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• 方法与技术 • 上一篇    

浙江省稻曲病发生气象等级预报技术

王治海1,孟仲1,金志凤1*,谢子正2,黄世文3,杨波1,季丹丹4   

  1. (1浙江省气候中心, 杭州 310017; 2浙江省植物保护检疫局, 杭州 310020; 3中国水稻研究所, 杭州 310006; 4柯桥区气象局, 浙江绍兴 312030)
  • 出版日期:2019-07-10 发布日期:2019-07-10

Forecast technique for meteorological grade of rice false smut.

WANG Zhi-hai1, MENG Zhong1, JIN Zhi-feng1*, XIE Zi-zheng2, HUANG Shi-wen3, YANG Bo1, JI Dan-dan4   

  1. (1Zhejiang Climate Center, Hangzhou 310017, China; 2Zhejiang Provincial Bureau of Plant Protection and Quarantine, Hangzhou 310020, China; 3China National Rice Research Institute, Hangzhou 310006, China; 4KeqiaoMeteorological Bureau, Shaoxing 312030, Zhejiang, China).
  • Online:2019-07-10 Published:2019-07-10

摘要: 开展稻曲病气象等级预报技术研究对提高水稻病害防控能力具有重要意义。基于浙江省稻曲病大田调查资料、71个常规自动气象站和2259个区域自动气象站的观测数据,以及最优化集成释用(OCF)精细化数值预报产品,应用加权指数求和法和GIS唯一值渲染技术,建立了稻曲病促病气象指数模型和气象等级动态预报方法。结果表明:促病气象指数模型回代检验准确率达87.5%,模拟效果较好;稻曲病气象等级逐日动态预报时效8 d,空间分辨率为乡镇单元;2018年8月21日稻曲病预报结果在全省11个地区的检验准确率达90.9%,气象等级与实际病情基本一致。研究成果可为农作物病害精细化定量化的监测预报服务提供气象科技支撑。

关键词: 油松中龄林, 郁闭度, 林木形质, 层次分析法, 黄土高原

Abstract: Research on meteorological grade prediction for rice false smut is critical to the prevention of rice disease. Based on the meteorological data from 71 basic weather stations and 2259 regional automatic stations in Zhejiang Province, Optimized Consensus Forecast fine grid numerical prediction products, as well as field investigation of rice false smut, the diseasepromoting meteorological index model and dynamic forecast method for rice false smut grade were established by GIS and weighted index sum method. Results showed that the disease-promoting meteorological index model performed well, with a validation accuracy rate of 87.5%. The meteorological grade of rice false smut could be predicted eight days in advance, with resolution at township. The forecast result of 21 August, 2018 was consistent with the actual situation, with a test accuracy rate of 90.9% in 11 cities across the province. Our results provide scientific meteorological technique support for fine and quantitative monitoring and forecasting services of crop disease.

Key words: middleaged Pinus tabuliformis plantation, canopy density, tree form quality, AHP, the Loess Plateau.