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基于概率分析的公路系统灾害风险研究

刘强 汤爱平

刘强, 汤爱平. 基于概率分析的公路系统灾害风险研究[J]. 西南交通大学学报, 2021, 56(6): 1268-1274, 1289. doi: 10.3969/j.issn.0258-2724.20191132
引用本文: 刘强, 汤爱平. 基于概率分析的公路系统灾害风险研究[J]. 西南交通大学学报, 2021, 56(6): 1268-1274, 1289. doi: 10.3969/j.issn.0258-2724.20191132
LIU Qiang, TANG Aiping. Highway System Disaster Risk Based on Probability Analysis[J]. Journal of Southwest Jiaotong University, 2021, 56(6): 1268-1274, 1289. doi: 10.3969/j.issn.0258-2724.20191132
Citation: LIU Qiang, TANG Aiping. Highway System Disaster Risk Based on Probability Analysis[J]. Journal of Southwest Jiaotong University, 2021, 56(6): 1268-1274, 1289. doi: 10.3969/j.issn.0258-2724.20191132

基于概率分析的公路系统灾害风险研究

doi: 10.3969/j.issn.0258-2724.20191132
基金项目: 战略性国际科技创新合作重点专项(2016YFE0202400)
详细信息
    作者简介:

    刘强(1994—),男,博士研究生,研究方向为交通灾害评估与管理,E-mail:qiangliuhit@163.com

    通讯作者:

    汤爱平(1968—),男,教授,研究方向为生命线工程防灾减灾,E-mail:tangap@hit.edu.cn

  • 中图分类号: U418.56

Highway System Disaster Risk Based on Probability Analysis

  • 摘要:

    针对高寒地区公路系统遭遇雪灾规模大、持续时间长的特点,以黑龙江地区公路系统及其常遭遇的风吹雪灾害为研究对象,从灾害发生机理探究灾害形成的宏观条件;基于概率论思想,通过影响因素的联合概率密度函数,将致灾因子发生可能性、危险等级及危险强度三者联系在一起,阐明了致灾因子的危险性评价理论;在公路系统脆弱性评估的基础上,构建了适用于寒区公路系统的风吹雪灾害风险评估体系. 通过此体系对黑龙江省2017年2月份内的风吹雪事件进行评估,并将预测结果与省气象信息中心发布的道路预警进行对比. 结果表明:研究区公路网在评价时段内相对风险等级最高的是鹤岗-伊春线、绥化-大庆线的绥化段、哈同公路的哈尔滨和佳木斯段以及牡丹江市周边,其相对风险概率大于0.69,需要对此路段多加关注. 该研究在一定程度上为今后寒区公路网的雪灾救援及物资配置提供了参考,使得寒区防灾减灾任务更加具有针对性.

     

  • 图 1  风吹雪灾害研究技术线路

    Figure 1.  Technical line of wind and snow blowing disaster

    图 2  降雪量概率统计分析

    Figure 2.  Probability analysis of snowfall

    图 3  风速概率统计分析

    Figure 3.  Probability analysis of wind speed

    图 4  风吹雪灾害危险性等级区划

    Figure 4.  Hazard grade zoning of snowdrift disaster

    图 5  公路脆弱性影响因素分布情况

    Figure 5.  Distribution of affecting factors on highway vulnerability

    图 6  公路系统网脆弱性等级

    Figure 6.  Vulnerability levels of highway system network

    图 7  风吹雪灾害风险等级区划

    Figure 7.  Risk level zoning of snowdrift disaster

    表  1  风吹雪灾害危险性等级划分

    Table  1.   Hazard classification of snowdrift disaster

    危险等级发生概率危险强度
    Ⅰ级 > 0.92 极高
    Ⅱ级 (0.72,0.92]
    Ⅲ级 (0.56,0.72] 较高
    Ⅵ 级 (0.42,0.56]
    Ⅴ级 ≤ 0.42 极低
    下载: 导出CSV

    表  2  公路系统脆弱性等级划分

    Table  2.   Classification of highway system vulnerability

    脆弱性
    分级
    Ⅰ级Ⅱ级Ⅲ级Ⅳ级V 级
    脆弱性
    指数
    > 0.85(0.70,0.85](0.50,0.70](0.35,0.70]≤ 0.35
    下载: 导出CSV

    表  3  风吹雪灾害风险性等级划分

    Table  3.   Risk classification of snowdrift disaster

    风险等级计算风险发生概率风险强度
    Ⅰ级> 0.69极高
    Ⅱ级(0.47,0.69]
    Ⅲ级(0.30,0.47]较高
    Ⅳ 级(0.15,0.30]较低
    V 级≤ 0.15
    下载: 导出CSV
  • [1] 梁伟,冀永进,李海梅. 灾害事件对我国城乡规划的启示[J]. 城市规划,2011,35(2): 26-31.

