<p>This work aims to quantify the extent to which the cultivar parameters in the DSSAT model affect the simulation output at different water and N application levels. To be specific, the extended Fourier amplitude sensitivity test (EFAST) method is used to analyze the global sensitivity and uncertainty of the cultivar parameters on the physiological indices output from the crop growth model under six different treatments. According to the test results, P5 and P1D are the varietal parameters most sensitive to aboveground dry matter and dry matter nitrogen fertilizer utilization; G2, G1, and P1D are the varietal parameters most sensitive to yield and maximum nitrogen at maturity; P1D and P1V are the varietal parameters most sensitive to the maximum leaf area index and dry matter water utilization. Due to the dual stresses of water and nitrogen, there is a significant decrease in the sensitivity of the parameters, with a greater impact caused by water stress treatments. Moreover, uncertainty is introduced to examine the effect of differences among treatments on model simulation. It is discovered that the uncertainty of these parameters is minimized at 200&#xa0;kg/hm<sup>2</sup> of N treatment with or without water stress. Therefore, the best simulation results are obtained at this level of nitrogen application. To sum up, this study provides crucial support for the parameterization and popularization of the DSSAT model under different water and N management treatments.</p>

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Sensitivity and uncertainty analysis of wheat cultivar parameters of the DSSAT model under different water and N treatments

  • Shikai Gao,
  • Pengcheng He,
  • Xuewen Gong,
  • Hao Li,
  • Yihao Liu,
  • Qian Wang,
  • Xiaomeng Wang,
  • Aofeng He,
  • Yuliang Fu

摘要

This work aims to quantify the extent to which the cultivar parameters in the DSSAT model affect the simulation output at different water and N application levels. To be specific, the extended Fourier amplitude sensitivity test (EFAST) method is used to analyze the global sensitivity and uncertainty of the cultivar parameters on the physiological indices output from the crop growth model under six different treatments. According to the test results, P5 and P1D are the varietal parameters most sensitive to aboveground dry matter and dry matter nitrogen fertilizer utilization; G2, G1, and P1D are the varietal parameters most sensitive to yield and maximum nitrogen at maturity; P1D and P1V are the varietal parameters most sensitive to the maximum leaf area index and dry matter water utilization. Due to the dual stresses of water and nitrogen, there is a significant decrease in the sensitivity of the parameters, with a greater impact caused by water stress treatments. Moreover, uncertainty is introduced to examine the effect of differences among treatments on model simulation. It is discovered that the uncertainty of these parameters is minimized at 200 kg/hm2 of N treatment with or without water stress. Therefore, the best simulation results are obtained at this level of nitrogen application. To sum up, this study provides crucial support for the parameterization and popularization of the DSSAT model under different water and N management treatments.