strong signal of increased water deficit by up to 30%, mostly in the current winegrowing regions. Intensified water deficit stress can represent a major threat for high-quality white wine production, as only mild water deficits are acceptable. Nevertheless, considerable variabilities of CWSI were discovered among RCMs, highlighting the importance of efforts towards reducing uncertainties in climate change impact assessment.