Abstract
Drip irrigation delivers water uniformly and precisely to the root zone, thereby influencing the soil hydrothermal regime of the soil. While this characteristic makes drip irrigation a promising water-saving technique, there are limited long-term comparative studies on drip irrigation and flood irrigation, which cannot comprehensively and systematically elucidate the impact of water-saving irrigation on soil temperature in Northwest China. We conducted a five-year field experiment from 2017 to 2021, focusing on the comprehensive impact of two irrigation methods (drip irrigation and flood irrigation) on soil temperature at different depths and at different positions (dripper source, root zone, inter-row buffer) during the maize growth periods. The results revealed that soil temperature and meteorological temperature had an extremely significant correlation (p < 0.001), and that the soil surface layer was more susceptible to air temperature influences and was positively correlated with atmospheric temperature. Compared to flood irrigation, drip irrigation increased soil temperature by 1.4%, while soil temperature exhibited a significant negative correlation with soil depth. Specifically, at 0 cm depth, the soil temperature varied most significantly, ranging from 19.79°C to 28.38°C, while at 90 cm, it was 19.98°C - 21°C. Compared to other positions, root zone soil temperature increased by 0.5% to 2.25%. Therefore, drip irrigation not only enhances soil temperature but also optimizes hydrothermal conditions for crop roots. The contribution of this study lies in its integration of multi - year, multi - depth, and multi - positional monitoring under field conditions, which fills a major gap in understanding how irrigation systems influence soil thermal regimes in dry locations. This study provides an actionable theoretical framework for optimizing water use efficiency and crop productivity in water-scarce agroecosystems, while also laying a solid scientific foundation for the development of sustainable management models for agricultural water resources in arid regions.