| 农林重大病虫害和农业气象灾害的预警及控制技术研究 |
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| 引用本文： | 王石立.农林重大病虫害和农业气象灾害的预警及控制技术研究[J].中国气象科学研究院年报,2005(1):8-11. |
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| 作者姓名： | 王石立 |
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| 作者单位： | 生态环境与农业气象研究所 |
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| 摘 要： | 1 农业气象灾害预警技术研究
对华北农业干旱、东北作物低温冷害、江淮小麦油菜渍害、华南经济林果寒害和水产寒害等农业气象灾害分别建立了统计预测模型和机理预测模型相结合、长中短不同预报时效相结合的预警预测模型。其中作物生长模型与区域气候模式相结合的新一代农业气象灾害预测技术在实现区域尺度预测应用上取得重要进展；各类预测模型在灾害指标、预测方法上取得新的突破，预报准确率进一步提高。在此基础上，成功研制出包含多种预测方法、不同预报时效、可供准业务运行的农业气象灾害多灾种综合预测预警系统。课题研制的模型进行了业务试验，部分成果如广东经济林果寒害预警已投入业务运行。课题于2005年12月顺利通过项目主持单位农业部组织的专家验收。该课题成果代表了我国目前农业气象灾害预警预测研究的最新进展和水平，对于进一步开展和提高其他地区、其他灾害的预报能力具有一定的推广借鉴作用和应用前景。
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| 关 键 词： | 农业气象灾害 预警技术 重大病虫害 控制技术 作物生长模型 预测模型 农林 区域气候模式 |
Research on Early-Warning and Control Techniques for Agricultural and Forest Pests and Diseases and Agrometeorological Disasters |
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| Abstract: | 1 Study on Prediction of Agrometeorological Disasters
The prewarning and prediction models were established respectively for agricultural droughts in North China, crop cold damage in Northeast China, wetting and waterlogging in the Changjiang and Haihe River basin, chilling injury of fruit trees and aquiculture in South China, with varied prediction leadtime and with the statistical prediction model combined with mechanism prediction models. The new generation agrometeorological disaster prediction techniques, with the crop growth model and the regional climate model combined, has made great progress in the regional-scale prediction and application. Some breakthroughs were made in disaster indexes and prediction methods, and prediction accuracy was further improved in various prediction models. Hereby, the composite agrometeorological multiple-disaster prediction and warning system was established, which contains various prediction methods and varied leadtime and can be put to the quasi-operational use. The operational experiments of the models developed by the project have been conducted, and parts of achievements have put into practice. The project passed the acceptance check by the expert team entrusted by the Ministry of Agriculture, PRC in December 2005. The achievements represent the advanced level of this field in China, provide useful reference for the improvement of our disaster prediction capability, and show encouraging application prospects. |
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