Assessing the spatial and temporal dynamics of crop production water footprint evolution and its drivers in the Yellow River Basin under future climate change

In this study, based on meteorological data from six global climate models (GCMs) under two shared socioeconomic pathways (SSP245 and SSP585) in the Yellow River Basin, the spatial and temporal evolution of maize yields and water footprints from the 2030s to the 2090s were simulated by the AquaCrop model, and the Monte Carlo method was used to parameterize the AquaCrop localization to improve the precision and accuracy of the model. The results found that ET0 showed a distribution of low in the southwest and high in the northeast, and showed an increasing trend in the time series. The mean values of maize yields and water footprints under the SSP245 and SSP285 scenarios were 6.27 ton/ha, 6.19 ton/ha, and 0.76 m3/kg, 0.78 m3/kg, respectively, and the combined view was that yields in the SSP245 scenario were slightly higher and with greater spatial heterogeneity and a lower water footprint. Regarding meteorological factors, relative humidity and average air temperature had more significant effects on the water footprint (direct pathway coefficients of −0.390 and −0.306, respectively), and precipitation had the least effect. The results of the study can provide a scientific basis and data reference for agricultural water management in the Yellow River Basin.