农业气象产量预报方法中权重系数的确定

doi:10.11927/j.issn.1673-503X.2016.02.015

Journal of Meteorology and Environment ›› 2016, Vol. 32 ›› Issue (2): 106-111.doi: 10.11927/j.issn.1673-503X.2016.02.015

Determination of weight coefficient in agro-meteorological yield prediction

QIU Mei-juan^1,2, SONG Ying-bo³, WANG Jian-lin³, WANG Dong-ni¹, QU Si-miao¹, REN Jing-quan¹, WU Ding-rong², LIU Jian-dong²

1. Institute of Meteorological Sciences in Jilin Province, Changchun 130062, China;
2. Chinese Academy of Meteorological Sciences, Beijing 100081, China;
3. National Meteorological Center, Beijing 100081, China

Received:2015-04-21 Revised:2015-07-08 Online:2016-04-30 Published:2016-04-30

Abstract

Abstract: In the crop yield prediction based on climate suitability index, the determination of weight coefficient was of vital importance to the results.Using winter wheat in Shandong province as a case study, weight coefficient of each ten-day was determined by methods of an absolute value, normalization and a correlation coefficient.Correlations among climate suitability indexes calculated by the above methods and with meteorological yield were analyzed, and the optimal one was used to dynamically predict wheat yield.The results indicate that the correlation between meteorological yield and climate suitability index obtained by the correlation coefficient method almost all passes a significant test of the 0.01 level compared with the other two methods, which can reflect the relationship between the development of winter wheat with change of climatic conditions.The accuracy rate of the historical fitting for the established model is above 94.5%, and the standardized root mean square error (n-RMSE) is less than 7.0%, showing the excellent performance of the model.The results of yield dynamic prediction during 2010 to 2011 suggest that the mean accuracy rate is above 93.0% and most are above 96.0%, which can meet the service needs.

Key words: Yield prediction, Climate suitability index, Weight coefficient, Absolute value method, Normalization method, Correlation coefficient method

CLC Number:

S165⁺.27

QIU Mei-juan, SONG Ying-bo, WANG Jian-lin, WANG Dong-ni, QU Si-miao, REN Jing-quan, WU Ding-rong, LIU Jian-dong. Determination of weight coefficient in agro-meteorological yield prediction[J]. Journal of Meteorology and Environment, 2016, 32(2): 106-111.

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References

[1] 王书裕.作物产量的预报方法[J].气象学报,1984,42(3):349-355.
[2] 杨霏云,王建林.晚稻单产动态预测方法研究[J].气象科技,2005,33(5):433-436.
[3] 宋迎波,王建林,陈晖,等.中国油菜产量动态预报方法研究[J].气象,2008,34(3):93-99.
[4] 刘景利,杨扬,梁涛,等.气象要素对大豆产量的影响分析[J].气象与环境学报,2013,29(5):136-139.
[5] 邱美娟,宋迎波,王建林,等.耦合土壤墒情的气候适宜度指数在山东省冬小麦产量动态预报中的应用[J].中国农业气象,2015,36(2):187-194.
[6] 李钰春,袁淑杰,郭晓梅,等.土壤水分条件对冬小麦生长发育及产量构成的影响[J].气象与环境学报,2014,30(5):90-97.
[7] 高永刚,王育光,殷世平,等.世界粮食研究模型在黑龙江省作物产量预报中的应用[J].中国农业气象,2006,27(1):27-30.
[8] 杜春英,李帅,王晾晾,等.基于历史产量丰歉影响指数的黑龙江省水稻产量动态预报[J].中国农业气象,2010,31(3):427-430.
[9] 李军玲,郭其乐,彭记永.基于MODIS数据的河南省冬小麦产量遥感估算模型[J].生态环境学报,2012,21(10):1665-1669.
[10] 刘伟昌,陈怀亮,余卫东,等.基于气候适宜度指数的冬小麦动态产量预报技术研究[J].气象与环境科学,2008,31(2):21-24.
[11] 易雪,王建林,宋迎波.气候适宜指数在早稻产量动态预报上的应用[J].气象,2010,36(6):85-89.
[12] 代立芹,李春强,康西言,等.基于气候和土壤水分综合适宜度指数的冬小麦产量动态预报模型[J].中国农业气象,2012,33(4):519-526.
[13] 游超,蔡元刚,张玉芳.基于气象适宜指数的四川盆地水稻气象产量动态预报技术研究[J].高原山地气象研究,2011,31(1):51-55.
[14] 魏瑞江,张文宗,康西言,等.河北省冬小麦气候适宜度动态模型的建立及应用[J].干旱地区农业研究,2007,25(6):5-9.
[15] 张建军,马晓群,许莹.安徽省一季稻生长气候适宜性评价指标的建立与试用[J].气象,2013,39(1):88-93.
[16] 李曼华,薛晓萍,李鸿怡.基于气候适宜度指数的山东省冬小麦产量动态预报[J].中国农学通报,2012,28(12):291-295.
[17] 么枕生.用于数值分类的聚类分析[J].海洋与湖沼通报,1994(2):1-12.
[18] 丁裕国,梁建茵,刘吉峰.EOF/PCA诊断气象变量场问题的新探讨[J].大气科学,2005,29(2):307-313.
[19] 邱美娟,宋迎波,王建林,等.新型统计检验聚类方法在精细化农业气象产量预报中的应用[J].中国农业气象,2014,35(2):187-194.
[20] 孙倩倩,刘晶淼.基于聚类分析的中国东北地区气温和降水时空变化特征[J].气象与环境学报,2014,30(3):59-65.
[21] 王展,刘荣花,薛明,等.基于气候适宜度的夏玉米发育期模拟模型[J].气象科学,2015,35(1):77-82.
[22] Jamieson P D,Porter J R,Wilson D R.A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand[J].Field Crops Research,1991,27(4):337-350.

Determination of weight coefficient in agro-meteorological yield prediction

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