Search

The conventional double cropping system of winter wheat and summer maize (WW-SUM) in the North China Plain (NCP) consumes a large amount of water and chemical fertilizer, threatening the sustainable development of agriculture in this region. This study was based on a three-year field experiment of different cropping systems (2H1Y—two harvests in one year; 3H2Y—three harvests in two years; and 1H1Y—one harvest in one year). The 2H1Y system had three irrigation–fertilization practices (FP—farmer's practice; RI—reduced input; and WQ—Wuqiao pattern in Wuqiao County, Hebei Province). A soil–crop system model (WHCNS—soil water heat carbon nitrogen simulator) was used to quantify the effects of different cropping systems on water and nitrogen use efficiencies (WUE and NUE, respectively), and to explore the trade-offs between crop yields and environmental impacts. The results showed that annual yield, water consumption, and the WUE of 2H1Y were higher than those of the 3H2Y and 1H1Y systems. However, local precipitation during the period of crop growth could only meet 65%, 76%, and 91% of total water consumption for the 2H1Y, 3H2Y and 1H1Y systems, respectively. Nearly 65% of irrigation water (groundwater) was used in the period of wheat growth that contributed to almost 40% of the annual yield. Among the three patterns of the 2H1Y system, the order of the WUE was 2H1Y_RI > 2H1Y_WQ > 2H1Y_FP. Compared to 2H1Y_FP, the total fertilizer N application rates in 2H1Y_WQ, 2H1Y_RI, and 3H2Y were reduced by 25%, 65%, and 74%, respectively. The 3H2Y system had the highest NUE of 34.3 kg kg−1, 54% greater than the 2H1Y_FP system (22.2 kg kg−1). Moreover, the 3H2Y system obviously reduced nitrate leaching and gaseous N loss when compared with the other two systems. The order of total N loss of different cropping systems was 2H1Y (261 kg N ha−1) > 1H1Y (78 kg N ha−1) > 3H2Y (70 kg N ha−1). Considering the agronomic and environmental effects as well as economic benefits, the 3H2Y cropping system with optimal irrigation and fertilization would be a promising cropping system in the NCP that could achieve the balance between crop yield and the sustainable use of groundwater and N fertilizer. [ABSTRACT FROM AUTHOR]

[Display omitted] • Parallel computing framework is introduced to upscale agroecosystem model. • The new model well reproduced soil and crop variables in North China Plain. • The optimum irrigation water and fertilizer N demands were estimated. • The model shows a potential value to optimize regional water and N management. Process-based agroecosystem model is difficult to apply at the regional scale due to the complexity of model parameterization and execution efficiency. Thus, developing a regional agroecosystem model is challenging. In this study, a parallel computing framework is introduced to upscale an agroecosystem model (WHCNS model) from field to regional scale by integrating parallel computing, inversing modeling, and spatial calculation. The newly developed model was tested in the North China Plain (NCP) for modeling water consumption, N fate, and crop growth for winter wheat–summer maize rotation system under different water and N management practices. The optimum irrigation water and fertilizer N demands of winter wheat–summer maize system was estimated based on the auto-irrigation and auto-fertilization component in the model. Multisite testing showed that the model well reproduced soil water and N dynamics, crop biomass, LAI, yield, and crop N uptake, with R2 exceeding 0.886. The estimated annual average irrigation water and fertilizer N demands of winter wheat–summer maize rotation system was 395.8 mm and 529.5 kg N ha−1, respectively. Winter wheat was the major consumer of irrigation water and fertilizer N, accounting for 79.2 % and 54.4 % of annual irrigation water and chemical N fertilizer use, respectively. These results suggested that winter wheat was a crop with high water and fertilizer N demand in the NCP. The RegWHCNS model has potential value to assess and optimize regional water and N management for intensive agricultural-production systems. This study can provide as a scientific reference to upscale agroecosystem models from field to region for other agroecosystem models. [ABSTRACT FROM AUTHOR]

Water scarcity and nitrate contamination in groundwater are serious problems in the North China Plain (NCP). The objective of this study was to compare the effects of farmer's practice and optimal water and nitrogen management on nitrate leaching, and water and nitrogen use efficiencies (WUE, NUE) during winter wheat season in the NCP. A winter wheat experiment with four treatments (traditional irrigation plus traditional fertilizer, W1N1; traditional irrigation plus optimal fertilizer, W1N2; optimal irrigation plus traditional fertilizer, W2N1; optimal irrigation plus optimal fertilizer, W2N2) was conducted from October 1999 to June 2001 in Beijing suburban. The soil–plant system, water and solute transport model was calibrated and validated based on the data collected from the experimental field, then the model was used to simulate the water movement, nitrogen (N) transport, and crop growth process. The results showed that the simulated soil water content, nitrate concentration in the soil profile, leaf area index, crop N uptake, and grain yield were all in good agreement with the measured data. The simulated results indicated that the improved management of water and fertilizer practice could increase crop yield, and reduce water drainage, nitrate leaching, and gaseous N loss compared to farmers' practice. WUE and NUE under improved practice were 1.36 kg m−3and 34.9 kg kg−1N−1in 2000, 1.07 kg m−3and 31.5 kg kg−1N−1in 2001, respectively. Compared to farmers' practice, the optimal management practice can save water about 4–19%, water drainage decreased 50–65%, N leaching reduced over 90% and gaseous N loss decreased about 70%, at same time leading to an increase in WUE and NUE by 10.6% and 10.3% in 2000, 64.5% and 98.3% in 2001, respectively. [ABSTRACT FROM AUTHOR]

