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气候变化研究进展  2018, Vol. 14 Issue (6): 573-582    DOI: 10.12006/j.issn.1673-1719.2018.090
  气候变化影响 本期目录 | 过刊浏览 | 高级检索 |
全球1.5℃和2.0℃升温对中国小麦产量的影响研究
孙茹1,韩雪1,潘婕1,熊伟1,2,居辉1
1 中国农业科学院农业环境与可持续发展研究所,北京 100081
The impact of 1.5℃and 2.0℃global warming on wheat production in China
Ru SUN1,Xue HAN1,Jie PAN1,Wei XIONG1,2,Hui JU1
1 Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
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摘要 

采用部门间影响模式比较计划(ISI-MIP)的气候模式,确定全球升温1.5℃和2.0℃出现的时间,并结合农业技术转移决策支持系统(DSSAT)模型模拟小麦的产量,最终选取4套数据对比研究中国小麦区温度和降水变化特征以及各区域小麦产量变化趋势,综合评价了不同升温情景对中国小麦产量的影响。结果表明:(1)在全球升温1.5℃和2.0℃背景下,我国小麦生育期内温度相对于工业革命前分别升高1.17℃和1.81℃。两种升温情景下我国春麦区升温幅度大于冬麦区升温幅度。春麦区中新疆春麦区升温幅度最大,西北春麦区升温幅度最小;冬麦区中温度变化最大和最小的麦区分别为西南冬麦区和黄淮冬麦区。(2)在全球升温1.5℃和2.0℃情景下,我国小麦生育期内降水相对于历史时段(1986—2005年)分别增加9.1%和11.3%。从各麦区来看,两种升温情景下春麦区降水增加幅度略大于冬麦区的增加幅度。所有麦区中只有新疆春麦区降水低于历史时段降水。春麦区降水增加幅度最大的麦区为北部春麦区。冬麦区中降水增加较大的麦区为北部冬麦区和黄淮冬麦区,降水增加较小的麦区为华南冬麦区和西南冬麦区。(3)两种升温情景下,我国小麦单产相对于历史时段(1986—2005年)平均减产分别为5.2%和4.6%,两种升温情景对中国小麦产量并没有显著的差异。在全球升温大背景下我国春小麦主要呈现增产趋势,冬小麦主要呈现减产趋势。减产幅度较大的麦区为华南冬麦区和青藏春麦区,增产幅度最大的麦区为西北春麦区。从各麦区产量减产面积比例上看,我国各麦区减产面积所占比例趋势为从北向南由多变少再变多,其中华南冬麦区减产面积所占比例最大,北部冬麦区最小。

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孙茹
韩雪
潘婕
熊伟
居辉
关键词:  全球1.5℃和2.0℃升温  中国小麦  产量  温度  降水    
Abstract: 

In this study, 1.5℃ warming and 2.0℃ warming scenarios were determined by four sets of data from CMIP5 models including IPSL-CM5A-LR (RCP2.6), GFDL-ESM2M (RCP4.5 and RCP6.0), NorESM1-M (RCP4.5). Simulations of wheat grain yield were performed using the DSSAT v4.5 crop model. Results show that: (1) The air temperature within the wheat growing season would increase 1.17℃ and 1.81℃ above the pre-industrial levels, respectively, at the global warming of 1.5℃and 2.0℃. The warming degree of spring wheat areas in China is higher than that of winter wheat areas. Among the spring wheat areas, the Xinjiang Spring Wheat Area has the largest temperature rise, and the Northwest Spring Wheat Area the smallest. Regarding of winter wheat areas, the maximum and the minimum temperature variation are Southwest Winter Wheat Area and Huang-Huai Winter Wheat Area, respectively. (2) Precipitation in China’s wheat growing season increases by 9.1% and 11.3%, respectively, at the global warming of 1.5℃and 2.0℃, relative to the historical period (1986-2005). The increase of precipitation in spring wheat areas is slightly larger than that of the winter wheat areas. The precipitation in the Xinjiang Spring Wheat Area is lower than that in the historical period. The largest increase of precipitation in spring wheat areas is the Northern Spring Wheat Area. In the winter wheat areas, the Northern and the Huang-Huai Winter Wheat Area shows a larger increase of rainfall, while the precipitation of South China Winter Wheat Area and the Southwest Winter Wheat Area increases slightly. (3) With 1.5℃and 2.0℃warming scenarios, wheat production in China is estimated to reduce by 5.2% and 4.6%, respectively, relative to the historical period (1986-2005). The difference between the two warming scenarios is not significant. With global warming, China’s spring wheat yield mainly shows an increase trend, and the winter wheat yield mainly shows a decrease trend. The largest yield decrease occur’s in the South China Winter Wheat Area and Qinghai-Tibet Spring Wheat Area. The largest yield increase occur’s in the Northwest Spring Wheat Area. The ratio of yield reduction area shows a trend of decreasing first and then increasing from north to south. The South China Winter Wheat Area has the maximum ratio, while the Northern Winter Wheat Area the minimum ratio.

