期刊文献+

基于可拓云模型的重庆市中心城区公路洪灾风险评价 被引量:2

Risk Assessment of Highway Flood Disaster in Central Chongqing City Based on Extension Cloud Model
下载PDF
导出
摘要 [目的]分析公路洪灾风险指标存在的模糊性和随机性,以及公路洪灾风险评价指标由定性描述转化为定量表达的问题,为提高公路洪灾风险防控能力提供科学决策依据,降低社会经济损失。[方法]首先从致灾因子危险性、孕灾环境敏感性、承灾体暴露性3个准则层出发选取12项指标,构建公路洪灾风险评价指标体系,其次利用AHP-熵权法确定各指标权重,最后基于可拓云模型构建了公路洪灾风险评价模型,将重庆市中心城区公路洪灾风险等级划分为Ⅰ—Ⅴ级(非常低、比较低、一般、比较高和非常高)。[结果](1)重庆市中心城区69.52%的公路洪灾风险为Ⅰ—Ⅲ级,仅30.38%的公路为Ⅳ—Ⅴ级;渝中区(64%)、巴南区(47%)和江北区(41%)高风险公路比例最高,应针对全区公路进行总体防控;(2)渝中区(71.06%)、巴南区(57.43%)和江北区(38.76%)的高风险公路长度最长,应针对区内Ⅳ—Ⅴ级公路进行防控。[结论]“两江四岸”及周边地区高风险公路最为密集,各大流域、湖泊及水库附近为次密集。应保障及完善两江水上交通系统及周边地区路网体系,同时推进各大流域水文站及防汛监测预警系统建设,编制防御及应急预案等。 [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.
作者 黄淇 牟凤云 张用川 陈林 李云燕 Huang Qi;Mou Fengyun;Zhang Yongchuan;Chen Lin;Li Yunyan(Smart City Academy,Chongqing Jiaotong University,Chongqing 400074,China;Chongqing Geographic Information and Remote Sensing Application Center,Chongqing 401147,China;Key Laboratory of New Technology for Construction of Cities in Mountain Area,Ministry of Education,Chongqing University,Chongqing 400045,China)
出处 《水土保持通报》 CSCD 北大核心 2022年第3期157-165,共9页 Bulletin of Soil and Water Conservation
基金 山地城镇建设与新技术教育部重点实验室开放基金“重庆市中心城区城市公路网络抗灾韧性评估研究”(LNTCCMA-20220112) 国家重点研计划项目(2019YFB2102500) 重庆交通大学研究生科研创新项目(CYS21362)。
关键词 可拓云模型 公路洪灾 洪灾风险 AHP-熵权法 重庆市中心城区 extension cloud model highway flooding flood risk AHP-entropy method Central Chongqing City
  • 相关文献

参考文献12

二级参考文献196

共引文献629

同被引文献21

引证文献2

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部