Abstract
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(-2) nitrogen fertilizer (F3), and F3 plus 63 kg hm(-2) organic fertilizer). The validated model demonstrated excellent performance in simulating key parameters, including soil water content (SWC) [mean relative error (MRE) and normalized root mean squared error (NRMSE) < 15%, consistency index (d) > 0.80], biomass (d > 0.85), grain yield (MRE < 15%), and NH(4) (+)-N and NO(3) (-)-N contents (RMSE < 10 mg kg(-1), MRE and NRMSE < 15%, d > 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(-2) were achieved using a combined application of 60% nitrogen and 40% organic fertilizer across three irrigation quotas. The irrigation quota of 250 m(3) hm(-2) demonstrated superior water use efficiency (WUE), irrigation water use efficiency (IWUE), and partial factor productivity (PFP) compared to quotas of 300 and 200 m(3) hm(-2). These findings provide valuable insights for developing sustainable irrigation and fertilizer strategies for spring maize production in a semi-arid region of China.