Spatiotemporal Dynamics and Future Projections of Crop Production Water Footprint Integrated With SWAP‐WOFOST and ARIMA Models

ABSTRACT Assessing the spatiotemporal dynamics of crop production water footprint (WF) at the regional scale is critical for optimizing agricultural water resource management. However, studies quantifying WF in the Hetao Irrigation District (HID) using distributed agro‐hydrological models remain limited, and integration of WF quantification with time‐series models for short‐term forecasting and WF‐driven planting optimization is still lacking. In this study, a calibrated SWAP‐WOFOST model was employed to quantify the total water footprint (WF total ), blue water footprint (WF blue ) and green water footprint (WF green ) of spring wheat, spring maize and sunflower in the HID during 2000–2017. Temporal trends were analysed using time‐series techniques, and the evolution of WF total from 2018 to 2027 was projected using the ARIMA model. Spatial WF patterns were further mapped to optimize crop allocation. The results revealed that WF blue for all crops exhibited a continuous upward trend during 2000–2017, which consistently exceeded WF green that showed a declining trend. Projections indicated a sustained increase in WF total from 2018 to 2027, with spring wheat demonstrating the highest growth rate. Following crop allocation optimization, WF total for all crops decreased significantly, accompanied by enhanced water use efficiency. This study provides scientific insights for water‐efficient crop placement strategies in arid irrigation regions.