基于Fisher判别的南方双季稻低温灾害等级预警
发布时间：2019-07-04 07:30
【摘要】：为了建立南方双季稻低温灾害综合预测预警技术体系,基于南方双季稻种植区1961 2010年708个气象站的逐日气象资料、水稻生育期资料和低温灾害发生的气象行业标准,采用Fishe r判别分析法、因子膨化法、相关性分析法,利用SPSS软件构建早稻春季低温灾害高风险区(Ⅰ区)未来10 d、晚稻寒露风高风险区(Ⅰ区)、主灾区(Ⅱ区)未来5 d的低温灾害发生等级逐日滚动预警模型。其中,1961 2009年资料用于模型构建和回代检验,2010年资料用于模型的外延预测。结果表明:早稻、晚粳稻、晚籼稻Ⅰ区平均外延预测基本一致准确率分别达到90.5%,74.2%,80.3%,晚粳稻、晚籼稻Ⅱ区平均外延预测基本一致准确率分别为89.4%和80.3%。构建的南方双季稻低温灾害逐日滚动预警模型的外延预测基本一致准确率多超过80%,等级预测检验误差总体上在1个等级以内,模型评价效果较好。
[Abstract]:In order to establish the comprehensive prediction and early warning technology system of low temperature disaster in southern double cropping rice, based on the daily meteorological data of 708 meteorological stations in southern double cropping rice growing area in 1961 and 2010, the data of rice growth period and the meteorological industry standard of low temperature disaster, Fishe r discriminant analysis, factor expansion method and correlation analysis were used to construct the early rice spring low temperature disaster high risk area (area I) for the next 10 days. A daily rolling early warning model for the occurrence of low temperature disasters in the high risk area of late rice Cold Dew (area 鈪，
本文编号：2509740
[Abstract]:In order to establish the comprehensive prediction and early warning technology system of low temperature disaster in southern double cropping rice, based on the daily meteorological data of 708 meteorological stations in southern double cropping rice growing area in 1961 and 2010, the data of rice growth period and the meteorological industry standard of low temperature disaster, Fishe r discriminant analysis, factor expansion method and correlation analysis were used to construct the early rice spring low temperature disaster high risk area (area I) for the next 10 days. A daily rolling early warning model for the occurrence of low temperature disasters in the high risk area of late rice Cold Dew (area 鈪，
本文编号：2509740
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