Predicting the Spatiotemporal Evolution Characteristics of Future Agricultural Water Demand in the Yellow River Basin Under Climate-Change Conditions

The Yellow River Basin is an important grain-production base in China, playing a crucial role in the country's agricultural production and overall national economy and social development. However, due to the impact of climate change, China's food security is facing challenges. Therefore, this article takes the Yellow River Basin as an example to reveal the temporal and spatial evolution patterns of the main crop yields in the basin. Based on a coupled statistical downscaling model (SDSM) and ten General Circulation Models (GCMs) from CMIP5, it estimates the future temporal and spatial evolution characteristics of rainfall and evaporation in the basin. Furthermore, a distributed crop-growth model (AquaCrop) is constructed to reveal the temporal and spatial evolution patterns of agricultural irrigation water requirements from a future perspective, clarifying the impact of multi-source uncertainty on the prediction uncertainty of agricultural irrigation water needs. The results indicate that the ten climate models constructed in this study can be effectively applied to the Yellow River Basin, and their ability to capture light-rain events is superior to that of moderate- and heavy-rain events. The simulation accuracy of the AquaCrop model significantly improves with an increase in precipitation frequency. The agricultural irrigation water demand in the middle and upper reaches of the basin is greater than that in the lower reaches, and the uncertainties from GCMs and RCPs have a significant impact on the uncertainty of agricultural irrigation water demand. The research results provide important references for formulating agricultural development plans for irrigation areas under climate-change conditions and for developing response measures for irrigation areas to cope with climate change.