Multi-scale Fast Quantification Model for Crop Blue-Green Water Footprint with Physical Process Interpretability

The intensification of land surface evapotranspiration and the increasing frequency of extreme precipitation have resulted in significant temporal and spatial scale changes in the consumption of blue and green water for global crop production. However, due to the complexity of multiple input parameters and the extended computational process of the model, the updated interval for crop blue-green water consumption data worldwide is ten years. This makes it challenging to further elucidate global crop blue-green water consumption dynamics under climate change. To acquire the latest crop blue-green water consumption data more promptly, this study integrates the Fast Track and field crop water requirement approaches. This combination results in a fast quantification model of the blue-green water footprint (WF), suitable for crop production at various temporal and spatial scales with interpretability of physical processes. A quantitative analysis was performed on the spatiotemporal evolution patterns of the WF and the blue-to-total WF ratio of maize production from 2000 to 2021. Additionally, a sensitivity analysis was conducted on the input parameters of model. The results indicate a high R2 between this study and others regarding the blue-to-total WF ratio of maize production, reaching 0.8. The total WF of global maize production reached 859.2×109m3 yr-1 in 2021, a 50% increase compared to 2000, with 33% occurring in East Asia. Regional heterogeneity in the blue-to-total WF ratio of maize production was significant, with the global average ranging from 10% to 12.1%. Among major maize-producing countries, 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. Additionally, the blue-to-total WF ratio of maize production in the United States and South Africa peaked in 2012 and 2015 (20.7% and 30%, respectively), influenced by extreme climate events. The multiyear standard deviation of the blue-to-total water consumption ratio of maize production at the monthly scale surpassed that at the annual scale, with August exhibiting the highest value. Among the four input parameters (precipitation, crop reference evapotranspiration, crop planting date, and crop coefficient), the sensitivity index of precipitation was the highest, with 57 countries exceeding 20, predominantly concentrated in southern Africa. Under the influence of climate change, the blue-to-total WF ratio of maize production has undergone significant changes at multiple temporal and spatial scales. Timely and efficient quantification of blue-green water consumption in crop production aids researchers in accurately clarifying and predicting changes in crop water consumption. This, in turn, facilitates the development of more effective and sustainable agricultural water-saving plans. Simultaneously, it proves beneficial for managers in identifying water hotspots, implementing dynamic water management, and actively responding to climate change.