Optimization of irrigation and nitrogen fertilizer management for spring maize in northwestern China using RZWQM2
Introduction
The Shiyang River basin in northwest China is a typical inland basin with typical arid to semiarid features (Hu et al., 2016). Spring maize is the most widely grown food crop in the region, accounting for more than 34% of the total crop planted area (Liu et al., 2018). Irrigation water, mainly from groundwater, is the main source of water consumed by crops for high yield due to little precipitation (approximately 160 mm per year) (Hu et al., 2016; Shi et al., 2018). The growing population and shrinking arable land area prompt increased irrigation and nitrogen (N) application for higher maize production. During the growing season, conventional irrigation (typically as flood irrigation) with high irrigation amount (90–120 mm) in each irrigation event and large N fertilizer inputs (> 400 kg ha-1) generally result in nonnegligible water drainage and N leaching, and achieve low water and N use efficiencies (WUE, NUE) (Li et al., 2005). A series of environmental problems associated with excessive water and N application have been reported in the region. The groundwater level in the Shiyang River basin declined by more than 22 m from 1977 to 2015 (Hu et al., 2016). Elevated NO3-N concentrations in water, particularly groundwater, are prevalent, and high N application is one contributing factor (Ma et al., 2009). Thus, conventional irrigation and nitrogen application can hardly ensure sustainable maize production in the study area.
Optimizing irrigation and nitrogen management (INM) for the enhanced NUE and WUE of crops is an effective way to achieve a balance among high crop production, low resource consumption and environmental protection (Fang et al., 2008; Hu et al., 2010; Wang et al. 2016). The application of N synchronizing with spatial and temporal variability in crop demand is considered to be judicious N management, and split N application can be one option to decrease the N application rate and N loss without compromised grain yield (Abrol et al., 2012). Nitrogen and water are codependent management factors that cannot be completely evaluated as independent factors (Hu et al., 2010). A suitable irrigation strategy is beneficial to save either water or N. Deficit irrigation (DI), which imposes timely moderate water stress on crops, is a widely used water-saving strategy (Fereres, 2007). Primary root zone irrigation (PRZI) as a special type of DI, in which soil water monitoring and soil water replenishment are restricted to the primary root zone (PRZ, top 60 cm soil layer), was recommended for surface irrigated maize production by previous studies (Panda et al. 2004; Greaves and Wang, 2017; Zhou et al., 2019). PRZI eliminates the monitoring of soil water status in deep soil layers, is more convenient and can achieve higher WUE with comparable grain yield compared with those of conventional irrigation strategies (Greaves and Wang, 2017; Zhou et al., 2019). Hence, PRZI combined with split N application may be an alternative INM practice to achieve enhanced WUE and NUE with high grain yield of spring maize, the keys of which are the suitable irrigation trigger point (ITP), N application rate and split N method.
The effects of INM on crop yield, WUE, NUE, water drainage and N leaching are the interactions of N application, irrigation, and climate factors (Cameira et al., 2014). The long-term investigation of the performances of a large number of INM options is necessary to achieve the optimal alternative INM practice (Liu et al., 2011). It is usually time-consuming and costly to optimize INM via long-term field experiments. In addition, some observational targets (e.g., water drainage, N leaching) for assessing INM practices are not accurately obtained under field conditions (Hu et al., 2010). By contrast, crop simulation models, taking into account weather-related risks and seasonal variability, are low-cost and efficient tools for simulating the effects of INM practices on crop growth and environment (Fang et al., 2008). Numerous cropping systems models have been developed including RZWQM2 (Ma et al., 2001), DSSAT (Liu et al., 2011), EPIC (Easterling et al., 1997), APSIM (Keating et al., 2003) and AquaCrop (Khoshravesh et al., 2013). RZWQM2 has advanced features of simulating soil water and N dynamics, and shows good performance in simulating the effects of soil water and N deficits on crop growth by coupling with the embedded CERES models (Fang, 2017; Ma et al., 2012). Hence, the RZWQM2 was used to assess INM options and analyze water- and nitrogen-uptake and utilization of spring maize plants in this study.
