SUMMARY: Phenological models are considered key tools for the short-term planning of viticultural activities and long-term impact assessment of climate change. In the present study, statistical phenological models were developed for budburst (BUD), flowering (FLO) and veraison (VER) of 16 grapevine varieties (autochthonous and international) from the Portuguese wine-making regions of Douro, Lisbon and Vinhos Verdes. For model calibration, monthly averages of daily minimum (Tmin), maximum (Tmax) and mean (Tmean) temperatures were selected as potential regressors by a stepwise methodology. Significant predictors included Tmin in January–February–March for BUD, Tmax in March–April for FLO, and Tmin, Tmax and Tmean in March–July for VER. Developed models showed a high degree of accuracy after validation, representing 0·71 of total variance for BUD, 0·83 for FLO and 0·78 for VER. Model errors were in most cases < 5 days, outperforming classic growing degree-day models, including models based on optimized temperature thresholds for each variety. Applied to the future scenarios RCP4·5/8·5, projections indicate earlier phenophase onset and shorter interphases for all varieties. These changes may bring significant challenges to the Portuguese wine-making sector, highlighting the need for suitable adaptation/mitigation strategies, to ensure its future sustainability.

Viticulture plays a key role on the Portuguese economic growth. The possibility of obtaining early predictions of viticultural parameters, such as phenology, water status, yield and potential wine characteristics, are of great value for growers, influencing the entire viticultural chain. The present study is a first approach to adapt STICS, a dynamical crop model, to the Portuguese winegrowing conditions and grapevine varieties. Several site specific parameters for climate, soil and management practices are assessed. Varietal specific parameters are measured from vineyards in the Douro and Lisboa winegrowing regions. Three of the most important varieties in the country (Aragonez, Touriga-Franca and Touriga-Nacional) are targeted for model calibration. Overall, the STICS crop model is successful in simulating yield, phenological stages and water stress, but not alcohol content. The relatively high model skill will allow improving the performance of vineyard operations and winemaking practices, namely organizing harvests, vineyard intervention scheduling, irrigation procedures and strategic planning of wineries. STICS can be considered as a feasible decision supporting tool for short- and long-term strategic planning in the Portuguese viticulture, particularly taking into account the projected impacts of climate change. The efficiency gains resulting from the use of this crop model by wine industry stakeholders is expected to increase the competitiveness and sustainability of the wine sector in Portugal.