    LIANG Wei, JI Yongjin, LI Haimei. Enlightenment of disasters to China’s urban-rural planing[J]. City Planning Review, 2011, 35(2): 26-31.
    [2] YIN Z E, YIN J, XU S Y et al. Community-based scenario modelling and disaster risk assessment of urban rainstorm waterlogging[J]. Journal of Geographical Sciences, 2011, 21(2): 274-284. doi: 10.1007/s11442-011-0844-7
    [3] 史培军. 防灾减灾是国家可持续发展的基础[N]. 中国气象报, 2014-06-11(1).
    [4] 刘艳华,曹蕾,白秀梅. 灾害天气对黑龙江省高速公路交通安全的影响及精细化防御措[J]. 自然灾害学报,2019,28(3): 114-118.

    LIU Yanhua, CAO Lei, BAI Xiumei. Influence of disaster weather on traffic safety of freeway in Heilongjiang Province and detailed defense measures[J]. Journal of Natural Disasters, 2019, 28(3): 114-118.
    [5] 曹玮,秦其明,范一大,等. 中国雪灾评估研究综述[J]. 灾害学,2013,28(4): 152-158. doi: 10.3969/j.issn.1000-811X.2013.04.027

    CAO Wei, QIN Qiming, FAN Yida, et al. Review on snow disaster assessment in China[J]. Journal of Catastrophology, 2013, 28(4): 152-158. doi: 10.3969/j.issn.1000-811X.2013.04.027
    [6] 隋琦,王瑛,李婷,等. 多源信息结合的雪灾交通风险评估研究[J]. 地球信息科学,2018,20(11): 1571-1578.

    SUI Qi, WANG Ying, LI Ting, et al. Application of multi-source information fusion in the traffic risk assessment of snow disaster[J]. Journal of Geo-information Science, 2018, 20(11): 1571-1578.
    [7] BERROCAL V J, RAFTERY A E, GNEITING T, et al. Probabilistic weather forecasting for winter road maintenance[J]. Journal of the American Statistical Association, 2010, 105(490): 522-537. doi: 10.1198/jasa.2009.ap07184
    [8] 席建锋,李江,朱光耀,等. 公路风吹雪积雪力学原理与积雪深模型[J]. 吉林大学学报(工学版),2006,36(2): 152-156.

    XI Jiangfeng, LI Jiang, ZHU Guangyao, et al. Hydromechanical mechanism of road snowdrift deposit and its depth model[J]. Journal of Jilin University (Engineering and Technology Edition), 2006, 36(2): 152-156.
    [9] 夏才初,周开方,程怡,等. 基于BP神经网络的公路风吹雪雪深预测模型[J]. 同济大学学报(自然科学版),2017,45(5): 714-721.

    XIA Caichu, ZHOU Kaifang, CHENG Yi, et al. Prediction modeal of smowdrift on highway based on BP neural newwork[J]. Journal of Tongji University (Natural Science), 2017, 45(5): 714-721.
    [10] 高卫东,刘明哲,魏文寿,等. 铁路沿线风吹雪灾害及其防治研究[J]. 中国铁道科学,2004,25(5): 97-101. doi: 10.3321/j.issn:1001-4632.2004.05.019

    GAO Weidong, LIU Mingzhe, WEI Wentao, et al. Study on the drifting snow disaster along railway and preventive treatment[J]. China Railway Science, 2004, 25(5): 97-101. doi: 10.3321/j.issn:1001-4632.2004.05.019
    [11] 秦华锋,金荣花. “0703”东北暴雪成因的数值模拟研究[J]. 气象,2008,34(4): 30-38. doi: 10.7519/j.issn.1000-0526.2008.04.004

    QIN Huafeng, JIN Ronghua. Numerical simulation study of the cause of snow storm process in northeast of China on March 3-5 of 2007[J]. Meteorology, 2008, 34(4): 30-38. doi: 10.7519/j.issn.1000-0526.2008.04.004
    [12] 陈长胜,王盘兴,杨秀峰,等. 东北地区暴雪天气的统计学划分方法及其时空分布特征[J]. 地理科学,2012,32(10): 1275-1281.