Optimizing INM has two main approaches: one is to minimize the apparent loss of water and N except crop absorption (e.g., soil evaporation, water drainage and N leaching), and the other is to improve WUE and NUE at the plant level (Abrol et al., 2012). The objectives of this work were to use the RZWQM2 model to (1) analyze characteristics of transpiration and plant N uptake in maize plants and their effects on grain yield, biomass, plant-level WUE (WUEp) and plant-level NUE (NUEp), providing theoretical support for optimizing INM; and to (2) optimize the alternative INM practice claimed by this study, including ITP, N application rate and its distribution between base fertilizer and topdressing fertilizer for enhanced WUE and high grain yield with less water drainage and N leaching.
Section snippets
Study region
A two-year (2016 and 2018) field experiment was established at the Shiyanghe Experimental Station of China Agricultural University (Gansu Province, China, 102°50´E, 37°52´N). The study site has a temperate continental arid climate with mean annual sunshine of about 3000 h. The mean annual potential evaporation is more than 1500 mm with mean annual precipitation of 164 mm. Given the low groundwater table (< 40 m) at the experimental site, groundwater cannot affect the water utilization of spring
Soil water and NO3-N dynamics
The statistical indices in Table 4 suggest that SWC and SNC dynamics were simulated well in either the calibration or validation data set. The SWC simulations in each soil layer resulted in RMSEs between 0.020 cm3 cm-3 (NRMSE = 8.29%, MRD = -16.31%, d-index = 0.55) and 0.041 cm3 cm-3 (NRMSE = 24.52%, MRD = 11.61%, d-index = 0.89). The mean RMSE, NRMSE, MRD and d-index of the SWC simulations across the eight treatments of two growing seasons were 0.034 cm3 cm-3, 20.81%, -5.00% and 0.73 in the
Conclusion
The RZWQM2 model proved its ability to simulate soil water and N dynamics and crop growth with high accuracy after careful model calibration and validation in the study area. We first analyzed characteristics of transpiration and plant N uptake in maize plants using calibrated RZWQM2. The results indicated that the maize plants with high WUEp generally have high NUEp, and reducing transpiration is an effective way to improve either WUEp or NUEp. The conventional INM practices can guarantee a
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We greatly appreciate the careful reviews and valuable comments from the anonymous reviewers and the editors. This research was supported by the National Natural Science Foundation of China (51179163), the Special Fund for Agro-scientific Research in the Public Interest (201503125) and the Natural Science Foundation of Shaanxi Province (2020JM-166). We are grateful to Wuwei Experimental Station staff for their valuable help in the studies. Finally, Shiwei Zhou wants to thank Miss Shuang Li for
References (59)
- et al.
Water and nitrogen budgets under different production systems in Lisbon urban farming
Biosyst. Eng.
(2014) - et al.
Effects of different irrigation regimes on soil moisture availability evaluated by CSM-CERES-Maize model under semi-arid condition
Ecohydrol. Hydrobiol.
(2017) - et al.
Modelling the effect of shelterbelts on maize productivity under climate change: An application of the EPIC model
Agric. Ecosyst. Environ.
(1997) - et al.
Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas
Agric. Water Manage.
(2009) - et al.
Effect of regulated deficit irrigation scheduling on water use of corn in southern Taiwan tropical environment
Agric. Water Manage.
(2017) - et al.
A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand
Field Crop. Res.
(1991) - et al.
An overview of APSIM, a model designed for farming systems simulation
Eur. J. Agron.
(2003) - et al.
Optimizing preplant irrigation for maize under limited water in the High Plains
Agric. Water Manage.
(2017) - et al.
Effects of intercropping and nitrogen application on nitrate present in the profile of an Orthic Anthrosol in Northwest China
Agric. Ecosys. Env.
