Liu Yonghong, Hu Haibo, Fang Xiaoyi, et al. Early warning and evaluating impacts of ice and snow disasters on Beijing urban transportation. J Appl Meteor Sci, 2013, 24(3): 373-379.
Citation: Liu Yonghong, Hu Haibo, Fang Xiaoyi, et al. Early warning and evaluating impacts of ice and snow disasters on Beijing urban transportation. J Appl Meteor Sci, 2013, 24(3): 373-379.

Early Warning and Evaluating Impacts of Ice and Snow Disasters on Beijing Urban Transportation

  • Received Date: 2012-03-26
  • Rev Recd Date: 2013-03-11
  • Publish Date: 2013-06-30
  • Using urban historical damage data of ice and snow from 1952 to 2011, the snow damage grades to Beijing urban transportation operation is built for the assessment on the accuracy of the following ice and snow warning and evaluation model. Based on disaster science principal combining with historical damage data, warning and evaluation indices of ice and snow damage to Beijing urban transportation operation are selected which are time, ice and snow intensity, traffic vulnerability, warning ability and disaster reduction ability. Ice and snow intensity can be determined by snowfall, snow depth and air temperature. Traffic vulnerability is determined by road network density and its time evolution. Warning ablility is mainly determined by weather forecast quality and its information spreading ability. Disaster reduction ability can be estimated by the gross domestic product and its time evolution. From the sensitive of these factors to snow disaster, method of experts marking is applied to computing and grades division of the single related factor and the comprehensive indices. Using judging-matrix of analytic hierarchy process (AHP) method, weights of four comprehensive evaluation indices are computed. Weights of four indices are ice and snow intensity with 0.4404, traffic vulnerability with 0.2789, disaster reduction ability with 0.1797, time with 0.05264 and warning ability with 0.0484, respectively. And Beijing urban ice and snow disaster warning and evaluation model is also constructed using AHP method. Using the model, 38 samples of historical ice and snow disaster events in Beijing are evaluated. The total accuracy is 76% and the accuracy in recent ten years (2002—2011) is 89% which shows the model can simulate effectively the impact of ice and snow disaster on Beijing urban area. The analysis of index weights shows that the hazard factor is still the major factor but not the only determinant factor of urban ice and snow disaster, as the total contribution of the other four factors to snow disaster overtakes the contribution of hazard factor. The ice and snow intensity as hazard factor affects Beijing urban transportation operation together with other factors under urbanization process such as transportation and disaster emergency management. The analysis of assessment on historical snow disaster events shows that under the influence of other factors, even light snow is able to cause serious damage on urban transportation operation and heavy snow perhaps only has medium effects.
  • Table  1  Snow damage grades to Beijing urban transportation operation

    等级 含义 表现 满足条件 典型冰雪灾害事件
    1 轻微或无 市区局部路段出现车辆排队等候现象 陆面交通堵塞有所增加或影响不大,航班取消和延误5%班次以下 2004-12-16小雪, 2002-12-15小雪
    2 一般 市区部分路段出现车辆排队等候现象,机场、火车站出现轻微旅客滞留现象 陆面交通堵塞明显增加,多条公交停驶、绕行,且航班取消和延误占当天班次5%以上 2010-02-06—07小雪, 2011-02-26—27大雪
    3 较严重 市区主要道路出现车辆排队等候现象,交通堵塞明显,机场、火车站出现旅客滞留现象 交通指数[19]为8.5以上,且交通事故明显或40%以上高速公路国道关闭,且航班取消和延误占当天班次40%以上 1998-01-13—16小雪, 2009-11-12大雪
    4 严重 市区大部分道路出现车辆排队等候现象,机场、火车站出现严重旅客滞留现象,进京货物车辆大量减少 交通指数为9.0以上,交通事故显著增加;或80%以上高速公路或国道关闭,且航班取消和延误班次占当天80%以上 1966-02-20—22暴雪, 1998-11-21—22大雪
    5 非常严重 市区主要道路不具备车辆正常通行条件,城市交通几乎瘫痪 交通指数9.5以上,且持续时间5 h以上;或大部分高速公路或国道关闭,且机场关闭2 d以上 2001-12-07小雪
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    Table  2  Evaluation marks of snow damage occurence time

    敏感程度 发生时间 评分值
    轻微 20:00—次日06:00 1
    节假日白天及周末白天 3
    工作日白天 5
    较高 长假第1天和结束前1天, 晚高峰 7
    很高 早高峰, 周五下午及20:00前 9
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    Table  3  Evaluation marks of snowfall, snow depth, average air temperature and ice and snow intensity