    CHEN Changsheng, WANG Panxing, YANG Xiufeng, et al. Classification and features of spatio-temporal variation of snowstorms in northeast China[J]. Scientia Geographica Sinica, 2012, 32(10): 1275-1281.
    [13] 孟宪宏. 高寒地区公路雪害的预防与治理[J]. 中国科技信息,2016(5): 1-2.
    [14] 尹占娥. 自然灾害风险理论与方法研究[J]. 上海师范大学学报(自然科学版),2012,41(1): 99-103. doi: 10.3969/j.issn.1000-5137.2012.01.014

    YIN Zhan’e. Literature review of research on theory and method of natural disaster risk[J]. Journal of Shanghai Normal University (Natural Sciences), 2012, 41(1): 99-103. doi: 10.3969/j.issn.1000-5137.2012.01.014
    [15] 郭君,孔锋. 自然灾害概率风险历史资料的有效性及其检验[J]. 灾害学,2019,34(3): 21-26. doi: 10.3969/j.issn.1000-811X.2019.03.005

    GUO Jun, KONG Feng. Validity analysis of historical data for probabilistic risk analysis in natural disaster[J]. Journal of Catastrophology, 2019, 34(3): 21-26. doi: 10.3969/j.issn.1000-811X.2019.03.005
    [16] SAMANTA S, PAL D K, PALSAMANTA B. Flood susceptibility analysis through remote sensing,GIS and frequency ratio model[J]. Applied Water Science, 2018, 8(2): 65-78. doi: 10.1007/s13201-018-0711-0
    [17] 王中隆,张志忠. 中国风吹雪区划[J]. 山地学报,1999,17(4): 312-317.

    WANG Zhonglong, ZHANG Zhizhong. Regionalization of snow drift China[J]. Journal of Mountain Science, 1999, 17(4): 312-317.
    [18] 尹洪英,徐丽群. 道路交通网络脆弱性评估研究现状与展望[J]. 交通运输系统工程与信息,2010,10(3): 7-13. doi: 10.3969/j.issn.1009-6744.2010.03.002

    YIN Hongying, XU Liqun. Vulnerability assessment of transportation networks[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(3): 7-13. doi: 10.3969/j.issn.1009-6744.2010.03.002
    [19] JIANG Y Z, PENG J H, FENG W W. A review on the classification and grading criteria of road transport natural disasters[J]. Journal of Architectural Research and Development, 2018, 2(5): 10-12.
    [20] 秦军,曹云刚,秦娟. 汶川地震灾区道路损毁度遥感评估模型[J]. 西南交通大学学报,2010,45(5): 768-774. doi: 10.3969/j.issn.0258-2724.2010.05.019

    QIN Jun, CAO Yungang, QIN Juan. Evaluation model for damage extent of roads in wenchuan earthquake stricken areas based on remote sensing information[J]. Journal of Southwest Jiaotong University, 2010, 45(5): 768-774. doi: 10.3969/j.issn.0258-2724.2010.05.019
    [21] 李华蓉,郭敏,潘建平,等. 重庆市山区公路雪灾等级划分及预警评估模型研究[J]. 公路交通技术,2010(2): 27-30. doi: 10.3969/j.issn.1009-6477.2010.02.007

    LI Huarong, GUO Min, PAN Jianping, et al. Classification for snow disasters on expressways in mountainous area of Chongqing and research on warning evaluation model[J]. Technology of Highway and Transport, 2010(2): 27-30. doi: 10.3969/j.issn.1009-6477.2010.02.007
    [22] 孙梦婷,魏海,李星,等. 基于路况数据的城市道路交通事件点检测[J]. 地理与地理信息科学,2019,35(6): 9-14. doi: 10.3969/j.issn.1672-0504.2019.06.002

    SUN Mengting, WEI Hai, LI Xing, et al. Traffic incident point detection of urban road based on traffic data[J]. Geography and Geo-information Science, 2019, 35(6): 9-14. doi: 10.3969/j.issn.1672-0504.2019.06.002
    [23] 陈报章,仲崇庆. 自然灾害风险损失等级评估的初步研究[J]. 灾害学,2010,25(3): 1-5. doi: 10.3969/j.issn.1000-811X.2010.03.001

    CHEN Baozhang, ZHONG Chongqing. A preliminary study on risk loss degree assessment of natural hazards[J]. Journal of Catastrophology, 2010, 25(3): 1-5. doi: 10.3969/j.issn.1000-811X.2010.03.001
    [24] 李宁,张鹏. 全国减灾救灾标准解读系列四《自然灾害风险分级方法》解读[J]. 中国减灾,2015(11): 56-59.
    [25] 吴吉东,何鑫,王菜林,等. 自然灾害损失分类及评估研究评[J]. 灾害学,2018,33(4): 157-163. doi: 10.3969/j.issn.1000-811X.2018.04.026

    WU Jidong, HE Xin, WANG Cailin, et al. A review on classification and loss assessment of natural disasters[J]. Journal of Catastrophology, 2018, 33(4): 157-163. doi: 10.3969/j.issn.1000-811X.2018.04.026
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  • 收稿日期:  2019-12-17
  • 修回日期:  2020-06-12
  • 网络出版日期:  2020-07-07
  • 刊出日期:  2020-07-07

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