(2005) - et al.
Optimized single irrigation can achieve high corn yield and water use efficiency in the Corn Belt of Northeast China
Eur. J. Agron.
(2016)
ABA regulated stomatal control and photosynthetic water use efficiency of potato (Solanum tuberosum L.) during progressive soil drying
Plant Sci.
Sources of water pollution and evolution of water quality in the Wuwei basin of Shiyang river, Northwest China
J. Environ. Manage.
Integrating system modeling with field research in agriculture: Applications of the Root Zone Water Quality Model (RZWQM)
Adv. Agron.
RZWQM simulated effects of crop rotation, tillage, and controlled drainage on crop yield and nitrate-N loss in drain flow
Geoderma
Calibrating RZWQM2 model for maize responses to deficit irrigation
Agric. Water Manage.
Effective management of irrigation water for maize under stressed conditions
Agric. Water Manage.
Can the drip irrigation under film mulch reduce crop evapotranspiration and save water under the sufficient irrigation condition? Agric
Water Manage.
Water use efficiencies of grain sorghum grown in three USA southern Great Plains soils
Agric. Water Manage.
Exploring optimal irrigation and nitrogen fertilization in a winter wheat-summer maize rotation system for improving crop yield and reducing water and nitrogen leaching
Agric. Water Manage.
Nitrogen cycle sustainability and sustainable technologies for nitrogen fertilizer and energy management
J. Indian I. Sci.
Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements
Water Resour. Manag.
Crop evapotranspiration: guidelines for computing crop water requirements
Irrig. Drain. Pap.
Maize growth, yield formation and water-nitrogen usage in response to varied irrigation and nitrogen supply under semi-arid climate
Turk. J. Field Crops
Evapotranspiration in high-yielding maize and under increased vapor pressure deficit in the US Midwest
Agric. Environ. Lett.
Regulated deficit irrigation for crop production under drought stress. A review
Agron. Sustain. Dev.
Integrated soil-crop system management for food security
Proc. Natl. Acad. Sci. U.S.A.
Uncertainty assessment of GlobalSoilMap soil available water capacity products: A French case study
Geoderma
Causes for silk delay in a lowland tropical maize population
Crop Sci.
Deficit irrigation. I. Analytical framework
J. Irrig. Drain E. ASCE
Cited by (12)
Modeling the impacts of groundwater depth and biochar addition on tomato production under climate change using RZWQM2
2022, Scientia HorticulturaeCitation Excerpt :The fluctuation of SWC in the top 20 cm of soil becomes more intense due to the frequent occurrence of irrigation events. The simulations of LAI were comparable to that of previous studies (Xu et al., 2020; Zhou et al., 2020). As for the underestimated LAI, it may be due to the high leaf abscission rate (5%/d) set by RZWQM2 (Qi, 2016).
Simulating the effects of irrigation and tillage on soil water, evapotranspiration, and yield of winter wheat with RZWQM2
2021, Soil and Tillage ResearchSimulation of maize crop growth using an improved crop model considering the disintegrated area of biodegradable film
2021, Field Crops ResearchCitation Excerpt :However, some studies have observed opposite trends. For example, Zhou et al. (2020) found that reduced irrigation treatments resulted in reductions in CY by only 2.3 %–9.4 % compared to that under the full irrigation treatment. These contradictory results among experiments could be attributed to differences in soil texture.
Evapotranspiration partitioning, water use efficiency, and maize yield under different film mulching and nitrogen application in northwest China
2021, Field Crops ResearchCitation Excerpt :In contrast, the difference in WUE between RFBM and RFPM under applied N was not significant in the 2019 wet season. The reason might be that drought limited the availability of N fertilizer in the dry season, while heavy rain caused N leaching losses in all plots in the wet season (Zhou et al., 2020). However, in 2019, yield was significantly higher in FPNM than in RFBM and RFPM when N was applied.