| Multi\|objective optimization of spring wheat yield and soil N2O emission parameters based on APSIM model using NSGA-II algorithm |
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| DOI：10.7606/j.issn.1000-7601.2026.03.23 |
| Key Words: spring wheat soil N2O emission APSIM model EFAST method NSGA-II multi\|objective optimization algorithm sensitivity analysis |
| Author Name | Affiliation | | SU Wanyi | College of Information Science and Technology, Gansu Agricultural University, Lanzhou, Gansu 730070, China | | DONG Lixia | College of Information Science and Technology, Gansu Agricultural University, Lanzhou, Gansu 730070, China | | LI Guang | College of Forestry, Gansu Agricultural University, Lanzhou, Gansu 730070, China | | YUAN Jianyu | Pratacultural College, Gansu Agricultural University, Lanzhou, Gansu 730070, China |
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| Abstract: |
| To estimate the response characteristics of spring wheat yield and soil N2O emissions in the semi\|arid region of Northwest China, and to enhance the accuracy and applicability of the APSIM model in simulating spring wheat yield and soil N2O emissions in this region, firstly, the extended fourier amplitude sensitivity test (EFAST) method was used to conduct sensitivity analysis on the internal parameters of the model, and the key parameters that have the most significant impact on nitrification and denitrification reactions in wheat varieties and soil were selected. Then, the non dominated sorting genetic algorithm II (NSGA-II) was used to perform multi\|objective optimization on the selected parameters. The results showed that the key parameters selected by sensitivity analysis included the key parameters of wheat varieties: potential grain filling rate, number of grains per gram of stem, accumulated temperature from germination to flowering, sensitivity to vernalization, and sensitivity to photoperiod. The key parameters of nitrification and denitrification reactions in soil include the power term of the denitrification soil water factor, the proportion of nitrogen discharged in the form of N2O during nitrification, the denitrification coefficient, the maximum nitrification rate, and the NH4 concentration of half of KMax(KNH4). The accuracy of the optimized APSIM model has significantly improved. The root mean square error of the yield decreased from 121.31 kg·hm-2 to 64.79 kg·hm-2, the normalized root mean square error decreased from 10.05% to 5.37%, and the determination coefficient of the wheat yield model increased from 0.74 to 0.92. The root mean square error of N2O emissions decreased from 32.46 μg·m-2·h-1 to 7.16 μg·m-2·h-1, the normalized root mean square error decreased from 13.92% to 3.07%, and the determination coefficient of the N2O emission model increased from 0.65 to 0.82. The optimized parameters showed good generalization ability at different fertilization levels (0, 55, 110, and 220 kg·hm-1), providing a scientific basis for the local application and parameter calibration of the APSIM model. |
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