Zhou Yu, Liu Zhiping, Zhang Guoping. Probability forecasting model of geological disaster along the Yingxia railway induced by pre-cipitation with its application. J Appl Meteor Sci, 2015, 26(6): 743-749. DOI:  10.11898/1001-7313.20150611.
Citation: Zhou Yu, Liu Zhiping, Zhang Guoping. Probability forecasting model of geological disaster along the Yingxia railway induced by pre-cipitation with its application. J Appl Meteor Sci, 2015, 26(6): 743-749. DOI:  10.11898/1001-7313.20150611.

Probability Forecasting Model of Geological Disaster Along the Yingxia Railway Induced by Pre-cipitation with Its Application

DOI: 10.11898/1001-7313.20150611
  • Received Date: 2015-03-05
  • Rev Recd Date: 2015-06-19
  • Publish Date: 2015-11-30
  • Precipitation is an important triggering factor of railway geological disasters. Every year significant economic losses are caused by railway geological disasters because of rainfall. To solve the problem of geological disaster forecasting in operational weather forecast service, a probability forecasting model is needed. Due to its special terrain and weather conditions, Yingxia Railway suffers from geological disasters more frequently and more severely. The disaster data from 2007 to 2012, as well as the temporal and spatial distribution features along Yingxia Railway are analyzed. Geological disasters happen most frequently at Qingzhou-Zhuozhai segment, especially from April to August.
        4 types of precipitation are the major trigger for the railway geological disasters: Local heavy precipitation, precipitation caused by typhoon, persistent precipitation and convectional weather. Geological disasters caused by typhoon are all relatively concentrated in Meishuikeng-Longhai-Xiamen segment. Persistent rainfall makes railway roadbed soil water saturation imbalance and thus slough or collapse may happen. Strong convective weather caused by rain could lead the soil flow to the air and thus causes the collapse of the shoulder. According to characteristics of different railway geological disasters caused by different types of precipitation, further study of the relationship between railway geological disasters and precipitation are carried out.
        10-min maximum precipitation, maximum hourly rainfall of a day, continuous rainfall and the cumulated rainfall of past 20 days are introduced as forecasting factors. Based on factor correlation analysis and logistic regression methods, the probabilistic forecasting models are established for each railway segment along Yingxia Railway. Although there are differences in precipitation hazard factor of each segment of geological disasters, the intraday precipitation is influencing for all segments. The precipitation one or two days before geological disasters plays an important role in probabilistic forecasting model. In order to verify the accuracy of this model, a test is applied on a heavy rainstorm happened from 20 May to 22 May in 2013 to forecast geological disasters of Yingxia Railway. The outcome indicates that the forecasting accuracy rates have reached above 80%. Effects of the probabilistic forecasting models are tested well. In the future, it can be used to conduct geological disaster forecasts to provide some technical support for railway safety meteorological services.
  • Fig. 1  Sections along Yingxia Railway

    Fig. 2  Frequency distribution of geological disasters for Yingxia Railway

    Table  1  Rainfall patterns and hazard situations along Yingxia Railway from 2007 to 2012

    降水类型 致灾时间 灾害次数 灾害类型 主要受灾区段 雨情
    台风降水 8—9月 58 溜坍、崩塌、滑坡、倒树侵限、栅栏倒塌、坡面风化 梅水坑—厦门 取决于台风强度和路径
    连续性降水 4—6月 417 溜坍、坍塌、水漫道床、滑坡 资溪—邵武, 青州—卓宅 24 h降水量小于50 m, 且连续降水量超过50 mm
    局地暴雨 4—6月 223 风化剥落、倒树侵限、溜坍、泥石流 各区段均有 24 h降水量超过50 mm
    强对流天气 (短时强降水、雷雨大风) 4—7月 212 溜坍、坍塌、水漫道床 青州—卓宅, 梅水坑—厦门 1 h降水量超过20 mm或10 min降水量超过7 mm
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    Table  2  Yingxia Railway geological disasters caused by typhoons and its hazard situations from 2007 to 2012

    序号 台风 登陆时间 受灾时间 次数 台风路径
    1 韦帕 2007-08-20 2007-08-20 6 西北路
    2 浣熊 2008-04-20 2008-04-20 4 北路
    3 凤凰 2008-07-30 2008-07-30 2 西北路
    4 鹦鹉 2008-08-23 2008-08-23 13 西路
    5 狮子山 2010-09-01 2010-09-02 4 北路
    6 莫兰蒂 2010-09-10 2010-09-10 7 北路
    7 凡亚比 2010-09-21 2010-09-21 10 西北路
    8 米蕾 2011-06-25 2011-06-25 5 北路
    9 南玛都 2011-08-31 2011-08-31 2 西北路
    10 苏拉 2012-08-03 2012-08-03 5 西北路
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    Table  3  Related statistics based on logistic regression equation along Qingzhou-Zhuozhai

    降水量因子 回归系数 标准差 Wald检验值 自由度 显著性水平 期望值
    R20 0.003 0.002 5.057 1 0.025 1.003
    R0 0.022 0.005 17.390 1 0.005 1.023
    R1 0.019 0.005 18.588 1 0.001 1.019
    R2 0.016 0.007 5.379 1 0.005 1.016
    R3 0.012 0.007 7.609 1 0.001 1.013
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    Table  4  Sectional probabilistic models of geological disasters along Yingxia Railway

