Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model
[Objective] The fuzziness and randomness of highway flood risk indicators, and transform highway flood risk evaluation indicators from qualitative descriptions to quantitative values were analyzed in order to improve highway flood risk prevention and control ability, to provide a scientific basis fo...
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| Format: | Article |
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Science Press
2022-06-01
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| Series: | Shuitu baochi tongbao |
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| Online Access: | http://stbctb.alljournal.com.cn/stbctben/article/abstract/20220321 |
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| author | Huang Qi Mou Fengyun Zhang Yongchuan Chen Lin Li Yunyan |
| author_facet | Huang Qi Mou Fengyun Zhang Yongchuan Chen Lin Li Yunyan |
| author_sort | Huang Qi |
| collection | DOAJ |
| description | [Objective] The fuzziness and randomness of highway flood risk indicators, and transform highway flood risk evaluation indicators from qualitative descriptions to quantitative values were analyzed in order to improve highway flood risk prevention and control ability, to provide a scientific basis for decision-making, and to reduce social and economic losses. [Methods] Twelve indicators from three criteria layers (namely, the risk of factors causing disasters, the sensitivity of disaster-pregnant environments, and the exposure of disaster-bearing bodies) were selected to construct a highway flood risk evaluation index system. Then the weight of each index was determined by the AHP-entropy weight method. Finally, a highway flood risk evaluation model was constructed based on an extension cloud model. The flood risk of highways in the central urban area of Chongqing City was divided into risk class Ⅰ to Ⅴ (very low, relatively low, average, relatively high, and very high). [Results] ① 69.62% of highways in the downtown area of Chongqing City had a flood risk of class Ⅰ to Ⅲ, and only 30.38% of highways had a flood risk of class Ⅳ to Ⅴ. Yuzhong District (64%), Banan District (47%), and Jiangbei District (41%) accounted for the highest proportion of high-risk highways, and these region's highways should be targeted for flood prevention and control. ② Yuzhong District (71.06%), Banan District (57.43%), and Jiangbei District (38.76%) had the longest length of high-risk highways, and flood prevention and control measures should be carried out for class Ⅳ and Ⅴ highways in the region. [Conclusion] The “two rivers and four banks” location and the surrounding areas were the most densely populated with high-risk highways, followed by major watersheds, lakes, and reservoirs. The water transportation system of the two rivers and the highway network system in the surrounding areas should be ensured and improved, the construction of hydrological stations and flood-control monitoring and early warning systems in major watersheds should be promoted, and the defense and emergency plans should be prepared. |
| format | Article |
| id | doaj-art-a466f8b9347541d5aa924f6dde1a1feb |
| institution | Kabale University |
| issn | 1000-288X |
| language | zho |
| publishDate | 2022-06-01 |
| publisher | Science Press |
| record_format | Article |
| series | Shuitu baochi tongbao |
| spelling | doaj-art-a466f8b9347541d5aa924f6dde1a1feb2024-12-27T10:27:57ZzhoScience PressShuitu baochi tongbao1000-288X2022-06-0142315716510.13961/j.cnki.stbctb.2022.03.0211000-288X(2022)03-0157-09Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud ModelHuang Qi0Mou Fengyun1Zhang Yongchuan2Chen Lin3Li Yunyan4Smart City Academy, Chongqing Jiaotong University, Chongqing 400074, ChinaSmart City Academy, Chongqing Jiaotong University, Chongqing 400074, ChinaSmart City Academy, Chongqing Jiaotong University, Chongqing 400074, ChinaChongqing Geographic Information and Remote Sensing Application Center, Chongqing 401147, ChinaKey Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing 400045, China[Objective] The fuzziness and randomness of highway flood risk indicators, and transform highway flood risk evaluation indicators from qualitative descriptions to quantitative values were analyzed in order to improve highway flood risk prevention and control ability, to provide a scientific basis for decision-making, and to reduce social and economic losses. [Methods] Twelve indicators from three criteria layers (namely, the risk of factors causing disasters, the sensitivity of disaster-pregnant environments, and the exposure of disaster-bearing bodies) were selected to construct a highway flood risk evaluation index system. Then the weight of each index was determined by the AHP-entropy weight method. Finally, a highway flood risk evaluation model was constructed based on an extension cloud model. The flood risk of highways in the central urban area of Chongqing City was divided into risk class Ⅰ to Ⅴ (very low, relatively low, average, relatively high, and very high). [Results] ① 69.62% of highways in the downtown area of Chongqing City had a flood risk of class Ⅰ to Ⅲ, and only 30.38% of highways had a flood risk of class Ⅳ to Ⅴ. Yuzhong District (64%), Banan District (47%), and Jiangbei District (41%) accounted for the highest proportion of high-risk highways, and these region's highways should be targeted for flood prevention and control. ② Yuzhong District (71.06%), Banan District (57.43%), and Jiangbei District (38.76%) had the longest length of high-risk highways, and flood prevention and control measures should be carried out for class Ⅳ and Ⅴ highways in the region. [Conclusion] The “two rivers and four banks” location and the surrounding areas were the most densely populated with high-risk highways, followed by major watersheds, lakes, and reservoirs. The water transportation system of the two rivers and the highway network system in the surrounding areas should be ensured and improved, the construction of hydrological stations and flood-control monitoring and early warning systems in major watersheds should be promoted, and the defense and emergency plans should be prepared.http://stbctb.alljournal.com.cn/stbctben/article/abstract/20220321extension cloud modelhighway floodingflood riskahp-entropy methodcentral chongqing city |
| spellingShingle | Huang Qi Mou Fengyun Zhang Yongchuan Chen Lin Li Yunyan Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model Shuitu baochi tongbao extension cloud model highway flooding flood risk ahp-entropy method central chongqing city |
| title | Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model |
| title_full | Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model |
| title_fullStr | Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model |
| title_full_unstemmed | Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model |
| title_short | Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model |
| title_sort | risk assessment of highway flood disaster in central chongqing city based on extension cloud model |
| topic | extension cloud model highway flooding flood risk ahp-entropy method central chongqing city |
| url | http://stbctb.alljournal.com.cn/stbctben/article/abstract/20220321 |
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