    敏感程度 P/mm P评分 H/cm H评分 Ta/℃ Ta评分 IS IS评分
    0 0 0 0 > 2.0 0 0 0
    轻微 0.1~0.9 1 0.1~1.0 1 0.1~2.0 1 0.01~1.50 1
    1.0~2.4 3 1.1~3.0 3 -1.9~0 3 1.51~3.50 3
    2.5~4.9 5 3.1~5.0 5 -6.9~-2.0 5 3.51~5.50 5
    较高 5.0~9.9 7 5.1~8.0 7 -14.9~-7.0 7 5.51~7.25 7
    10.0~30.0 8 8.1~18.0 8 -28.0~-15.0 8 7.26~8.25 8
    很高 > 30.0 9 > 18.0 9 < -28.0 9 > 8.25 9
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    Table  4  Evaluation marks of transportation development coefficient and traffic vulnerability

    敏感程度 时段 CT评分 VT VT评分
    轻微 1983-12以前 0.2 < 0.20 1
    1984-01—1995-12 0.4 0.20~0.40 3
    1996-01—2002-12 0.6 0.41~0.60 5
    较高 2003-01—2007-02 0.8 0.61~0.80 7
    很高 2007-03至今 1.0 > 0.80 9
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    Table  5  Evaluation marks of prediction and warning quality, information spread capability and warning capability

    敏感程度 Q Q评分 时段 I评分 W W评分
    轻微 提前24 h以上冰雪及量级预报预警 1 2009-09至今 1 ≤1.80 1
    提前12 h以上冰雪预报预警或与预报降雪量差1个等级以下 3 2003-04—2009-08 3 1.81~3.80 3
    12 h前漏报平原雪而降雪量达小雪或与预报降雪量差2个等级 5 1995-01—2003-03 5 3.81~5.80 5
    较高 6 h前漏报平原雪而降雪量达中雪或与预报降雪量差3个等级 7 1985-01—1994-12 7 5.81~7.80 7
    很高 6 h前漏报雪而降雪量达大雪以上量级 9 1984-12以前 9 > 7.80 9
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    Table  6  Evaluation marks of current disaster reduction index, disaster reduction development coefficient and disaster reduction ability

    敏感程度 D0 D0评分 时段 Rd评分 DR DR评分
    轻微 > 100000 0.9 ≤0.10 1
    很低 50001~100000 0.8 1993-12以前 0.2 0.11~0.20 2
    10001~50000 0.6 1994-01—2001-12 0.4 0.21~0.40 3
    2001~10000 0.4 2002-01—2004-11 0.6 0.41~0.60 5
    较高 500~2000 0.2 2004-12— 2010-10 0.8 0.61~0.80 7
    很高 < 500 0.1 2010-11至今 1.0 > 0.80 9
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    Table  7  Snow damage warning and evaluation grades

    影响等级 A 评估等级
    轻微或无 < 4.00 1
    一般 4.00~5.50 2
    较严重 5.51~6.50 3
    严重 6.51~7.50 4
    非常严重 > 7.50 5
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    Table  8  Comparsion between model evaluation result and actual evaluation result of different snow damage events

    小雪 中雪 大雪 暴雪
    时间 评估等级 时间 评估等级 时间 评估等级 时间 评估等级
    模型 实际 模型 实际 模型 实际 模型 实际
    2010-02-06—07 2 2 2011-12-02 2 2 2011-02-26—27 2 2 2010-03-14—15 3 3
    2007-12-10 2 2 2011-02-13 3 2 2009-11-12 3 3 2010-01-02—03 3 3
    2004-12-16 1 1 2011-02-10 2 2 2009-02-17—19 3 3 2009-11-09—10 3 3
    2002-12-15 1 1 2006-12-30—31 2 2 2002-12-19—24 3 3 2009-10-30—11-01 3 3
    2001-12-07 2 5 2004-12-22—24 3 3 2001-01-05—08 3 4 2005-02-15—18 3 3
    1998-01-13—16 3 3 2000-01-11—12 3 3 1998-11-21—22 4 4 2003-11-05—07 4 3
    1994-02-11 1 1 2000-01-03—05 3 3 1997-12-05—06 3 3 1979-02-22—23 3 3
    1991-11-26—27 1 2 1997-01-03—04 3 2 1989-01-05—06 3 4 1966-02-20—22 3 3
    1996-12-31—1997-01-01 2 2 1959-02-24—26 3 4
    1994-02-14—15 2 2
    1993-11-19 3 2
    1986-02-17 2 2
    1952-12-18—19 3 3
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    • Received : 2012-03-26
    • Accepted : 2013-03-11
    • Published : 2013-06-30

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