Wang Peijuan, Zhang Jiahua, Xie Donghui, et al. Estimation for weather yield of winter wheat under A2 and B2 scenarios in Hebei, Shandong and Henan provinces. J Appl Meteor Sci, 2011, 22(5): 549-557.
Citation: Wang Peijuan, Zhang Jiahua, Xie Donghui, et al. Estimation for weather yield of winter wheat under A2 and B2 scenarios in Hebei, Shandong and Henan provinces. J Appl Meteor Sci, 2011, 22(5): 549-557.

Estimation for Weather Yield of Winter Wheat Under A2 and B2 Scenarios in Hebei, Shandong and Henan Provinces

  • Received Date: 2010-08-24
  • Rev Recd Date: 2011-06-13
  • Publish Date: 2011-10-31
  • Winter wheat is one of the main crops in China. Hebei, Shandong and Henan provinces are the main planting areas for winter wheat in China. It is important for China to recognize the change of weather yield for winter wheat in the next several decades.Trend yield models of winter wheat are built based on statistical yield from 1978 to 2008 using nonlinear simulation method for Hebei, Shandong and Henan provinces. Multiple correlation coefficients of trend yield models are greater than 0.90 for each province. Then, weather yields of winter wheat are got by subtracting the trend yield from statistical yields for each province. Historical meteorological data from 1978 to 2008 are disposed to get the average data (or maximum or minimum or sum) of every ten days for three provinces. Disposed meteorological data and weather yields of winter wheat are used to establish the models, whose significance reaches 0.05 level.In order to predict the weather yields of winter wheat, meteorological data coming from regional climate model (PRECIS) are used. The average data (or maximum or minimum or sum) of every ten days for each province for the reference period of 1978—1990 are achieved, as well as the data for future climate change under A2 and B2 scenarios of 2011—2050. Weather yields of winter wheat for the reference period are computed by using disposed meteorological data with weather yield models for Hebei, Shandong and Henan provinces. Meanwhile, trend yields of winter wheat are calculated using trend yield models by province. The total yields of each province from 1979 to 1990 are summed by weather yields and trend yields, which are compared with statistical yields. The results show that the correlation coefficients are 0.928, 0.792 and 0.837 for Hebei, Shandong and Henan. The significance reaches 0.001 level for Hebei and Henan, 0.002 level for Shandong.Weather yields of winter wheat are simulated based on weather yield models under A2 and B2 scenarios from 2012 to 2050 with disposed regional climate model (PRECIS) data for Hebei, Shandong and Henan provinces. The results show that in both A2 and B2 scenarios, the weather yields of winter wheat deduce for Hebei and Henan, with increase for Shandong for most years of 2012—2050.
  • Fig. 1  Flowchart of the research

    Fig. 2  True yield of winter wheat for Hebei, Shandong and Henan provinces

    Fig. 3  Comparison between true yield and simulated yield based on basically climate data for Hebei, Shandong and Henan provinces

    Fig. 4  Weather yield of winter wheat in A2 and B2 scenarios for Hebei, Shandong and Henan provinces

    Table  1  Parameters of meteorological yield models for Hebei, Shandong and Henan provinces

    省份 判定项 常数项 正相关 负相关
    因子 线性回归系数 因子 线性回归系数
    河北* R=0.527
    F=3.341
    -1072.253 第14旬最低温度
    4月降水量
    65.947
    4.476
    第1旬最低温度 -27.474
    山东* R=0.647
    F=2.745
    -710.405 第12旬最低温度
    第3旬最高温度
    第3旬最低温度
    前一年10月至当年5月降水量
    76.373
    50.648
    32.859
    2.312
    第1旬平均温度
    第2旬最高温度
    -63.371
    -49.750
    河南** R=0.703
    F=3.078
    -2109.941 第15旬最低温度
    第10旬最低温度
    第7旬最高温度
    前一年10月至当年5月降水量
    57.454
    56.937
    17.581
    1.809
    第2旬最低温度
    第1旬平均温度
    第35旬最低温度
    -32.879
    -27.332
    -21.410
    注:*回归模型通过0.05的显著性检验,**回归模型通过0.025的显著性检验;R为相关系数,F为检验值。
    DownLoad: Download CSV

    Table  2  Positive and negative mean and years of winter wheat whether yield in A2 and B2 scenarios for Hebei, Shandong and Henan provinces

