Accounting and Evolution of Global Spatial Explicit Blue and Green Water Footprint of Maize Production With Fewer Inputs

Abstract Gridded data updating for crop water consumption differentiating blue (i.e., irrigation water) and green (i.e., soil water) components at global scale is too hysteretic because of heavy working load and time cost of physical‐based models to prompt understanding and management of water for food. This study constructs a model for crop blue‐green water footprint (WF) with interpretability of physical processes. The modeling performance was tested at 5 arcminute resolution with the case for maize over the period 2000–2021, showing higher reliability in WF estimates for countries with high maize production (R 2 = 0.67–0.89) and robustness under extreme climate conditions. Results indicate the total WF of global maize production reached 898.1 × 10 9 m 3 yr −1 in 2021, a 50% increase since 2000. The current global average blue‐to‐total WF ratio was 13%. Markable spatiotemporal heterogeneities in the blue‐to‐total WF ratio of maize production are observed. Among major maize producers, South Africa experienced the most substantial increase in the blue‐to‐total WF ratio, rising from 1.3% in 2000 to 25.9% in 2021 (with highest blue uWF of 231 m 3 t −1 ), influenced by drought. This model provides a feasible approach to accounting and deviation of the non‐negligible variations between blue and green water consumption in crop production based on seven sets of data and fewer formulas.