Water shortage and reactive N (Nr) release from excessive fertilization are major challenges for sustainable grain production in the North China Plain (NCP). Alternative cropping systems in this region must be explored because traditional winter wheat and summer maize (WW-SM) rotation is maintained at the cost of high consumption of irrigation water and N loss to the environment. In this study, a soil–crop system model (WHCNS, soil water heat carbon and N simulator) and a life cycle assessment were integrated to analyze and evaluate water footprint (WF) and N footprint (NF) for alternative cropping systems of wheat and maize (2H1Y_FP, two harvests in 1 year with farmer's practice; 2H1Y_RI, two harvests in 1 year with reduced inputs; 1H1Y, one harvest in 1 year with reduced inputs; and 3H2Y, three harvests in 2 years with reduced inputs) in the NCP. Results showed that NH 3 volatilization and NO 3 − leaching are the main hot spots of NF for different crops. For the composition of WF, blue and green WF contributed largely to the total WF of wheat and maize, respectively, and the proportion of gray WF for maize could be decreased by 30% with the reduction in fertilizer amount. The yearly average NF (kg N-eq t−1 y−1) showed the following order: 1H1Y (2.65) <3H2Y (3.41) <2H1Y_RI (6.15) <2H1Y_FP (17.46), and the yearly average WF (m3 t−1 y−1) showed the same order as follows: 1H1Y (565.22) <3H2Y (830.15) <2H1Y_RI (1162.19) <2H1Y_FP (1633.18). Among the compared cropping systems, the 1H1Y and 3H2Y modes as potential alternatives to traditional WW-SM cropping systems showed advantages of sustaining groundwater exploitation and mitigating groundwater nitrate contamination in the NCP. However, the two modes compromised 33%–37% and 20%–25% of crop yield in comparison with those of 2H1Y systems. By considering the site-specific climate and soil conditions, the WHCNS model-based WF and NF analyses could serve as an accurate and effective tool for screening various cropping systems in clean agricultural production. • The WHCNS model is incorporated into the life cycle NF and WF assessment. • Spring maize has lower WF gray (7–22%) and higher WF green (39–70%) than winter wheat and summer maize. • The NF is dominated by NH 3 volatilization (46–64%) and NO 3 − leaching (6–38%). • 1H1Y and 3H2Y are favorable due to reduced WF (29–65%) and NF (45–85%) compared to 2H1Y mode. [ABSTRACT FROM AUTHOR]

The impact of soil nutrient depletion on crop production is a thoroughly researched issue; however, robust assessments on the impact of climate change on water and N fluxes in agroecosystem are lacking. The complexity of soil water and N fluxes in response to climate change under agroecosystems makes simulation-based approaches to this issue appealing. This study evaluated the responses of crop yield, soil water, and N fluxes of a wheat–maize rotation to two Representative Concentration Pathways climate scenarios (RCP4.5 and RCP8.5) at Tai'an, a representative site on the North China Plain (NCP). Results showed that the mean air temperature and accumulated precipitation for both winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.) growing seasons changed in both magnitude and pattern under various climate scenarios. The temperature increases shortened the growth periods of these two crops by more than 13 days and decrease summer maize yields (P < 0.05). These results are illustrated by lower yield results associated with RCP4.5 (20.5%) and RCP8.5 (19.3%) climate scenarios, respectively. During the winter wheat growing season, water drainage examined in the climate scenarios was significantly higher (more than double) than the baseline, and there was no significant change to nitrate leaching and denitrification. In the summer maize growing season, with continuously rising temperatures, the ranking for evaporation was in the order baseline < RCP4.5 < RCP8.5, however, the opposite ranking applied for transpiration and evapotranspiration. The increase in water drainage was 1.4 times higher than the baseline, whereas the nitrate leaching in soil significantly decreased. Our simulation results provide an opportunity to improve the understanding of soil water and N fluxes in agroecosystems, which can lead to deficient or excess N under future climate conditions. [ABSTRACT FROM AUTHOR]

