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当前位置: 首页 > 文章 > 北京市通州区暴雨特征及风险评估研究 安徽农业科学 2015 (27) 167-171
Position: Home > Articles > Characteristics of Rainstorm and Its Disaster Risk Assessment in Tongzhou District,Beijing Journal of Anhui Agricultural Sciences 2015 (27) 167-171

北京市通州区暴雨特征及风险评估研究

作  者：
高晓容;张继权;李硕;王翌
单  位：
东北师范大学城市与环境科学学院;北京市通州区气象局
关键词：
暴雨;时空分布;风险评估;通州区;北京市
摘  要：
利用近60年气候资料分析北京市通州区暴雨的时空分布特征。另外,以15个乡镇(街道)为风险评估单元,以人口和社会经济作为承灾体,根据联合国人道主义事务部的风险表达式,利用自然灾害风险指数法建立暴雨风险评估模型;利用指标体系法评估承灾体的脆弱性状态,根据加权综合评分法建立脆弱性评估模型;分析15个乡镇(街道)孕灾环境和致灾因子的危险性、承灾体的脆弱性及灾害风险的差异,并对通州区暴雨灾害风险进行区划,结果表明,通州暴雨洪涝灾害风险高值区在中仓、新华街道及马驹桥镇,较高值区在北苑、玉桥街道及宋庄、永顺、西集、漷县、于家务乡(镇)。
译  名：
Characteristics of Rainstorm and Its Disaster Risk Assessment in Tongzhou District,Beijing
作  者：
GAO Xiao-rong;ZHANG Ji-quan;LI Shuo;Tongzhou Branch of Beijing Meteorological Service;Institute of Natural Disaster Research,College of Urban and Environmental Sciences,Northeast Normal University;
关键词：
Rainstorm;;Spatial-temporal distribution;;Risk assessment;;Tongzhou District;;Beijing
摘  要：
The climate data in the last 60 years is used in this paper to analyze the spatial-temporal distribution of rainstorms in Tongzhou District,Beijing. With 15 countryside towns( streets) as risk assessment units and population and social economy as the hazard-affected bodies,a risk assessment model of rainstorm disaster is established by using the natural disaster risk index method and the risk expression of UN Office for the Coordination of Humanitarian Affairs. The index system method is adopted to assess the vulnerability of disaster-affected bodies and synthetic weighted marking is used to establish the vulnerability assessment model. The hazard of disaster-breeding environment and disaster-causing factors,vulnerability of disaster-affected bodies and differences among disaster risk at 15 countryside towns( streets) are analyzed,and the rainstorm disaster risk in Tongzhou District is also zoned. The results show that Zhongcang,Xinhua Street and Majuqiao Town are at high risk of rainstorm flood disaster,and Beiyuan,Yuqiao Street,Songzhuang,Yongshun,Xiji,Huoxian and Yujiawu Town are at relatively high risk.

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