Key words:  1.5℃and 2.0℃global warming    Wheat in China    Yield    Temperature    Precipitation
收稿日期:  2018-06-14      修回日期:  2018-07-24           出版日期:  2018-11-30      发布日期:  2018-11-30      期的出版日期:  2018-11-30
基金资助: 国家自然科学基金“冬小麦品种对高浓度CO2差异响应的机理研究”(41505100);国家重点研发计划“北部冬麦区丰产节水型优质强筋小麦品种筛选及其配套栽培技术”(2016YFD0300401)
通讯作者:  韩雪   
作者简介:  孙茹,女,硕士研究生;
引用本文:    
孙茹,韩雪,潘婕,熊伟,居辉. 全球1.5℃和2.0℃升温对中国小麦产量的影响研究[J]. 气候变化研究进展, 2018, 14(6): 573-582.
Ru SUN,Xue HAN,Jie PAN,Wei XIONG,Hui JU. The impact of 1.5℃and 2.0℃global warming on wheat production in China. Climate Change Research, 2018, 14(6): 573-582.
链接本文:  
http://www.climatechange.cn/CN/10.12006/j.issn.1673-1719.2018.090  或          http://www.climatechange.cn/CN/Y2018/V14/I6/573
图1  中国小麦种植区划
Table 1  Genetic coefficients in China region
Table 2  The characteristics of 4 CMIP5 model outputs
Table 3  Wheat growing seasons by wheat region in China
图2  全球升温1.5℃ (a)和2.0℃ (b)情景下小麦生育期平均气温(20年平均值)相对于1850—1900年的变化
图3  全球升温1.5℃ (a)和2.0℃ (b)情景下各麦区温度相对于1850—1900年的变化
图4  全球升温1.5℃ (a)和2.0℃ (b)情景下我国小麦生育期内降水相对历史时段(1986—2005年)的变化
图5  全球升温1.5℃ (a)和2.0℃ (b)情景下各麦区降水相对历史时段(1986—2005 年)变化
图6  全球升温1.5℃ (a)和2.0℃ (b)情景下全国小麦单产相对历史时段(1986—2005 年)的变化
图7  全球升温1.5℃ (a)和2.0℃ (b)情景下我国小麦产量相对历史时段(1986—2005年)的变化
图8  全球升温1.5℃和2.0℃ 我国各麦区产量变化
[1] IPCC. Climate change 2013: the physical science basis [M]. Cambridge: Cambridge University Press, 2013: 1535
[2] Hirabayashi Y, Mahendran R, Koirala S , et al. Global flood risk under climate change[J]. Nature Climate Change, 2013,3(9):816-821
doi: 10.1038/NCLIMATE1911
[3] Rogelj J, Elzen M D, H?hne N , et al. Paris Agreement climate proposals need a boost to keep warming well below 2.0℃[J]. Nature, 2016,534(7609):631
doi: 10.1038/nature18307
[4] Tao F L, Yokozawa M, Xu Y , et al. Climate changes and trends in phenology and yields of field crops in China 1981-2000[J]. Agricultural & Forest Meteorology, 2006,138(1):82-92
doi: 10.1016/j.agrformet.2006.03.014
[5] Tao F L, Yokozawa M, Liu J , et al. Climate-cropyield relationships at province scale in China and the impacts of recent climate trends[J]. Climate Research, 2008,38(1):83-94
doi: 10.3354/cr00771
[6] Tao F L, Yokozawa M, Zhang Z . Modelling the impacts of weather and climate variability on crop productivity over a large area: a new process-based model development, optimization, and uncertainties analysis[J]. Agricultural & Forest Meteorology, 2009,149(8):1266-1278
[7] Chen C, Pang Y M, Pan X B , et al. Impacts of climate change on cotton yield in China from 1961 to 2010 based on provincial data[J]. Journal of Integrative Agriculture, 2014,29(7):515-524
doi: 10.1007/s13351-014-4082-7
[8] Nicholls N . Increased Australian wheat yield due torecent climate trends[J]. Nature, 1997,387:484-485
doi: 10.1038/387484a0
[9] Lobell D B, Schlenker W, Costaroberts J . Climate trends and global crop production since 1980[J]. Science, 2011,333(6042):616
doi: 10.1126/science.1204531
[10] Peng S B, Huang J L, Sheehy J E , et al. Rice yields decline with higher night temperature from global warming[J]. Proceedings of the National Academy of Sciences of the United States of America, 2004,101:9971-9975
doi: 10.1073/pnas.0403720101 pmid: 15226500
[11] You L Z, Rosegrant M W, Wood S , et al. Impact of growing season temperature on wheat productivity in China[J]. Agricultural and Forest Meteorology, 2009,149:1009-1014
