| Water and nitrogen applications play a key role in maintaining and increasing winter wheat yield. However, unreasonable water and nitrogen applications do harm to its growth, and result in environmental pollution and wasteful resources. Moreover, shortages of resources and increasing food demand no doubt place greater demand for increasing yield and resource use efficiency. Thus, three irrigation levels(Full irrigation,70-80%;Light irrigation,60-70%;Moderate irrigation,50-60% field capacity)and three nitrogen levels(High nitrogen,180 kg N hm-2;Medium nitrogen,135 kg N hm-2;Low nitrogen,90 kg N hm-2) were set to conduct the 2009-2012 experiments. Based on the experiments, water consumption and nitrogen uptake of winter wheat, and the relationship between water consumption and nitrogen uptake & yield were analyzed under different water and nitrogen conditions. Meanwhile, the survey data and literature combined with weather data were collected. Then DSSAT(Decision Support System for Agrotechnology Transfer)-CERES(Crop Estimation through Resource and Environment Synthesis)-Wheat was employed to analyze the impact of water, nitrogen and weather on yield, and to establish tactical and strategic irrigation schedules. Winter wheat yield gap and its causes were analyzed using the collected data based on the CERES-Wheat model, and then proposed the corresponding measures. The main results were as follows:(1) Water consumption and nitrogen uptake as well as the relationship between them both and yield for winter wheat were analyzed under different water and nitrogen conditions. Results showed that total water consumption was the most when higher irrigation and nitrogen were input, but water consumption at different stages varied. Water consumption at the stages of sowing date to stem elongation and heading to harvest was greater than that at the stage of stem elongation to heading, and its intensity at the stages from stem elongation to heading and heading to harvest was larger than that at the stage of sowing date to stem elongation. In addition, water consumption modulus for the stage from stem elongation to harvest were above 0.55. To be specific, water consumption was generally not affected by light irrigation deficit at the early tillering. The combination of moderate irrigation at the early tillering and moderate irrigation at the early stem elongation led to reduction in water consumption, and other treatments were not significantly affected. Water stress at the late growing season did not significantly influence water consumption. Cumulative nitrogen content of leaves and stems in the vegetative stage was higher while they decreased during the reproductive stage. Besides, higher water and nitrogen had the positive effect on cumulative nitrogen and lower water and nitrogen showed the negative effect on it.Yield increased at first and then decreased with increase in water consumption when each treatment had the same nitrogen input. However, the relationship could differ and the correlated coefficient decreased when different nitrogen was added into each treatment. The correlated coefficient between canopy nitrogen content and yield was higher while the coefficient between grain nitrogen content and yield was lower. The nonlinear relationship between water consumption and canopy nitrogen content & yield showed that the contribution of water to yield was larger than that of nitrogen.(2) The applicability of the CERES-Wheat model which could be used to expand the experiments related to water and nitrogen was discussed. Results showed that simulated aboveground biomass, grain yield, leaf area index, canopy nitrogen, cumulative evapotranspiration, water use efficiency and nitrogen partial factor productivity from the measured data were acceptable with normalized root mean square error below 21%. Leaf area index rose as nitrogen application increased and the synergistic impact of irrigation and nitrogen was exerted on leaf area index. Evapotranspiration and canopy nitrogen at maturity increased with irrigation although nitrogen application was different for the periods of 2010-2011 and 2011-2012. The response of both evapotranspiration and canopy nitrogen to fertilizer nitrogen showed the similar trend. Besides, the impact of irrigation on the evapotranspiration was affected by different nitrogen applications under low irrigation conditions. Water use efficiency and nitrogen partial factor productivity were exerted a great influence on by nitrogen fertilizer and the impact of irrigation on them was not significant. Model sensitivity analysis indicated that the grain yield was very sensitive to field capacity among the factors except for the date-related factors and planting date had a significant influence on grain yield by comparison with the factors related to the date. Therefore, the model can be used for the region to assess and optimize winter wheat yield with respect to irrigation and nitrogen applications as well as other influential factors.