基于DNDC模型的农田管理措施-气候变化作用下粮食产量与N2O排放模拟研究:以四川省丘陵地区为例

Simulation Study of Grain Yield and N2O Emissions under Farmland Management Measures and Climate Change Based on DNDC Model: Case Study of Hilly Regions in Sichuan Province

  • 摘要: 当前农田管理措施成为应对气候变化导致的粮食安全与生态环境问题的主要手段之一。以四川省丘陵地区江油市某典型农田为研究对象,通过实地调研与样本分析,采用DNDC模型模拟氮肥施用量、施肥深度、耕作深度、无机有机肥配施4类农田管理措施下的小麦-玉米产量及N2O排放量,并在此基础上将厘定的最佳农田管理措施应用于未来气候变化情景(RCP4.5和RCP8.5情景),揭示未来气候变化下农田管理措施对粮食产量及N2O排放量的影响机制。结果表明:(1)DNDC模型对粮食产量的模拟效果较好,在基准情景(BS)验证期间,玉米和小麦产量观测值与模拟值的R2分别为0.59、0.62,平均相对误差(MRE)分别为-1.63%和-3.19%,标准化均方根误差(NRMSE)分别为7.32%、3.60%;(2)70%惯用施肥量(F3)、施肥深度12 cm(D3)、耕作深度20 cm(T3)、无机有机肥配施25%(M1)分别为各类农田管理措施中最佳情景。其中,M1为最佳单一措施情景,最佳组合情景为D3M1,其产量分别为9 802.63和9 804.83 kg·hm-2·a-1;(3)在未来气候变化情景下,D3M1情景的N2O排放量分别较M1、BS情景下降4.87%~17.51%和33.62%~36.76%,而各情景产量无明显差异,因此D3M1情景为最佳农田管理措施。在D3M1-RCP4.5和D3M1-RCP8.5情景下,未来长期玉米产量较历史时期分别下降0.03%和0.07%,其主要与生长季温度升高和产籽前期降雨增加有关,小麦生长季降雨量增加则导致产量分别下降1.31%和2.72%,且温度升高可能会使其成熟期提前。同时,未来降雨量增加使N2O排放量呈逐渐上升趋势。研究表明,在未来可采取氮肥深施12 cm与无机有机肥配施25%的组合措施(D3M1),以及适量降低惯用施肥量、合理调整播种施肥日期等农田管理措施,以保障粮食安全及应对气候变化带来的不利影响。

     

    Abstract: It is crucial to propose suitable farmland management measures for addressing food security and ecological challenges caused by climate change. In this study, a typical farmland located in Jiangyou City of Sichuan Province was selected as the study site, which is characterized by hilly geographical feature. Based on field investigation and sample analysis, the DNDC model was firstly used to simulate the grain yield and N2O emissions of the Wheat-Maize planting system under four different farmland management measures related to nitrogen fertilizer application rate, fertilization depth, tillage depth, and application of inorganic-organic fertilizers. Subsequently, the optimal farmland management measure was determined, and then integrated to future climate change scenarios (RCP4.5 and RCP8.5) to reveal their impacts on grain yield and N2O emission. The detailed results show that: (1) During the baseline scenario, the R2 values between the simulated and observed yields of maize and wheat were 0.59 and 0.62, respectively With the MRE to be -1.63% and -3.19%, and NRMSE to be 7.32% and 3.60%, respectively. These indexes indicate that the simulated results of DNDC model were credible and can be applied to next scenario simulation. (2) The optimal scenarios for various farmland management measures include: the conventional fertilizer application rate of 70% (F3), a fertilization depth of 12cm (D3), a tillage depth of 20cm (T3), and the application of inorganic-organic fertilizers of 25% (M1). The M1 is the best single farmland management measure scenario, while the best combined farmland management measure scenario is D3M1, with yields of 9 802.63 kg·hm-2·a-1 and 9 804.83 kg·hm-2·a-1, respectively. (3) Under future climate change scenarios, N2O emissions in the D3M1 combined farmland management measure scenario decreased by 4.87% to 17.51% and 33.62% to 36.76% compared with the M1 and BS single farmland management measure scenario, respectively, while the yield did not show significant differences. Therefore, the D3M1 is determined as the optimal farmland management measure. In the long-term of D3M1-RCP4.5 and D3M1-RCP8.5 climate change scenarios, the maize yields respectively decreased by 0.03% and 0.07% compared with historical climate period, this is primarily attributed to increasing temperatures during the growing season and higher precipitation before seed production. The increased precipitation during the wheat growing season resulted in yield reductions of 1.31% and 2.72%, with rising temperature potentially accelerated maturity. Meanwhile, the increased precipitation under future climate change scenario led to a consistent rise in N2O emissions. This research indicates that farmland management measures can be adopted to guarantee food security and mitigate the effects of climate change in the future, for example, using the combined farmland management measures (a fertilization depth of 12cm and the application of inorganic-organic fertilizers of 25%, D3M1), reducing the fertilizer application rate, adjusting crop seeding and fertilization timing appropriately, and so on.

     

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