Chinese Journal of Agrometeorology ›› 2015, Vol. 36 ›› Issue (02): 187-194.doi: 10.3969/j.issn.1000-6362.2015.02.009

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Application of Climate Suitability Index Coupling Soil Moisture in Dynamic Yield Prediction of Winter Wheat in Shandong Province

QIU Meijuan, SONG Yingbo, WANG Jianlin, WU Dingrong, LIU Ling, LIU Jiandong   

  1. 1Institute of Meteorological Sciences of Jilin Province, Changchun130062,China; 2Chinese Academy of Meteorological Sciences,Beijing100081; 3National Meteorological Center, Beijing100081
  • Received:2014-08-19 Online:2015-04-20 Published:2015-06-25

Abstract: Taking into account soil moisture, and taking advantage of developmental stages, yield material and daily meteorological data of 14 weather stations from 1981 to 2011 in Shandong Province, and each tenday soil moisture material of 20 centimeter in growth stages of winter wheat, the climate suitability index in different growth stages of winter wheat were constructed. In addition, dynamic yield forecast model of each tenday during March to May were established, based on two kinds of climate suitability index, via the correlation and regression analysis with meteorological yield, and history back to the generation of test and dynamic extrapolation forecast were made. The results showed that the climate suitability index that considering soil moisture could reflect the influence of weather and soil moisture conditions on the yield formation more objective, and its correlation with meteorological yield had all passed the significant test of the 0.01 level, which was greater than the correlation between climate suitability taking no account of soil moisture and meteorological yield. The mean accuracy of the dynamic prediction model of yield for historical fitting test was all above 95.0%, and the standardized root mean square error RMSE was less than 6%. The dynamic prediction of yield in 2010-2011 showed that, the accuracy of the highest reached 99.4%, and the lowest was 95.4%. The accuracy of prediction was higher so that the dynamic prediction model of yield could apply to operational service.

Key words: Growth stage, Meteorological yield, Meteorological condition, Soil moisture