四川省降雨诱发滑坡灾害的气象预警模型
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四川省国土资源厅科学研究计划(KJ-2015-18);四川省应急测绘与防灾减灾工程技术研究中心开放基金资助项目(K2014B002);数字制图与国土信息应用工程国家测绘地理信息局重点实验室开放基金资助项目(DM2014SC01);四川省高校人文社会科学重点研究基地“气象灾害预测预警与应急管理研究中心”开放课题(ZHYJ15-YB09);城市空间信息工程北京市重点实验室经费资助项目(2014202)


Meteorologic Early-warning Model for Rainfall-induced Landslide Disasters in Sichuan Province
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    摘要:

    [目的] 分析四川省2008-2014年的滑坡灾害与前期降雨量间的关系,构建降雨诱发滑坡灾害气象预警模型,优化模型的权重参数,为四川省滑坡灾害预警工作提供有效参考。[方法] 基于降雨信息资料,对四川省滑坡灾害的前期雨量进行统计分析,并采用逻辑回归分析分别计算和优化灾害的前期综合日降雨量间的权重关系和气象预警模型中地质环境背景值与降雨诱发灾害概率值的权重系数。[结果] 滑坡灾害的当日降雨量、前一日降雨量和前两日降雨量对灾害的影响权重分别为0.587,0.220,0.189,气象预警模型的地质背景概率和综合雨量概率的权重参数分别为0.394,0.606。根据以上研究构建灾害气象预警模型,利用已有灾害点对其进行验证,证得模型的整体准确率为78.36%,进而通过2013年7月10日的群发滑坡灾害个例对模型进行检验,检验结果良好。[结论] 该模型预警效果良好,精确度较高,能为相关部门提供的防灾减灾参考。

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    [Objective] The relation between landslide hazards and antecedent rainfall in 2008 to 2014 was analyzed. A meteorological early-warning model for the rainfall-induced landslide hazards was established and the weight coefficients of the model were optimized in order to provide an efficient reference for disaster warning.[Methods] Through statistical analysis of the antecedent rainfall based on the precipitation information, we adopted logistic regression analysis to calculate the weights of daily rainfall and optimize the weight coefficients of the model.[Results] The weights of disaster-occurring day rainfall, the 2-day and the 3-day rainfall before landslide disaster are 0.587, 0.220 and 0.189. The weight coefficients of the model for geological background and rainfall are 0.394 and 0.606. The previously occurred disasters were used to test and verify the model and the accuracy is 78.36%. The massively occurred disasters were also taken in July 10, 2013 as a single example to verify the model and the result is rather good.[Conclusion] The model has good early warning effect, so as to provide an efficient reference for the disaster prevention and mitigation.

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费晓燕,柳锦宝,屈伯强,刘志红,王增武.四川省降雨诱发滑坡灾害的气象预警模型[J].水土保持通报,2017,37(5):315-321,327

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历史
  • 收稿日期:2017-03-28
  • 最后修改日期:2017-04-25
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  • 在线发布日期: 2017-11-14
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