Simulating maize response to historical climate variability in a main maize-producing region of Portugal

This study evaluates the effect of climate variability on the maize growth cycle (LGC), net irrigation requirements (NIR), grain yield and irrigation water productivity (IWP) in the Coruche region, Portugal, using a bias-corrected climate dataset for a 30-year historical scenario (1971–2000). The AquaCrop-OSPy model was further validated with three years of field data (2021–2023). Three sowing scenarios were simulated: anticipated sowing (AS), traditional sowing (TS), and delayed sowing (DS). Results indicate a warming trend that shortens LGC, with TS LGC ranging from 139 to 177 days. NIR showed substantial interannual variability (ranging for AS: 424–707 mm, TS: 413–696 mm, DS: 460–684 mm). However, with close average NIR values for all sowing dates. The climatic variability impacts the dynamics of production across all sowing dates, but with no significant differences in average grain yield (14.5, 14.2, and 14.0 t ha⁻¹ for AS, TS, and DS, respectively). The results are only statistically significant under severe and extreme drought conditions, where AS is able to enhance grain yield. These findings suggest that anticipating sowing dates can be an advantageous practice to improve maize resilience and productivity under increased water scarcity conditions, considering the designed scenarios, modelling assumptions, regional conditions, and management practices considered.