    区段 判对率/% 概率模型
    鹰潭—资溪 80.2
    资溪—邵武 73.0
    邵武—吉舟 82.6
    吉舟—青州 78.3
    青州—卓宅 76.9
    卓宅—梅水坑 74.0
    梅水坑—龙海 83.8
    龙海—厦门 82.4
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    Table  5  Rainstorm factors and predictive value of geological disasters from 20 May to 22 May in 2013

    区段 灾害次数 降水量因子/mm P实际 P预报
    R0 R1 R2 R3 Rc R20 R10 min
    鹰潭—资溪 0 4 10.2 6.0 0 20.2 114 2.1 0 0.14
    资溪—邵武 0 4.2 8.5 6.2 0 18.9 109 0.5 0 0.12
    邵武—吉舟 0 3.7 32 31.4 0 65.1 170 0.3 0 0.32
    吉舟—青州 2 24.1 17.6 0 0 88.9 39 4.7 1 0.56
    青州—卓宅 5 3.4 24.1 7.7 0.2 35.2 104.6 1.3 1 0.37
    卓宅—梅水坑 4 0.1 4.3 73.5 5.1 127 121.9 0.1 1 0.76
    梅水坑—龙海 22 45.3 0 0.1 5.2 45.3 83.8 13.1 1 0.96
    龙海—厦门 5 39.6 121 0 1 160 201 8.5 1 0.92
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  • [1]
    刘传正, 温铭生, 刘艳辉. 基于气象因素的区域地质灾害预报原理与应用//第二届全国岩土与工程学术大会论文集 (上册), 2006: 696-703.
    [2]
    贾小龙, 陈丽娟, 高辉, 等.我国短期气候预报技术进展.应用气象学报, 2013, 24(6):641-655. doi:  10.11898/1001-7313.20130601
    [3]
    张亚杰, 吴慧, 吴胜安, 等.南渡江流域暴雨洪涝致灾临界面雨量的确定.应用气象学报, 2014, 25(6):731-740. doi:  10.11898/1001-7313.20140609
    [4]
    李明, 唐红梅, 叶四桥.典型地质灾害链式机理研究.灾害学, 2008, 23(1):1-5. http://www.cnki.com.cn/Article/CJFDTOTAL-CSDI201610030.htm
    [5]
    刘传正.中国崩塌滑坡泥石流灾害成因类型.地质评论, 2014, 60(4):858-868. http://www.cnki.com.cn/Article/CJFDTOTAL-DZLP201404018.htm
    [6]
    崔鹏.中国山地灾害研究进展与未来应关注的科学问题.地理科学进展, 2014, 33(2):145-152. doi:  10.11820/dlkxjz.2014.02.001
    [7]
    Wei F Q, Yang H J.Measuring internal velocity of debris flows by temporally correlated shear forces.Journal of Earth Science.2012, 3(3):373-380.
    [8]
    刘艳辉, 唐灿, 李铁锋, 等.地质灾害与降水雨型的关系研究.工程地质学报, 2009, 17(5):656-661. http://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ200905012.htm
    [9]
    李媛, 杨旭东.降雨诱发区域性滑坡预报预警方法研究.水文地质工程地质, 2006(2):101-103;107. http://www.cnki.com.cn/Article/CJFDTOTAL-SWDG200602026.htm
    [10]
    徐晶, 张国平, 张芳华, 等.基于Logistic回归的区域地质灾害综合气象概率预报模型.气象, 2007, 22(12):3-8. doi:  10.7519/j.issn.1000-0526.2007.12.001
    [11]
    徐晶, 李伟华.台风强降水诱发地质灾害的降水量特征分析.气象, 2009, 35(8):42-48. doi:  10.7519/j.issn.1000-0526.2009.08.005
    [12]
    张国平.有效降水量和泥石流滑坡灾害概率模型.气象, 2014, 40(7):886-890. doi:  10.7519/j.issn.1000-0526.2014.07.013
    [13]
    温华洋, 田红, 唐为安, 等.安徽省电线积冰标准冰厚的气象估算模型.应用气象学报, 2011, 22(6):747-752. doi:  10.11898/1001-7313.20110613
    [14]
    张自银, 马京津, 雷杨娜.北京市夏季电力负荷逐日变率与气象因子关系.应用气象学报, 2011, 22(6):760-765. doi:  10.11898/1001-7313.20110615
    [15]
    魏庆朝, 杨永平, 张大炜.中国铁路水害环境致灾因子分析.自然灾害学报, 2002, 11(1):123-127. http://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH200201020.htm
    [16]
    张清, 黄朝迎.我国铁路水害及其评估模型研究.应用气象学报, 1999, 10(4):498-502. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=199904103&flag=1
    [17]
    周华国, 魏庆朝, 曾学贵, 等.近十几年来中国铁路水害的时空统计特征.自然灾害学报, 1995, 4(4):76-81. http://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH199504011.htm
    [18]
    刘秀英, 范永玲, 张喜娃, 等.铁路水害临界降水量值的初步探讨.山西农业科学, 2007, 35(10):56-57. http://www.cnki.com.cn/Article/CJFDTOTAL-SXLX200710020.htm
    [19]
    许力, 王锦贵, 陈桂英.优选概率集成预报研究初步.应用气象学报, 2005, 16(增刊Ⅰ):133-135. http://www.cnki.com.cn/Article/CJFDTOTAL-YYQX2005S1018.htm
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    • Received : 2015-03-05
    • Accepted : 2015-06-19
    • Published : 2015-11-30

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