Optimized irrigation and fertilization for spring maize under warming and wetting climate in a semi-arid region of China.

Inefficient irrigation and fertilizer practices in spring maize production in a Chinese semi-arid region have led to suboptimal fertilizer utilization and yield limitations. Few studies in this region have adequately incorporated long-term meteorological data to optimize irrigation and fertilizer strategies. In this study, we employed the Root Zone Water Quality Model 2 (RZWQM2) to evaluate and optimize irrigation and fertilizer management practices. The model was calibrated and validated using field experimental data during 2022-2023, including two irrigation levels [75%-95% (I1) and 55%-75% field capacity (I2)] and three fertilizer treatments [234.27 (F1), 157.5 (F2), and 157.5 kg hm nitrogen fertilizer (F3), and F3 plus 63 kg hm organic fertilizer). The validated model demonstrated excellent performance in simulating key parameters, including soil water content (SWC) [mean relative error () and normalized root mean squared error () < 15%, consistency index () > 0.80], biomass ( > 0.85), grain yield ( < 15%), and NH -N and NO -N contents ( < 10 mg kg, and < 15%, > 0.60), of spring maize in 2022 and 2023. Under simulated climate scenarios, optimal yields of 21.54, 20.78, and 17.57 t hm were achieved using a combined application of 60% nitrogen and 40% organic fertilizer across three irrigation quotas. The irrigation quota of 250 m hm demonstrated superior water use efficiency (), irrigation water use efficiency (), and partial factor productivity () compared to quotas of 300 and 200 m hm. These findings provide valuable insights for developing sustainable irrigation and fertilizer strategies for spring maize production in a semi-arid region of China.