Increasing water scarcity and environmental contamination with excess chemical nitrogen fertilizer use necessitate the development of water-nitrogen conservation technology in rice production. Therefore, a 2-year field experiment (2017–2018) was conducted with three water regimes, namely (1) continuous flooding irrigation, CF; (2) safe alternate wetting and drying irrigation, AWD_safe; and (3) severe alternate wetting and drying irrigation, AWD_severe, and four nitrogen application (N_app) rates, namely 0 (N₀), 90 (N₁), 180 (N₂), and 270 (N₃) kg N ha⁻¹, to determine the effects of water regimes and N_app rates on rice yield, total water productivity (WP_i+r) and nitrogen recovery efficiency (NRE). The results demonstrated that the water regime, N_app rate and their interaction showed significant effects on rice yield, WP_i+r and NRE and similar variations were observed in 2017 and 2018. The rice grain yield and WP_i+r (or the water productivity of irrigation, WP_i) significantly increased from N₀ to N₂ treatments but varied little between N₂ and N₃ treatments. The rice yield under AWD_safe was higher than that under AWD_severe, whereas their WP_i+r and WP_i values showed the opposite trends. The WP_i values in 2018 were substantially higher than those in 2017 due to the lower irrigation amount in 2018. The highest rice NRE occurred with the combination of N₂ with the CF and AWD_safe conditions, and it was significantly higher than that under AWD_severe. The dualistic and quadric regression equations of water and N_app rate showed that rice yield, WP_i+r and NRE could not be maximized simultaneously. Based on the maximum likelihood method, it was demonstrated that maintaining the water quantity and N_app rate at 11,000 m³ ha⁻¹ and 160 kg N ha⁻¹ can serve as a suitable strategy to achieve maximal comprehensive benefits for rice grain yield, WP_i+r and NRE in certain regions with water shortage. The optimization model can save approximately 17.0% of water input and 11.1% of N_app rate, respectively, compared to the traditional strategy. However, further research should validate and adapt these technologies in larger-scale fields.

过量使用化学氮肥会增加水的稀缺性和环境污染，因此有必要在水稻生产中开发水氮保持技术。因此，我们进行了为期2年的田间试验（2017-2018年），研究了三种水情，即（1）连续洪水灌溉CF；（2）安全的干湿交替灌溉，AWD_安全；（3）严重的交替干湿灌溉，AWD_严重和四个施氮量（N _app），即0（N ₀），90（N ₁），180（N ₂）和270（N ₃）kg N ha ^-1，以确定水情和N _app的影响水稻产量，总水分生产率（WP _{i + r}）和氮回收效率（NRE）的比率。结果表明，2017年和2018年的水分状况，N _app速率及其相互作用对水​​稻产量，WP _{i + r}和NRE表现出显着影响，并且观察到相似的变化。水稻籽粒产量和WP _{i + r}（或水）灌溉生产力，WP _i）从N ₀增加到N ₂处理，但在N ₂和N ₃处理之间变化不大。AWD_安全下的水稻产量高于AWD_严重者，但其WP _{i + r}和WP _i值显示相反的趋势。由于2018年的灌溉量较低，2018年的WP _i值大大高于2017年。水稻NRE最高的是N ₂与CF和AWD_安全条件的结合，显着高于AWD条件下_严重的。水和N二元和二次回归方程_的应用率表明，水稻产量，WP_{我+ ř}和NRE无法同时最大化。基于最大似然法，证明将水量和N _app速率维持在11,000 m ³  ha ^-1和160 kg N ha ^-1可以作为实现水稻籽粒最大产量，WP的最佳策略。_{i + r}和NRE在某些缺水地区。优化模型可节约水输入的大约17.0％和N 11.1％_应用率，分别为相对于传统的策略。但是，进一步的研究应该在更大范围的领域中验证和适应这些技术。