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Urban waterlogging risk assessment of 7.20 heavy rainfall in Kaifeng City
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摘要: 河南7.20特大暴雨由于降雨强度大、历时长、洪灾多发引起了广泛关注，特大暴雨导致郑州、开封等城市出现严重内涝。针对城市内涝风险评估问题，对开封市12个自动内涝监测站点数据进行筛选和分析，构建了由短期风险、长期风险2个维度9个影响因子组成的半结构多层次多目标指标体系，在输入层采用信息熵权向量，在准则层对短期风险、长期风险2个子系统采用熵值权向量、对等权向量、决策偏好权向量3种赋权方法，构成改进风险模糊评价模型。对12个站点的内涝风险进行5个级别（极高、较高、中等、较低、极低）的评估。结果显示：在短期风险评估中，5号站点为极高风险，10号站点为中等风险；在长期风险评估中，6号站点为较高风险，8号站点为极低风险；在目标层的最终评价中，3种方法均显示5号、2号站点风险极高，7号、8号站点风险较低。经过与开封市内涝实际情况对比，认为评价体系和改进模型具有较强的适用性，针对城市内涝风险能够给出短期风险、长期风险、综合风险精准的评估结果，为城市进行排水管网完善、内涝积水点防治等提供可靠的数据支持，为应对暴雨引发的内涝问题制定应急减灾预案和应对措施提供依据。Abstract: On July 20, 2021, the heavy rain in Henan Province attracted wide attention due to its heavy rainfall intensity, long duration and frequent floods. The heavy rain caused serious waterlogging in Zhengzhou, Kaifeng and other cities. Aiming at the problem of urban waterlogging risk assessment, the data of 12 automatic monitoring stations were screened, and a semi-structural index system consisting of two dimensions of short-term risk and long-term risk and nine influencing factors was constructed. In the input layer, information entropy weight vector was adopted, and in the criterion layer, three weighting methods were adopted: entropy weight vector, equal weight vector and decision preference weight vector, which constitute the improved risk fuzzy evaluation model. Waterlogging risk was assessed at five levels (very high, high, medium, low, and very low) for 12 sites. The results show that: in the short-term risk assessment, site 5 means very high risk, and site 10 is medium risk. In the long-term risk assessment, site 6 is high risk, and site 8 is very low risk. In the final evaluation of the target layer, the three methods all show that the risk of No. 5 and No. 2 sites is very high, and the risk of No. 7 and No. 8 sites is low. Compared with the actual situation of waterlogging in Kaifeng City, the evaluation system and improved model are considered to have strong applicability. Accurate evaluation results of short-term risk, long-term risk and comprehensive risk can be provided for urban waterlogging risk, providing reliable data support for urban drainage pipe network improvement and waterlogging prevention and control. It provides a basis for making emergency disaster reduction plan and countermeasures to deal with waterlogging caused by rainstorm.
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Key words:
- heavy rain /
- urban waterlogging /
- risk assessment /
- Kaifeng City of Henan Province
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图 1 开封市7.20特大暴雨降水过程（56 h）
Figure 1. Precipitation process of 7.20 heavy rainstorm in Kaifeng City (56 hours)
图 2 研究区域内涝积水监测站点分布
Figure 2. Distribution of urban waterlogging monitoring points in research area
图 3 开封市城市内涝风险3种方法评价对比
Figure 3. Comparison of urban waterlogging risk evaluation by three methods in Kaifeng City
图 4 开封市7.20特大暴雨12个站点内涝过程（56 h） (单位： mm)
