Zhang Hongjuan, Zhang Rui, Sun Lina, Li Haolin, Xue Yanling, Zhao Xia, Liu Jiahui, Yuan Chao
College of Water Conservancy and Hydropower Engineering, Gansu Agricultural University, Lanzhou, China.
Liangzhou District Agricultural Technology Extension Center, Wuwei, China.
Front Plant Sci. 2025 Jul 2;16:1600561. doi: 10.3389/fpls.2025.1600561. eCollection 2025.
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.
中国半干旱地区春玉米生产中低效的灌溉和施肥方式导致肥料利用不理想，产量受限。该地区很少有研究充分纳入长期气象数据来优化灌溉和施肥策略。在本研究中，我们采用根区水质模型2（RZWQM2）来评估和优化灌溉与施肥管理措施。利用2022 - 2023年的田间试验数据对模型进行了校准和验证，试验包括两个灌溉水平[75% - 95%（I1）和田间持水量的55% - 75%（I2）]以及三个施肥处理[234.27（F1）、157.5（F2）和157.5千克公顷氮肥（F3），F3加63千克公顷有机肥]。验证后的模型在模拟关键参数方面表现出色，包括2022年和2023年春玉米的土壤含水量（SWC）[平均相对误差（）和归一化均方根误差（）< 15%，一致性指数（）> 0.80]、生物量（> 0.85）、籽粒产量（< 15%）以及NH - N和NO - N含量（< 10毫克千克，和< 15%，> 0.60）。在模拟气候情景下，通过在三个灌溉定额中联合施用60%的氮肥和40%的有机肥，实现了21.54、20.78和17.57吨公顷的最优产量。与300和200立方米公顷的定额相比，250立方米公顷的灌溉定额表现出更高的水分利用效率（）、灌溉水利用效率（）和偏生产力（）。这些研究结果为中国半干旱地区春玉米生产制定可持续的灌溉和施肥策略提供了有价值的见解。
