戴彤, 王靖, 赫迪, 王娜. 1961—2010年气候变化对西南冬小麦潜在和雨养产量影响的模拟分析[J]. 中国生态农业学报(中英文), 2016, 24(3): 293-305.
引用本文: 戴彤, 王靖, 赫迪, 王娜. 1961—2010年气候变化对西南冬小麦潜在和雨养产量影响的模拟分析[J]. 中国生态农业学报(中英文), 2016, 24(3): 293-305.
DAI Tong, WANG Jing, HE Di, WANG Na. Impact simulation of climate change on potential and rainfed yields of winter wheat in Southwest China from 1961 to 2010[J]. Chinese Journal of Eco-Agriculture, 2016, 24(3): 293-305.
Citation: DAI Tong, WANG Jing, HE Di, WANG Na. Impact simulation of climate change on potential and rainfed yields of winter wheat in Southwest China from 1961 to 2010[J]. Chinese Journal of Eco-Agriculture, 2016, 24(3): 293-305.

1961—2010年气候变化对西南冬小麦潜在和雨养产量影响的模拟分析

Impact simulation of climate change on potential and rainfed yields of winter wheat in Southwest China from 1961 to 2010

  • 摘要: 利用农业气象试验站作物资料及土壤资料, 评价APSIM-Wheat模型在西南地区的适应性, 应用该模型分析该地区1961—2010年冬小麦潜在和雨养产量的时空变化特征, 通过逐步回归分析揭示小麦生长季主要气象因子对潜在产量和雨养产量的影响及相对贡献率。研究结果表明: APSIM模型对该区5个常用小麦品种的模拟效果较好, 模拟与实测生育期的均方根误差(RMSE)在7.0 d以内, 地上部分生物量和产量模拟值与实测值的归一化均方根误差(NRMSE)均低于25%, 模型在西南地区具有较好的适应性。1961—2010年研究区域36%的站点冬小麦生长季总辐射显著降低, 其中北部、东南部和南部中区最显著; 68%的站点生长季≥0 ℃有效积温显著增加, 西部增温显著; 30%的站点生长季平均气温日较差显著减小, 南部中区最显著; 全区生长季总降水大面积减少但不显著, 减少区主要位于最南端和东南部。模拟的冬小麦潜在产量在65%的站点呈显著减产趋势, 南部中区和北部变化最明显; 雨养产量在25%的站点显著降低, 北部地区较明显, 全区减产趋势较弱。减产显著的站点中, 生长季辐射降低、温度升高、气温日较差减小对潜在产量降低的贡献率分别为45%、36%和2%, 对雨养产量降低的贡献率分别为36%、39%和8%, 而降水减少对雨养产量降低的贡献率为7%。西南冬小麦生长季辐射降低、温度升高及降水减少共同导致了冬小麦潜在和雨养产量的显著下降, 而气温日较差的降低对冬小麦潜在和雨养产量的影响分别表现为负作用和正作用, 整体上辐射和温度的影响程度最大。

     

    Abstract: Using crop and soil data from agro-meteorological observational stations together with meteorological data from meteorological stations, the study evaluated the adaptability of APSIM-Wheat (Agricultural Production Systems sIMulator- Wheat) model in winter wheat planting zones in Southwest China (SWC). Then, the model was used to calculate the potential and rainfed yields of winter wheat from 1961 to 2010 in SWC. The relative contribution rates of the changes in main climatic factors during crop growing season to the changes in simulated potential and rainfed yields of winter wheat were determined with the stepwise regression method. The study results showed that APSIM-Wheat model performed well in simulating phenology, above-ground biomass and yield of five representative winter wheat varieties in SWC. Root Mean Square Error (RMSE) between simulated and observed wheat phenology were less than 7.0 d for all the varieties. Normalized Root Mean Square Error (NRMSE) between simulated and observed above-ground biomass and yield were lower than 25% and 21%, respectively, for all the varieties. Total solar radiation during wheat growing season decreased significantly at 36% of the study stations centered in the northern, southeastern and mid-southern SWC. The effective accumulative temperature of not less than 0 ℃ during wheat growing season increased significantly at 68% of the study stations centered in the western SWC, while average diurnal temperature range during wheat growing season decreased significantly at 30% of study stations centered in the mid-southern SWC (P < 0.05). Total precipitation during wheat growing season decreased at most of study stations centered in the southern and southeastern SWC from 1961 to 2010. As a result, simulated potential yield of winter wheat also showed a significant decline at 65% of study stations, especially in the mid-southern and northern SWC. Simulated yield of rainfed wheat showed a significant decline at 25% of study stations, especially in the northern SWC. The contribution rates of the decrease of solar radiation and diurnal temperature range, the increase of temperature during wheat growing season were 45%, 2% and 36%, respectively, to the reduction in simulated potential yield, and 36%, 39% and 8%, respectively, to the reduction in simulated yield of rainfed wheat. The contribution rate of decreasing precipitation during wheat growing season was 7% to the reduction in simulated yield of rainfed wheat. In general, solar radiation and temperature had the most obvious effects on simulated yield variations of winter wheat in SWC from 1961 to 2010. The decrease in solar radiation and precipitation, and the increase in temperature during winter wheat growing season led to a decline in both simulated potential and rainfed yields at most of study stations in SWC, while the decreased diurnal temperature range had both negative and positive effects on potential and rainfed yields, respectively. Quantifying the impacts of light, temperature and precipitation on wheat production using APSIM model provided a sound foundation for taking countermeasures for adapting to climate change and improving wheat yield in Southwest China.

     

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