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

FEI Xiaoyan; LIU Jinbao; QU Boqiang; LIU Zhihong; WANG Zengwu

doi:10.13961/j.cnki.stbctb.2017.05.053

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

- Meteorologic Early-warning Model for Rainfall-induced Landslide Disasters in Sichuan Province
- Bulletin of Soiland Water Conservation Vol. 37, Issue 5, Pages: 315-321(2017)
- 作者机构：
  
  1. 成都信息工程大学资源环境学院,四川,成都,610225
  2. 城市空间信息工程北京市重点实验室,北京,100038
  3. 四川省地质环境监测总站,四川,成都,610081
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2017.05.053
  CLC：
- Published：2017
- 稿件说明：
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FEI Xiaoyan, LIU Jinbao, QU Boqiang, et al. Meteorologic Early-warning Model for Rainfall-induced Landslide Disasters in Sichuan Province[J]. Bulletin of Soiland Water Conservation, 2017, 37(5): 315-321.
DOI：

FEI Xiaoyan, LIU Jinbao, QU Boqiang, et al. Meteorologic Early-warning Model for Rainfall-induced Landslide Disasters in Sichuan Province[J]. Bulletin of Soiland Water Conservation, 2017, 37(5): 315-321. DOI： 10.13961/j.cnki.stbctb.2017.05.053.

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。

Abstract

[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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