(3) The impact of different water, nitrogen and climate on yield was made clear. The CERES – Wheat model was also used to analyze the impact of irrigation, nitrogen, and climate on wheat yield using 58-year climate data based on the 2009-2012 experiments. Analyses were conducted by four assumed scenarios using 60 mm of irrigation depth once as well as nitrogen applications(0~300 kg N hm-2 with a step of 60 kg N hm-2). Results showed that yield gap ranged from 0.39 to 5.37 t hm-2 under the experimental conditions. The proper range of nitrogen application was from 120 to 180 kg N hm-2. Irrigation and nitrogen had significant impacts on grain yield and the impact of irrigation on grain yield was greater than that of nitrogen for the 2009-2012 experiment. The contribution of irrigation and nitrogen to yield varied with increase in them, and the contribution of climate to yield was affected by water and nitrogen, ie., water or both of water and nitrogen could weaken the contribution of climate on yield. Solar radiation significantly correlated with yield under the conditions with both irrigation and nitrogen, on the contrary, precipitation had the significant correlation with yield. Relative humidity and maximum temperature consistently correlated with yield under all conditions.(4) The impact of water on yield was further analyzed, and irrigation scheduling under different precipitation conditions was deduced by yield of winter wheat. Standardized precipitation index was used to divide long-term growing seasons into three groups(wet, normal and dry). In addition, the 2003-2004 and 2007-2008 experiments were used and combined with the CERES-Wheat model to determine irrigation scheduling in different growing seasons. In general, yield and water use efficiency were used to evaluate optimal irrigation scheduling. Results showed that yield gap under the experimental conditions was from 1.08 to 4.24 t hm-2, and the range varied in different growing seasons. Measured yield gained from the experiments of 2003-2004 and 2007-2008 matched well with simulated yield by CERES-Wheat. Simulated normalized values agreed well with measured values and maximum simulated and measured values corresponded to the same treatment when the weights of yield and water use efficiency were respectively 0.6 and 0.4. Then two values were used to decide that irrigation schedules in 2003-2004 and 2007-2008 were 75 mm irrigation applied on December 19 th and 75 mm irrigation on April 10 th, but stayed unchangeable based on the original optimum irrigation scheduling. As for the long-term irrigation scheduling, optimal irrigation scheduling almost contained all irrigation schedules available in the normal growing seasons; total irrigation depth for the dry growing seasons was relatively larger than that for the wet growing seasons.(5) The trend of yield potential variability was revealed, and the magnitude of yield gap was determined. Then the causes of yield gap were dicussed and finally the feasible measurements were put fordward. Climate variation led to decrease in yield potential probably due to decrease in solar radiation and increase in temperature. Solar radiation, maximum temperature and relative humidity had highly significant correlations with yield potential while precipitation had no correlation with yield among climate factors. Yield gap ranged from 0 to 6 t hm-2 in the region. Yield gap at each city in the region varied, so did that at each county. Yield gap obtained from different methods differed. The trends of long-term yield gap in the Qishan county, Qian county and Sanyuan County were similar to that of yield potential. Short-term simulated yield gap in the Pucheng county was the highest while that in the Hu county was the lowest. Simulated yield gap was far greater than on-farm yield gap, and yield difference among farmers was relatively large, thereby resulting in the later yield gap.According to the relationship between agricultural input and yield in Shaanxi, increase in yield was due to fertilizer, agronomic measures, irrigation application. Analysis of agricultural input showed that low yield gap for the cities and counties was ascribed to proper fertilizer input, good agronomic measures applied. Analysis of data from literature illustrated that inappropriate cultivar selection, unreasonable fertilizer, improper planting density and inappropriate combination of management and agronomic measures were causes of yield gap.Therefore, to raise yield and close yield gap is to select proper cultivar, to apply reasonable nitrogen and irrigation, and to sow proper seeds combined effectively with agronomic measures. |
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