Efforts to enhance wheat quality without compromising yield are imperative in the context of climate change. However, the quantification of management measures that simultaneously elevate wheat protein concentration, especially its components, while maintaining yield has been scarcely addressed due to its inherent complexity. In this study, we investigated the impact of various combinations of sowing dates, nitrogen fertilizer, and irrigation on improving the protein concentration of strong gluten winter wheat (Jimai 20) using a validated wheat grain protein component simulation model in Tai'an, Shandong. Our results indicate that climate change between 2031 and 2060 is anticipated to cause a significant decrease in wheat yield and an increase in wheat protein concentration compared to the period from 1981 to 2010. Albumin and globulin are projected to decrease, while gliadin and glutenin are expected to increase, respectively. The average glutenin-to-gliadin ratio in the baseline is 1.096, whereas in scenarios SSP2–4.5 and SSP5–8.5, it is 1.093 and 1.102, respectively. Adapted measures can effectively synergize to enhance both wheat protein quality and yield under climate change. Specifically, delaying sowing and reducing nitrogen application to 210–240 kg·ha−1 with 200–240 mm of irrigation contribute to maintaining yields at the current conventional treatment level. Furthermore, these practices result in a 3.89 % and 0.13 % increase in grain protein concentration, and a 1.19 % and 6.02 % enhancement in the glutenin-to-gliadin ratio under scenarios SSP2–4.5 and SSP5–8.5, respectively, compared to conventional treatments. This comprehensive analysis provides valuable insights into practical strategies for synergistically improving wheat yield and protein quality in the face of climate change. • Adaptive measures ease the negative correlation between grain protein concentration and yield under climate change. • Increasing grain protein requires more nitrogen and less irrigation compared to enhancing wheat yield. • Delayed sowing, reduced irrigation and nitrogen enhance grain protein without yield penalty under climate change. [ABSTRACT FROM AUTHOR]

Highlights • Groundwater level dynamics and crop production under different cropping systems were compared. • The groundwater levels of current cropping system decreased faster than other cropping systems. • Groundwater levels would stop falling when the current planting area of winter wheat decreased by 76%. • The SNWT project has to provide 50% of irrigation water to prevent groundwater decline without reducing yield. Abstract Over-exploitation of groundwater for irrigation has led to a series of ecological and environmental problems in the North China Plain (NCP). Identifying the water consumption and groundwater level dynamics under different cropping systems can help to develop groundwater neutral system in the NCP. The WHCNS (soil Water, Heat, Carbon and Nitrogen Simulator) model was applied to quantify the effects of different cropping systems (2H1Y, two harvests in one year; 3H2Y, three harvests in two years; and 1H1Y, one harvest in one year) on groundwater use and crop growth, and to explore the trade-offs of possible scenarios on the decline of groundwater level and cereal yield. Results showed that WHCNS performed well in simulating soil water content, leaf area index, dry matter and crop yield, as well as groundwater level dynamics, with the Nash and Sutcliffe Efficiency > 0.4 and index of agreement > 0.8. The simulated results indicated that the groundwater levels of 2H1Y decreased faster than those of other cropping systems, at a decline rate of 0.33 m yr−1. Irrigation of 300 mm yr−1 for the remaining high yield of winter wheat mainly resulted in the decline of groundwater level in the NCP. Scenario analyses showed that the groundwater levels would stop decreasing when the current planting area of winter wheat decreased by 76%. However, the reduction of wheat planting area (scenario 1) will also decrease the annual yield by 27% (from 13,547 to 9909 kg ha−1). Fallowing (scenario 2) may reduce annual yield by 50% (from 13,547 to 6834 kg ha−1) in order to maintain groundwater level. The SNWT (South to North Water Transfer) project (scenario 3) may have to provide 50% of irrigation water (130 mm yr−1), to prevent groundwater decline while maintaining the current yield. Scenario 3 could be better than scenario 1 only if the water price was less than 8 ￥m-3. In the future, reducing winter wheat planting area (especially for low-yield cropland) may be a good option to mitigate groundwater decline while maintaining relatively high yield and income for local farmers in the NCP. [ABSTRACT FROM AUTHOR]

• Four different representative N dilution curve approaches was compared. • WHCNS model performed well in simulating soil water and N supply. • The M2 method performed well using the minimum input parameters. • The smaller the crop water and N stresses, the larger the uncertainty of crop N uptake modeling. Crop nitrogen (N) uptake is a key process in soil-crop models. This process affects crop growth and soil N cycling and determines crop quality. However, crop N uptake modeling remains uncertain because of the various N dilution curve approaches adopted in soil-crop models. In this study, four different representative N dilution curve approaches (i.e., DAISY, M1; CERES and RZWQM, M2; EPIC, M3; and CROPSYST or STICS, M4) were incorporated into a soil-crop model platform (WHCNS), and their effects on crop N uptake and crop growth simulation under different water and N stresses were evaluated via global sensitivity analysis methods. The three-year field experiment data of winter wheat-summer maize rotation under different water and N management practices were used to test the model. Results showed that the WHCNS model performed well in modeling the supplies of soil water and mineral N. The values of statistical indices for crop N uptake, LAI, dry matter and yield simulation by the four methods were within the acceptable ranges, and had the relative mean square error (RRMSE) < 24 %, index of agreement (IA)> 0.81 and Nash and Sutcliffe index (NSE) > 0.37. However, the M2 method performed well using the minimum input parameters, and hence recommended to simulate crop N uptake in soil-crop models. In this study, the dataset of high water and N input treatment was more suitable for model parameter estimation to reduce uncertainty, and the datasets of middle and low water and N input treatments was appropriate to validate the model. These information were useful to guide selecting the modeling method and the model calibration dataset. [ABSTRACT FROM AUTHOR]