| North China Plain (NCP) is one of the most important grain production regions in China. In recent years excessive amount of water and fertilizers have been put into soils to meet the growing demand for food, which has not only weakened the effect of water and fertilizers on increasing yields and reduced water and N use efficiencies (WUE and NUE), but also caused severe environmental problems. Therefore, it is necessary to utilize water and N resources efficiently and keep stable or even higher yields in the meanwhile to ensure the sustainable development of agriculture. In order to explore the best management practices (BMPs), four integrated management practices were designed in Tai’an City of Shandong Province from October2009to June2011:(1) traditional farming practices (FP);(2) optimized combination of cropping systems and fertilization (OPT-1);(3) practice for high yield (HY); and (4) further optimized combination of cropping systems and fertilization (OPT-2). Then the field data of soil water content and nitrate content, crop growth and crop yield were used to calibrate and validate the soil water, heat, carbon, and N simulation (WHCNS) model. Then the model was used to simulate the balance of water and nitrogen under different integrated management practices. Finally, the scenario analysis of the winter wheat-summer maize rotating system under different planting dates, planting density and irrigation and N fertilizer amount were conducted. The main results of our study were as follows:Calibration and validation results showed that the field data of soil water contents, NO3-N concentrations, leaf area index (LAI) and dry matter weight matches well with the simulation. And the values of RMSE, E, d and correlation coefficient between simulated and measured data indicated that the model can simulate water and N dynamics and crop growth in our study area accurately.Simulation of the four growing seasons from2009to2011demonstrated that the annual average grain yield under OPT-1. HY and OPT-2practices were27.6%、56.8%and40.8%higher than that of FP practice respectively. Compared with the FP practice, the annual average total N loss under the OPT-1practice decreased by about28.6%, while the NUE increased by25.7%. The largest annual average grain yield and total N loss occurred in the HY practice (23590kg ha-1and240.6kg N ha-1, respectively). Although the annual average grain yield of the OPT-2practice was15.4%lower than that of HY practice, the total N loss was decreased by about53.8%and NUE was increased by19.2%. Among the four practices, the annual average nitrate leaching under the OPT-2practice was the least and reduced25.5%-60.0%. The order of WUEs for all practices was HY> OPT-2> OPT-1> FP in both wheat and maize seasons. Among the four practices, the OPT-2practice achieved the most preferable results, namely the lowest N loss and the highest NUE at the expense of a slight decrease in grain yield. Therefore, the OPT-2practice was the BMPs among the four practices and should be recommended to maximize the economic and environmental benefits in the study region.Based on the OPT-2practice,5sowing dates and17sowing densities were set per winter wheat season in2007-2012; and5sowing dates and22sowing density were set per summer maize season in 2008-2012. Then responses of crop yield, water drainage, nitrate leaching, gaseous N emission, WUE, and NUE of different planting date and density practices were simulated by WHCNS model. With the sowing date of winter wheat-summer maize delaying, the annual average grain yield showed an increased trend. Hence it is recommended to sow winter wheat around October15th and sow summer maize around June15th. With sowing density of winter wheat-summer maize increasing, the annual grain yield increased firstly and then decreased. The WUE and NUE of different sowing density showed the same trends. In order to identify the optimal sowing density, agronomy factor, environmental factor, and value to cost ratio were selected as the evaluation indices. The results indicated that the optimal sowing density of winter wheat and summer maize is300×104to390×104plants ha-1, and8.4×104to10.2×104plants ha-1, respectively.Based on the OPT-2practice from2009to2010,165scenarios of winter wheat and55scenarios of summer maize combining various amounts of irrigation and fertilization were set. Then the calibrated and validated WHCNS model was used to simulate scenarios mentioned above. Results suggested that: the grain yield increased linearly with the irrigation amount and reached a maximum when irrigation amount increased to251mm in the wheat season and0mm in the maize season. The relationships between grain yield and fertilizer inputs are similar to that between grain yield and irrigation, following a linear then plateau model in both seasons. When fertilizer input was greater than106kg N ha-1in the wheat season and70kg N ha-1in the maize season, the grain yield reached a maximum. In order to identify the BMPs, agronomy factor, environmental factor, and value to cost ratio were selected as the evaluation indices. An osculating value method was used to obtain the BMPs. The results indicated that the treatment with240mm irrigation and60kg N ha-1fertilizer input was the BMPs for wheat season. For maize season, the treatment with0mm irrigation and90kg N ha-1fertilizer input was the BMPs.Based on forty years of meteorological data for the study area (1973-2012), one can estimate the rainfall of different hydrologic years. We used the WHCNS model to optimize the irrigation and fertilizer input for the hydrologic years with rainfall amount of25%,50%and75%, respectively. Simulation results indicated that the optimal irrigation amount was about287,258and276mm for winter wheat in the hydrologic years of25%,50%and75%, respectively. N fertilizer input of wheat season had no effect on the grain yield. There is no need irrigation for maize season in the hydrologic years of25%,50%and75%. The optimal N fertilizer input was about97,133and117kg N ha-1for summer maize in the hydrologic years of25%,50%and75%, respectively. |
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