湖北农业科学 ›› 2021, Vol. 60 ›› Issue (22): 195-200.doi: 10.14088/j.cnki.issn0439-8114.2021.22.041

• 经济·管理 • 上一篇    下一篇

基于产量历史丰歉气象影响指数的辽宁省粮食作物产量动态预报

王贺然1, 张琪1, 陈鹏狮1, 赵明2, 刘东明1, 黄岩1, 黄悦3   

  1. 1.辽宁省生态气象和卫星遥感中心,沈阳 110166;
    2.辽宁省气象台,沈阳 110166;
    3.中国平安财产保险股份有限公司,深圳 518048
  • 收稿日期:2020-09-14 出版日期:2021-11-25 发布日期:2021-12-10
  • 通讯作者: 黄岩(1985-),女,辽宁辽阳人,高级工程师,硕士,主要从事农业气象科研服务工作,(电话)18802488909(电子信箱)yanhuangstone@126.com。
  • 作者简介:王贺然(1985-),女,辽宁抚顺人,高级工程师,博士,主要从事农业气象科研服务工作,(电话)15840102104(电子信箱)wangheran001@aliyun.com。
  • 基金资助:
    2019年国内外作物产量气象预报专项; 中国气象局沈阳大气环境研究所区域合作项目(2020SYIAEHZ1); 东北区域气象中心科技创新联合攻关任务合作项目(2019QYLH3); 中国气象局沈阳大气环境研究所区域合作项目(2020SYIAEZD3); 辽宁省科技厅农业攻关及产业化项目(2017210001); 辽宁省气象局博士启动金项目(D201604); 辽宁省气象局科研课题(BA202008)

Dynamic forecast of cereals yield in Liaoning province based on influence index for bumper or poor harvest from historic yield

WANG He-ran1, ZHANG Qi1, CHEN Peng-shi1, ZHAO Ming2, LIU Dong-ming1, HUANG Yan1, HUANG Yue3   

  1. 1. Ecological Meteorology and Satellite Remote Sensing Center of Liaoning Province,Shenyang 110166,China;
    2. Meteorological Observatory of Liaoning Province,Shenyang 110166,China;
    3. China Ping An Property Insurance Co., Ltd., Shenzhen 518048,China
  • Received:2020-09-14 Online:2021-11-25 Published:2021-12-10

摘要: 基于作物产量历史丰歉气象影响指数,建立2016年辽宁省14市及全省的春玉米、水稻、大豆的产量动态预报模型,探究辽宁省粮食作物产量动态预报方法。结果表明,辽宁省春玉米、水稻、大豆的单产预报准确率普遍高于80%,其中在不同预报时间,水稻的单产预报准确率普遍高于其他2种旱田作物且预报值较稳定。该方法可以实现辽宁省三大粮食作物的逐候产量动态预报,满足辽宁省省、市两级作物产量预报业务需求,为该地区及时、准确进行产量预测提供技术支撑。

关键词: 影响指数, 产量预报, 春玉米, 水稻, 大豆, 辽宁省

Abstract: Based on the influence index for bumper or poor harvest from historic yield, the dynamic forecast models for spring maize, rice, soybean of Liaoning province and 14 cities in 2016 were constructed, the dynamic forecast technology of cereals yield in Liaoning province was studied. The results showed that the forecast accuracy of unit yield of spring maize, rice, soybean in Liaoning province were generally over 80%, in different forecast time, the forecast accuracy of rice yield were generally higher than the other two, and the results were stable. This technology can realize the dynamic forecast of the three grain crops in Liaoning province and meet the needs of production forecast business of provincial and municipal crops in Liaoning province, in order to provide technical support for timely and accurate production prediction in the region.

Key words: influence index, yield forecast, spring maize, rice, soybean, Liaoning province

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