两种不同产量历史丰歉气象影响指数确定方法在农业气象产量预报中的对比研究
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摘要
利用吉林省1980—2015年春玉米单产数据、50个气象站逐日气象资料,基于欧式距离和相关系数建立综合诊断指标,利用综合诊断指标研究分析预报年与历史年春玉米气象产量丰歉气象影响指数的关系,以此构建春玉米产量预报模型,对吉林省春玉米产量进行动态预报。产量预报模型对2003—2012年的预报试验结果表明,产量丰歉趋势ΔY的平均正确率均在60%以上,加权分析法的单产预报准确率除2009年外,均高于80.0%,且各时段的预报准确率均高于大概率法的。对2013—2015年吉林省春玉米产量的预报检验结果表明,加权分析法对产量丰歉趋势ΔY的预报结果稍好;加权分析法单产预报准确率几乎都在90.0%以上,普遍高于大概率法的。说明加权分析法建立的产量预报模型预报效果更好,可在业务上应用。
Based on the data of spring maize yield and the daily meteorological data at 50 meteorological stations in Jilin province during 1980—2015, the integrated diagnostic indexes were established based on Euclidean distance and correlation coefficient. Using the integrated diagnostic indexes, the relationship of impact index of spring maize yield between forecast year and history year was analyzed. The spring maize yield prediction model was established, and used to forecast spring maize yield in Jilin province. The results of yield prediction model for 2003—2012 indicated that the average accuracy of the trend of bumper or poor harvest ΔY was all above 60%, and the per unit yield forecast accuracy of the weighted analysis method was all higher than 80.0%(except in 2009), and was higher than that of large probability method at each forecast period. The test results of yield prediction model for 2013—2015 indicated that the result of the trend of bumper or poor harvest ΔY of the weighted analysis method was slightly better, and the yield prediction accuracy of the weighted analysis method was almost more than 90.0%,generally higher than the large probability method. The results indicated that the method of weighted analysis could better predict the yield and could be used in business.
Based on the data of spring maize yield and the daily meteorological data at 50 meteorological stations in Jilin province during 1980—2015, the integrated diagnostic indexes were established based on Euclidean distance and correlation coefficient. Using the integrated diagnostic indexes, the relationship of impact index of spring maize yield between forecast year and history year was analyzed. The spring maize yield prediction model was established, and used to forecast spring maize yield in Jilin province. The results of yield prediction model for 2003—2012 indicated that the average accuracy of the trend of bumper or poor harvest ΔY was all above 60%, and the per unit yield forecast accuracy of the weighted analysis method was all higher than 80.0%(except in 2009), and was higher than that of large probability method at each forecast period. The test results of yield prediction model for 2013—2015 indicated that the result of the trend of bumper or poor harvest ΔY of the weighted analysis method was slightly better, and the yield prediction accuracy of the weighted analysis method was almost more than 90.0%,generally higher than the large probability method. The results indicated that the method of weighted analysis could better predict the yield and could be used in business.
引文
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[20]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.
[21]黄晚华,薛昌颖,李忠辉,等.基于作物生长模拟模型的产量预报方法研究进展[J].中国农业气象,2009,30(增1):140-143.
[22]帅细强,陆魁东,黄晚华.不同方法在湖南省早稻产量动态预报中的比较[J].应用气象学报,2015,26(1):103-111.
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[25]邱美娟.基于动力与统计相结合的精细化冬小麦产量动态预报集成技术研究[D].北京:中国气象科学研究院,2014.
[2]张桂华,王艳秋,郑红,等.气候变暖对黑龙江省作物生产的影响及其对策[J].自然灾害学报,2004,13(3):95-100.
[3]王洪丽,杨双,王军,等.吉林省玉米产量波动分析[J].玉米科学,2011,19(5):134-136.
[4]郭庆海.吉林省玉米产业发展面临的问题及对策[J].玉米科学,2011,19(5):128-133.
[5]阿布都克日木·阿巴司,努尔帕提曼·买买提热依木,帕提曼·阿不都艾尼,等.喀什地区夏玉米发育期与气象因子关系分析[J].沙漠与绿洲气象,2016,10(4):25-31.
[6]王海梅.高温胁迫对河套灌区玉米生理指标及产量构成要素的影响[J].干旱气象,2015,33(1):59-62.
[7]穆佳.东北区玉米生产对气候变化的响应[D].北京:中国气象科学研究院,2015.
[8]孙向伟.2015年农业气象条件对河套灌区春玉米生长的影响[J].农业灾害研究,2016,6(1):26-27.
[9]王秀萍,刘荣花,詹静.连阴雨对玉米的影响研究进展[J].气象与环境科学,2016,39(4):121-125.
[10]邱美娟,宋迎波,王建林,等.山东省冬小麦产量动态集成预报方法[J].应用气象学报,2016,27(2):191-200.
[11]辜永强,郝宏飞,郝宏蕾,等.巴楚夏玉米产量对气候变化的响应[J].沙漠与绿洲气象,2017,11(6):89-93.
[12]成林,刘荣花.农学模式在冬小麦产量动态预报中的应用[J].气象与环境科学,2017,40(2):28-32.
[13]Holzman M E,Rivas R E.Early maize yield forecasting from remotely sensed temperature/vegetation index measurements[J]. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing,2016,9(1):507-519.
[14]陶祖钰,赵翠光,陈敏.谈谈统计预报的必要性[J].气象科技进展,2016,6(1):6-13.
[15]吴钟铃,陈铁如,李琳一.农业气象产量预报方法的探讨和长春水稻、玉米产量试报[J].吉林农业大学学报,1993,15(4):20-23.
[16]邹春辉,陈怀亮,张雪芬.新一代省级农业气象预报系统通用统计预报模型的设计与实现[J].气象与环境科学,2005(2):40-42.
[17]钱永兰,侯英雨,延昊,等.基于遥感的国外作物长势监测与产量趋势估计[J].农业工程学报,2012,28(13):166-171.
[18]罗丽华,陈桂华,胡英,等.气象因素与早稻产量因子的相关性分析[J].自然资源学报,2010,25(10):1718-1726.
[19]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.
[20]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.
[21]黄晚华,薛昌颖,李忠辉,等.基于作物生长模拟模型的产量预报方法研究进展[J].中国农业气象,2009,30(增1):140-143.
[22]帅细强,陆魁东,黄晚华.不同方法在湖南省早稻产量动态预报中的比较[J].应用气象学报,2015,26(1):103-111.
[23]易雪.早稻产量动态预报技术研究[D].南京:南京信息工程大学,2010.
[24]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.
[25]邱美娟.基于动力与统计相结合的精细化冬小麦产量动态预报集成技术研究[D].北京:中国气象科学研究院,2014.