    省份 A2情景 B2情景
    正效应 负效应 正效应 负效应
    产量平均值
    /(kg·hm-2)
    频数 产量平均值
    /(kg·hm-2)
    频数 产量平均值
    /(kg·hm-2)
    频数 产量平均值
    /(kg·hm-2)
    频数
    河北 122.43 15 -145.06 24 103.75 17 -125.11 22
    山东 237.15 21 -249.30 18 247.18 24 -219.80 15
    河南 133.67 16 -156.74 23 161.63 13 -208.56 26
    DownLoad: Download CSV
  • [1]
    程延年, 周兆德.用分阶段回归模式进行作物产量气候分析——以北京地区冬小麦为例.应用概率统计, 1994, 10(2): 218-220. http://www.cnki.com.cn/Article/CJFDTOTAL-YYGN199402012.htm
    [2]
    张金艳, 李小泉, 张镡.全球粮食气象产量及其与降水量变化的关系.应用气象学报, 1999, 10(3): 327-332. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19990377&flag=1
    [3]
    秦剑.气候因子与云南粮食生产的关系.应用气象学报, 2000, 11(2): 213-220. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20000231&flag=1
    [4]
    詹志明, 刘军臣, 巍东岚.旱涝对豫东地区冬小麦产量的影响评估.中国农业气象, 1999, 20(4): 10-15. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGNY199904002.htm
    [5]
    张力, 张保华.冬小麦气象产量分析.中国农业气象, 2004, 25(1): 22-24. http://www.cnki.com.cn/Article/CJFDTOTAL-HBSL201504006.htm
    [6]
    魏瑞江, 张文宗, 李二杰.河北省冬小麦生育期气象条件定量评价模型.中国农业气象, 2007, 28(4):367-370. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGNY200704005.htm
    [7]
    郭海英, 万信, 杨兴国.利用气象与生态要素预测冬小麦产量.气象科技, 2008, 36(4): 440-443. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200804013.htm
    [8]
    李月英, 刘全喜, 张文英, 等.黑龙港流域冬小麦产量与气象因子相关与通径分析.华北农学报, 2008, 23(增刊): 329-333. http://www.cnki.com.cn/Article/CJFDTOTAL-HBNB2008S2077.htm
    [9]
    李月英, 柳斌辉, 刘全喜, 等.河北低平原气候条件对冬小麦产量的影响.麦类作物学报, 2009, 29(2): 330-334. http://www.cnki.com.cn/Article/CJFDTOTAL-MLZW200902031.htm
    [10]
    罗蒋梅, 王建林, 申双和, 等.影响冬小麦产量的气象要素定量评价模型.南京气象学院学报, 2009, 32(1): 94-99. http://www.cnki.com.cn/Article/CJFDTOTAL-NJQX200901012.htm
    [11]
    马鹏里, 蒲金涌, 赵春雨, 等.光温因子对大田冬小麦累积生物量的影响.应用生态学报, 2010, 21(5): 1270-1276. http://www.cnki.com.cn/Article/CJFDTOTAL-YYSB201005029.htm
    [12]
    高素华, 郭建平, 王春乙.气候变化对旱地作物生产的影响.应用气象学报, 1995, 6(增刊): 83-88. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=yyqx5s1.011&dbname=CJFD&dbcode=CJFQ
    [13]
    张建平, 赵艳霞, 王春乙, 等.气候变化对我国华北地区冬小麦发育和产量的影响.应用生态学报, 2006, 17(7): 1179-1184. http://www.cnki.com.cn/Article/CJFDTOTAL-YYSB200607005.htm
    [14]
    Guo Ruiping, Lin Zhonghui, Mo Xingguo, et al.Responses of crop yield and water use efficiency to climate change in the North China Plain.Agricultural Water Management, 2010, 97: 1185-1194. doi:  10.1016/j.agwat.2009.07.006
    [15]
    王馥棠.近十年来我国气候变暖影响研究的若干进展.应用气象学报, 2002, 13(6): 755-766. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20020699&flag=1
    [16]
    张宇, 王石立, 王馥棠.气候变化对我国小麦发育及产量可能影响的模拟研究.应用气象学报, 2000, 11(3): 264-270. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20000341&flag=1
    [17]
    许吟隆, Richard Jones.利用ECMWF再分析数据验证PRECIS对中国区域气候的模拟能力.中国农业气象, 2004, 25(1): 5-9. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGNY200401001.htm
    [18]
    赵俊芳, 郭建平, 徐精文, 等.基于湿润指数的中国干湿状况变化趋势.农业工程学报, 2010, 26(8): 18-24. http://www.cnki.com.cn/Article/CJFDTOTAL-NYGU201008005.htm
    [19]
    邱新法, 曾燕.影响我国冬小麦产量的气象因子研究.南京气象学院学报, 2000, 23(4): 575-578. http://www.cnki.com.cn/Article/CJFDTOTAL-NJQX200004016.htm
    [20]
    王荣堂, 刘章勇.江陵小麦生长的气象条件及小麦产量预测.湖北农学院学报, 1996, 16(3): 175-180. http://www.cnki.com.cn/Article/CJFDTOTAL-HBNX603.002.htm
  • 加载中
  • -->

Catalog

    Figures(4)  / Tables(2)

    Article views (5504) PDF downloads(1484) Cited by()
    • Received : 2010-08-24
    • Accepted : 2011-06-13
    • Published : 2011-10-31

    /

    DownLoad:  Full-Size Img  PowerPoint