Iran’s water crisis, driven by agriculture as its largest consumer, necessitates a fundamental shift towards smart water demand management. Despite valuable regional studies, the absence of a comprehensive national-scale analysis considering the country’s vast agro-climatic heterogeneity is a key knowledge gap. This research aims to fill this gap by conducting a spatio-temporal assessment of the green and blue water footprint of maize in 23 key agricultural regions of Iran. Using the process-based simulation model SSM-iCrop2, we simulated maize growth, yield, and water balance across 2760 scenarios designed based on a combination of 23 regions, 30-year climate data, and four maturity groups (cultivars). The results revealed a strong hydro-climatic gradient across Iran, ranging from absolute dependence on irrigation in the hot and arid south (blue water footprint more than 700 m³/ton) to a significant 37% green water share in the cool and semi-arid north. The key finding was that this climatic pattern can be disrupted by management decisions; selecting an unsuitable cultivar in Sarpol-e Zahab led to a 54% increase in the blue water footprint compared to the Karaj region (with a similar climate). These findings demonstrate the inefficacy of ‘one-size-fits-all’ policies in Iranian agricultural water management. Optimizing water use therefore requires a transition towards precise, regional approaches, for which we propose the development of climate-smart cultivation atlases as a key strategic tool to enhance water productivity.