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基于APSIM模型的不同水氮条件下旱作麦田N2O排放参数敏感性分析

Sensitivity analysis of N2O emission parameters in dryland wheat fields under different water and nitrogen conditions using the APSIM model

  • 摘要: 作物模型参数敏感性的正确分析结果,有助于提高模型的效率和应用的准确性。为探究作物模型中影响旱作麦田N2O排放的敏感因素,该研究采用扩展傅里叶振幅灵敏度检验(extended Fourier amplitude sensitivity test,EFAST)方法,以春小麦品种‘定西35号’为研究对象,设置5个施氮梯度和3个补灌梯度,对APSIM模型中旱作麦田土壤N2O排放的作物品种参数、土壤参数和气象参数进行全局敏感性分析。结果显示,不同水氮变化组合下,光周期作物敏感指数(photoperiod sensitivity index,PS)是影响旱作麦田N2O排放最敏感的作物品种参数,其敏感性随施氮量的增加而减小,随补灌量的增加而增大。不同水氮变化组合下,土壤容重(bulk density, BD)是影响旱作麦田N2O排放最敏感的土壤参数。其敏感性总体上随施氮量和补灌量的增加而增强。不同水氮变化组合下,日最高温度(max temperature,Max)是影响旱作麦田N2O排放最敏感的气象参数,随施氮量的增加敏感性整体逐渐减小,随补灌量的增加,敏感性整体呈现出先下降后上升的变化趋势。该研究有助于深入理解APSIM模型中旱作麦田土壤N2O排放各参数的敏感性贡献,为模型的参数率定提供了理论基础和重要依据。

     

    Abstract: Water and nitrogen are the key influencing factors on the N2O emissions in the farmland ecosystem cycle, particularly in the dry wheat fields. However, it is often required for the accurate and rapid analysis of the parameter sensitivity in the crop model, in order to enhance the model efficiency and application. This study aims to explore the sensitivity of water and nitrogen factors to the output variables, including the N2O emission parameters in the agricultural production systems simulator (APSIM) crop model. The extended Fourier amplitude sensitivity Test (EFAST) was employed to verify the simulation. The spring wheat variety, 'Dingxi 35' was taken as the research subject. Five gradients of nitrogen application were set as 0, 55, 110, 150, and 220 kg/hm2. Additionally, three gradients of supplemental irrigation were set as 0, 50, and 100 mm. A global sensitivity analysis was conducted on the nine parameters of the crop variety, thirteen soil parameters, and four meteorological parameters related to the soil N2O emissions in dryland wheat fields within the APSIM model. The results indicated that the photoperiodic sensitivity index (PS) was the most sensitive parameter to the N2O emissions under different water and nitrogen treatments. The average values in the global sensitivity index of the PS were 0.518, 0.548, and 0.57, respectively. Their sensitivity decreased with the increasing nitrogen application, whereas, there was an increase with the supplemental irrigation. Furthermore, the soil bulk density (BD) was identified as the most sensitive parameter on the N2O emissions in dry wheat fields under water and nitrogen conditions. The average values in the global sensitivity index of the BD were 0.324, 0.301, and 0.427, respectively. Overall, their sensitivity increased with the higher nitrogen application rates and supplemental irrigation. The maximum daily temperature (Max) was found to be the most sensitive meteorological parameter to the N2O emissions. The average values in the global sensitivity index of Max were 0.554, 0.477, and 0.537, respectively. Their sensitivity generally decreased with the increasing nitrogen application rates, but there was a trend of the first decreasing and then increasing with the supplemental irrigation rates. Notably, there was a great variation in the meteorological parameters on the much smaller values of the N2O flux output in the APSIM model, compared with the crop variety and soil parameters. This finding can provide valuable insights into the sensitivity contributions of the soil N2O emission parameters in the APSIM model. A theoretical basis can also offer a strong reference to calibrate the parameters for applicability and simulation accuracy in the study area. Additionally, the scientific foundation can be gained for water and nitrogen management in dry wheat fields.

     

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