doi: 10.1016/j.agrformet.2008.12.004
[12] Oijen M V, Ewert F . The effects of climatic variation in Europe on the yield response of spring wheat cv. Minaret to elevated CO2, and O3: an analysis of open-top chamber experiments by means of two crop growth simulation models[J]. European Journal of Agronomy, 1999,10(3-4):249-264
doi: 10.1016/S1161-0301(99)00014-3
[13] Ludwig F, Asseng S . Climate change impacts on wheat production in a Mediterranean environment in Western Australia[J]. Agricultural Systems, 2006,90(1-3):159-179
doi: 10.1016/j.agsy.2005.12.002
[14] Lobell D B, Field C B . Global scale climate: crop yield relationships and the impacts of recent warming[J]. Environmental Research Letters, 2007,2(1):014002
doi: 10.1088/1748-9326/2/1/014002
[15] Lobell D B, Burke M B, Tebaldi C , et al. Prioritizing climate change adaptation needs for food security in 2030[J]. Science, 2008,319(5863):607
doi: 10.1126/science.1152339
[16] 赵广才 . 中国小麦种植区划研究(一)[J]. 麦类作物学报, 2010,30(5):886-895
doi: 10.7606/j.issn.1009-1041.2010.05.019
[17] Gbegbelegbe S, Cammarano D, Asseng S , et al. Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars[J]. Field Crops Research, 2016,202(15):122-135
doi: 10.1016/j.fcr.2016.06.010
[18] 赵广才 . 中国小麦种植区划研究(二)[J]. 麦类作物学报, 2010,30(6):1140-1147
doi: 10.7606/j.issn.1009-1041.2010.05.019
[19] Moore F C, Baldos U L C, Hertel T . Economic impacts of climate change on agriculture: a comparison of process-based and statistical yield models[J]. Environmental Research Letters, 2017,12(6):1-9
doi: 10.1088/1748-9326/aa6eb2
[20] 张勇 . 中国区域未来极端气候事件情景分析及其对华北主要农作物生产的影响评估[D]. 北京: 中国科学院大气物理研究所, 2007
[21] 杨绚, 汤绪, 陈葆德 , 等. 气候变暖背景下高温胁迫对中国小麦产量的影响[J]. 地理科学进展, 2013,32(12):1771-1779
doi: 10.11820/dlkxjz.2013.12.006
[22] Chen Y, Zhang Z, Tao F L . Impacts of climate change and climate extremes on major crops productivity in China at a global warming of 1.5℃ & 2.0℃[J]. Earth System Dynamics Discussions, 2018: 1-27
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[2] . Analysis of Factors Impacting China's CO2 Emissions During 1971-2005[J]. Climate Change Research, 2008, 04(001): 42 -47 .
[3] Cao Guoliang;Zhang Xiaoye; Wang Yaqiang;et al.. Inventory of Black Carbon Emission from China[J]. Climate Change Research, 2007, 03(00): 75 -81 .
[4] . Dryness/Wetness Changes in Qinghai Province During 1959-2003[J]. Climate Change Research, 2007, 03(06): 356 -361 .
[5] Xu Xiaobin;Lin Weili; Wang Tao;et al.. Long-term Trend of Tropospheric Ozone over the Yangtze Delta Region of China[J]. Climate Change Research, 2007, 03(00): 60 -65 .
[6] Gao Qingxian; Du Wupeng; Lu Shiqing;et al.. Methane Emission from Municipal Solid Waste Treatments in China[J]. Climate Change Research, 2007, 03(00): 70 -74 .
[7] . Guide to Authors[J]. Climate Change Research, 2006, 02(00): 84 .
[8] . Granger Causality Test for Detection and Attribution of Climate Change[J]. Climate Change Research, 2008, 04(001): 37 -41 .
[9] . AIntra-annual Inhomogeneity Characteristics of Precipitation over Northwest China[J]. Climate Change Research, 2007, 03(05): 276 -281 .
[10] . Projection of Future Precipitation Extremes in the Yangtze River Basin for 2001-2050[J]. Climate Change Research, 2007, 03(06): 340 -344 .
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