| 广西双季稻种植区涝灾量化评估技术研究 |
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| 引用本文： | 黄海洪,谭宗琨,罗永明.广西双季稻种植区涝灾量化评估技术研究[J].中国农学通报,2019,35(11):95-102. |
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| 作者姓名： | 黄海洪 谭宗琨 罗永明 |
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| 作者单位： | 广西壮族自治区气象减灾研究所 |
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| 基金项目： | 公益性行业专项（气象）“海南冬菜气象灾害监测预警技术研究”(GYHY201206019)；广西区政府与中国气象局省部合作项目“广西农业气 象服务集约化业务系统”(504001XM15N0016)；广西区气象局重点项目“广西农业气象服务集约化业务系统关键技术研究”(GQK2016Z102)。 |
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| 摘 要： | 通过对广西南、中、北不同地形地貌代表县份历史典型涝灾年强降水过程的雨量分析,结果表明：涝灾当前日有效雨量与灾前6d有效雨量和的线性关系最为明显,达到95%置信检验。在此基础上,基于前人研究成果和历史灾情,构建了以涝灾当前日与灾前6d的有效雨量总和为致灾因子的农田涝灾等级指标,并以广西双季稻种植空间分布遥感信息为涝灾承灾体,采用智能格点雨量预报产品、乡镇自动观测站实时雨量的有效雨量值栅格图与之镶嵌、融合方法,实现广西双季稻洪涝灾前的量化评估。这一研究结果对政府及相关部门针对性开展防灾减灾,以及气象为农智慧化直通式服务有积极意义。
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| 关 键 词： | 涝灾 等级 双季稻种植区 灾前量化评估 |
| 收稿时间： | 2017/12/1 0:00:00 |
| 修稿时间： | 2018/1/16 0:00:00 |
Quantitative Assessment of Waterlogging in Double-cropping Rice Area in Guangxi |
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| Abstract: | The paper aims to analyze rainfalls of typical flood years over the past 30 years in representative counties of southern, central and northern Guangxi. The results showed that: the linear correlation between the effective rainfall of the waterlogging disaster day and that of the 6 days before flood was most obvious, reached 95% confidence level. Based on this finding as well as previous studies and disasters in history, the grade index of farmland waterlogging was constructed by the sum of the effective rainfall of the waterlogging disaster day and that of the 6 days before the flood. Taking the remote sensing information of the spatial distribution of double-cropping rice in Guangxi as the waterlogging disaster bearing body, smart grid point rainfall forecast products were embedded in and mixed with the effective rainfall raster maps of real- time rainfall from township automatic observation stations, to realize the quantitative assessment of double-cropping rice before waterlogging disaster in Guangxi. This research can provide certain references for government institutions to carry out disaster prevention and mitigation, and promote direct and smart meteorological service for
agricultural production. |
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| Keywords: | waterlogging grades double-cropping rice planting area quantitative assessment before disaster |
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