A high-resolution gridded dataset of water footprints for China's major food crops from 2001 to 2020

Abstract. Increasingly unsustainable water use in food systems and rising regional water scarcity jointly pose a critical challenge to food security. Advancing sustainable agricultural water management requires accurate quantification of crop water use, including the contributions of blue and green water and their spatiotemporal dynamics throughout growing seasons, the absence of which impedes reliable estimation of agricultural water requirements and the improvement of water management practices. Here, we integrated multi-source remote sensing datasets with high-resolution crop distribution and phenology data within a detailed water footprint accounting framework. This approach generated in ChinaCropWF (Hua and Wang, 2025; https://doi.org/10.5281/zenodo.18057808), a 1-km, nationwide, daily-resolution dataset spanning 2001–2020, which quantifies blue and green water footprints for China's five major crops. Our dataset shows the total crop water footprints ranked as rice (139.65–193.65 Gm³) > maize (130.22–140.98 Gm³) > wheat (61.15–64.59 Gm³) > soybean (32.05–35.39 Gm³) > potato (0.15–11.31 Gm³). The blue and green water composition was primarily determined by crop-specific traits and regional precipitation regimes. In contrast to the global increase in blue water footprints, China's blue water footprints for major food crops have declined, despite pronounced spatial heterogeneity. By contrast, green water footprints have increased widely across all major cropping regions. By capturing spatial heterogeneity in water volume and use efficiency, ChinaCropWF provides data support for adaptive irrigation, regional water management, and food-water nexus assessments.