Figure 4. Waterlogging process at 12 stations of 7.20 heavy rain in Kaifeng City (56 hours) (unit: mm)
表 1 开封市积水内涝自动监测站点位置
Table 1. Location of automatic monitoring points of waterlogging in Kaifeng City
编号 地理位置 经度/° 纬度/° 对应气象站 备注 1 市国家气象站 34.803 150 114.295 080 A站 老城区城墙外 2 汴京路与劳动路交叉口 34.793 738 114.373 899 G站 老城区城墙外 3 大庆路与滨河路交叉口 34.785 541 114.324 634 G站 老城区城墙外 4 东环路与苹果园中路口 34.809 161 114.368 118 F站 老城区城墙外 5 复兴大道西段 34.832 763 114.320 652 B站 老城区城墙外 6 复兴大道与东环北路交叉口 34.828 897 114.371 634 F站 老城区城墙外 7 解放路与自由路交叉口 34.789 262 114.353 777 G站 老城区城墙内 8 劳动路与新曹路交叉口 34.801 004 114.374 269 G站 老城区城墙外 9 市第三职业高中大门对面 34.784 870 114.346 056 E站 老城区城墙内 10 东京大道与西环北路交叉口 34.821 567 114.323 614 C站 老城区城墙外 11 西环城路与向阳路交叉口 34.795 028 114.324 342 D站 老城区城墙外 12 滨河路公园路交叉口 34.779 660 114.367 694 G站 老城区城墙外 
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表 2 7.20特大暴雨开封市内涝风险评估指标数据
Table 2. Waterlogging risk assessment index data of 7.20 heavy rainstorm in Kaifeng City
风险
因素指标 代码 1 2 3 4 5 6 7 8 9 10 11 12 短期
风险
（4）最大积水深度/cm xn1 75 83 76 51 104 90 18 56 37 6 38 68 平均积水深度/cm xn2 16.25 55.54 34.98 24.81 60.44 44.59 3.10 46.80 14.25 4.01 11.05 15.61 最大积水深度
出现时间/minxn3 30 76 210 90 60 86 6 674 278 202 44 44 积水面积 xn4 中等 较大 较大 中等 最大 较大 较小 中等 最小 中等 中等 较大 长期风险
（5）积水累计时间/h xa1 38.0 41.5 41.5 39.0 35.5 41.5 10.0 5.0 37.5 40.5 40.0 19.0 积水深度10~25 cm
累计时长/minxa2 236 0 156 1030 80 450 78 0 294 0 368 86 积水深度26~50 cm
累计时长/minxa3 436 718 546 954 266 532 0 242 682 0 506 324 积水深度51~80 cm
累计时长/minxa4 238 1692 940 48 402 746 0 110 0 0 0 58 积水深度81~120 cm
累计时长/minxa5 0 60 0 0 880 348 0 0 0 0 0 0
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表 3 短期风险、长期风险子系统的熵值和权值
Table 3. Entropy value and weight vector of short-term and long-term risk subsystem
指标 xn1 xn2 xn3 xn4 xa1 xa2 xa3 xa4 xa5 熵值 0.992 0.990 0.992 0.993 0.986 0.995 0.993 0.994 0.995 权值 0.234 0.293 0.254 0.219 0.371 0.139 0.184 0.163 0.143
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表 4 开封市内涝风险评估12个站点的级别特征值
Table 4. Level characteristic values of 12 stations for waterlogging risk assessment in Kaifeng City
子系统权向量 级别特征值 1 2 3 4 5 6 7 8 9 10 11 12 熵值权向量
w=(0.381，0.619)3.759 4.595 4.215 3.851 4.810 4.465 1.591 1.598 3.386 3.248 3.712 3.011 对等权向量
w=(0.500，0.500)3.443 4.332 3.976 3.514 4.844 4.164 1.708 1.879 2.954 2.830 3.440 2.998 决策偏好权向量
w=(0.600，0.400)3.166 4.151 3.872 3.233 4.870 3.993 1.794 2.031 2.607 2.490 3.200 2.991
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表 5 开封市内涝风险评估12个站点综合评价结果
Table 5. Comprehensive evaluation results of waterlogging risk assessment of 12 stations in Kaifeng City
评价方法 综合风险评估值及级别 1 2 3 4 5 6 7 8 9 10 11 12 熵值权向量法 0.752 0.919 0.843 0.770 0.962 0.893 0.177 0.179 0.677 0.650 0.742 0.602 评价级别 Ⅳ
较高Ⅴ
极高Ⅳ
较高Ⅳ
较高Ⅴ
极高Ⅳ
较高Ⅱ
较低Ⅱ
较低Ⅳ
较高Ⅳ
较高Ⅳ
较高Ⅳ
较高对等权向量法 0.689 0.866 0.795 0.703 0.969 0.833 0.212 0.264 0.586 0.549 0.688 0.599 评价级别 Ⅳ
较高Ⅴ
极高Ⅳ
较高Ⅳ
较高Ⅴ
极高Ⅳ
较高Ⅱ
较低Ⅱ
较低Ⅲ
中等Ⅲ
中等Ⅳ
较高Ⅲ
中等决策偏好权向量法 0.633 0.830 0.774 0.647 0.974 0.799 0.238 0.309 0.482 0.447 0.640 0.597 评价级别 Ⅳ
较高Ⅳ
较高Ⅳ
较高Ⅳ
较高Ⅴ
极高Ⅳ
较高Ⅱ
较低Ⅱ
较低Ⅲ
中等Ⅲ
中等Ⅳ
较高Ⅲ
中等
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