长江流域资源与环境 >> 2013, Vol. 22 >> Issue (06): 801-.

• 自然灾害 • 上一篇    下一篇

江浙沪地区历史重大洪涝灾害情景下的人口和GDP物理暴露量分析

黄红铸 ||崔玉娟 |叶 瑜 ||方修琦   

  1. (1.北京师范大学地理学与遥感科学学院|北京 100875; 2.教育部环境演变与自然灾害重点实验室|北京 100101
  • 出版日期:2013-06-20

EXPOSURE OF GDP AND POPULATION UNDER THE SCENARIOS OF HISTORICAL EXTREME FLOOD YEARS IN JIANGSUZHEJIANGSHANGHAI AREA

HUANG Hongzhu1| CUI Yujuan1| YE Yu1|2|FANG Xiuqi1   

  1. (1.School of Geography,Beijing Normal University,Beijing 100875,China|2.Key Laboratory of Environment Change and Natural Disaster,Ministry of Education,Beijing 100101,China
  • Online:2013-06-20

摘要:

利用江浙沪地区1644~1949年洪涝灾害数据库,基于年受灾县次,对该地区历史重大洪涝灾害年进行了辨识,并以历史重大洪涝灾害为情景,对其重现于2010年的人口和GDP物理暴露量进行分析,得到以下结论:(1)按受灾县次划分,1644~1949年江浙沪地区重大洪涝灾害频率在50~100年一遇的为1670年、1683年、1804年;100~300年一遇的为1823年、1849年;300年一遇的为1931年;(2)重大洪涝灾害暴露区主要集中于长江三角洲地区;(3)6次重大洪涝灾害情景下,人口物理暴露量基本超过2010年该区人口总量的40%,而GDP物理暴露量则几乎超过了其总量的50%;(4)江苏受灾最为明显,上海受灾幅度波动最大,尤其是在100年一遇洪涝灾害前后受灾影响差距很大,浙江受灾影响相对稳定;(5)该区人口、GDP物理暴露量并不一定与受灾县次呈典型的正相关关系,可能与其人口、经济分布格局等因素有关

Abstract:

The research of flood disasters in history could provide analogies for better understanding the mechanism and impacts of the current and future floods.Today the research of historical flood is playing a more and more important role in the risk assessment and prediction.During the recent 300 years,there were lots of floods in China,especially in the southeast China,which can be given evidences by lots of historical documents before the instrumental meteorological observation.It can help to make sure the advantage of doing research on historical floods in China.This paper selected Jiangsu,Zhejiang,Shanghai provinces as the study area and constructed the historical floods database from 1644 to 1949AD according to historical document.The historical extreme flood years were identified according to the statistic analysis of annual floods counties.Then the paper analyzed the exposure of population and GDP of this area in 2010 under the scenarios of these historical extreme floods years without caring about the changes of the characters of hazardaffected bodies and margin of exposure.Results are as follow.(1) The worsthit year in recent 300 years in JiangsuZhejiangShanghai area was 1931AD,and the frequency of this flood was once in 300 years,which involved about eightysix counties.The worsehit years were 1823 and 1849AD and their frequency were between once in 100 years and once in 300 years,which involved about eighty counties.In 1670,1683,1804AD,the frequency were between once in 50 years and once in 100 years,which involved about sixty to seventy counties.(2) The paper recovered the spatial distribution of these historical extreme floods through the GIS tool and statistics.It is found that disastrous areas were mainly distributed in the Yangtze River Delta Area,including shanghai,the southern Jiangsu and northern Zhejiang.(3) It calculated the exposure of GDP and population in JiangsuZhejiangShanghai area in 2010 under the scenario of these extreme floods,it is found that if these extreme floods happened in 2010,JiangsuZhejiangShanghai area was relatively vulnerable and suffered great losses.The percentage of GDP and population's exposure almost accounted for more than 40% of the total,especially GDP exposure had risen to 50% of the total GDP.(4) The extreme floods had different impacts in different disastrous areas.Jiangsu was relatively suffering more than others.The fluctuation of disasters impacts in Shanghai was bigger than that in Jiangsu and Zhejiang,especially when the frequency were between once in 100 years and 300 year;the exposure was obviously larger than those years that the frequency were between once in 50 years and 100 years.Shanghai should be more vulnerable and cautious about the extreme floods with frequency of once in more than 100 years.Zhejiang exposure in these extreme floods scenarios was relatively little fluctuant.Zhejiang was less sensitive to the flood than Jiangsu and Shanghai.(5) There was no significant correlation between the exposure of the population and GDP and the number of disastrous counties.Higher exposure doesn't mean larger disastrous spatial distribution,because of the economic and population's unbalanced growth

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