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刘文茹,陈国庆,刘恩科,居辉,刘勤.基于DSSAT模型的长江中下游冬小麦潜在产量模拟研究.生态学报,2018,38(9):3219~3229 本文二维码信息
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基于DSSAT模型的长江中下游冬小麦潜在产量模拟研究
The variations in winter wheat potential yields in the middle and lower reaches of the Yangtze River under the RCP scenarios
投稿时间:2017-02-28  修订日期:2017-12-29
DOI: 10.5846/stxb201702280320
关键词冬小麦  潜在产量  DSSAT  典型浓度  长江中下游地区
Key Wordswinter wheat  potential yield  DSSAT  RCP (Representative Concentration Pathway)  the middle and lower reaches of the Yangtze River
基金项目国家自然科学基金项目(41401510);中国农业科学院创新工程(2017-2020)
作者单位E-mail
刘文茹 山东农业大学农学院, 泰安 271018  
陈国庆 山东农业大学农学院, 泰安 271018  
刘恩科 中国农业科学院农业环境与可持续发展研究所, 北京 100081  
居辉 中国农业科学院农业环境与可持续发展研究所, 北京 100081  
刘勤 中国农业科学院农业环境与可持续发展研究所, 北京 100081 liuqin02@caas.cn 
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摘要:
为了探明气候变化对长江中下游地区冬小麦潜在产量的影响,基于政府间气候变化专门委员会(IPCC) AR5提出的BCC-CSM1-1(Beijing Climate Center Climate System Model version1-1)气候系统模式输出的基于典型浓度RCP各情景(基准时段baseline、RCP 2.6、RCP 4.5和RCP 8.5)主要气象要素的逐日模拟数据和历史观测数据。通过DSSAT模型模拟历史时期(2001-2009年)冬小麦的物候期和产量,并计算模拟数据与实测数据二者的均方根误差和一致性指数(开花、成熟期和产量模拟结果的相对均方差根误差分别在0.83%-2.98%之间和7%以下,符合度D均接近于1)明确最优遗传参数,应用最优参数模拟加以验证,完成模型参数区域化。结合历史阶段(1961-1990年)和未来时期(2021-2050年)主要气象要素变化趋势,利用DSSAT模型模拟分析未来30年长江中下游地区气候变化对小麦产量的影响及变化趋势,以期为未来作物生产提供理论依据。结果表明,DSSAT-CERES-Wheat品种遗传参数本地化后能准确模拟冬小麦的生长发育过程及产量潜力。较基准年相比,2021-2050年RCP情景下,冬小麦生育期内≥10℃积温除RCP 2.6情景外呈现逐渐增加趋势,增加幅度为RCP 8.5 > RCP 2.6 > RCP 4.5;降水量年际波动都比较大,区域性差异明显;太阳总辐射量较基准年均有所降低,但降低的幅度随着年份的增加逐渐减小,变化率均呈现显著或极显著的增加趋势。除昆山外冬小麦开花期、成熟期较基准年均有所提前,开花期到成熟期天数则随之缩短。仅考虑气候条件时,长江中下游地区冬小麦产量潜力与基准年减少,昆山、英山下降幅度较滁州、钟祥大(3%-59%),且区域差异明显。分析可得,一定范围内冬小麦产量随积温的增加逐渐增加,超过一定阈值时则逐渐减少,其他气候因子增加或减少并不能弥补积温过低产生的负效应。
Abstract:
The purpose of this study was to evaluate the effects of climate change on the potential yield of winter wheat in the middle-lower Yangtze area. Based on the BCC-CSM1-1 (Beijing Climate Center Climate System Model version1-1) climate system model proposed by the United Nations Intergovernmental Panel on Climate Change (IPCC) AR5, and historical daily meteorological elements were obtained under different RCP scenarios (baseline, RCP2.6, RCP4.5, and RCP8.5). In our study, which used the DSSAT-GLUE module, the phenotype and yield of winter wheat for the historical period (2001-2009) was used to optimize parameters and test the model performance. The performance of the parameters and model was evaluated by the normalized root mean squared error (NRMSE) and the consistency index (D). Then the wheat yield over the next 30 years was predicted by DSSAT, and its change trends were analyzed using meteorological elements recorded between 1961 and 1990 and future predictions (2021-2050). After parameter optimization, the NRMSE for flowering duration and maturity duration ranged from 0.83% to 2.98%, and the NRMSE for yield was below 7%. Climate change will have negative effects on future agricultural production and food security. The results showed that under the RCP2.6 scenario, accumulative temperature (> 10℃) decreased significantly compared to the baseline climatic condition, but increased in the other two scenarios. The precipitation fluctuation was relatively large with obvious regional differences and an insignificant change rate. The total solar radiation in the three RCP scenarios was lower than the baseline, whereas the rate decreased as the number of years increased. Simulated accumulative temperature (> 10℃), precipitation, and solar total radiation during the growing period 2021-2050 compared to the baseline climatic condition had different change tendencies. When only the climate factors were taken into account (without considering CO2 concentration effect, variety substitution, soil change, and management optimization), the growth period and yield of winter wheat had different change tendencies. In the RCP2.6 scenario, except for Kunshan, the flowering and maturing stages for winter wheat were delayed (RCP8.5 > RCP4.5), and the days from flowering to maturity decreased. In general, there was a significant difference in regional trends for potential yield:Kunshan and Yingshan declined more than Chuzhou and Zhongxiang (3%-59%); yield reduction in Kunshan was lowest under the RCP2.6 scenario; but Chuzhou, Yingshan, and Zhongxiang were the opposite. These results indicated that winter wheat yield increased gradually with the increase in accumulated temperature, which in turn decreased as a certain threshold was exceeded. Furthermore, the increase or decrease in other climatic factors could not compensate for the negative effects of low accumulated temperatures. When the temperature was too high, flowering and maturity were delayed, which subsequently prolonged vegetative growth and blocked reproductive growth, which resulted in too many tillers and reduced the spike rates, thereby causing lower yields.
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