地理学报 ›› 2018, Vol. 73 ›› Issue (3): 405-413.doi: 10.11821/dlxb201803002

• 气候变化 • 上一篇    下一篇

基于情景的1951-2011年中国极端降水风险评估

尹占娥,田鹏飞,迟潇潇   

  1. 上海师范大学旅游学院地理系,上海 200234
  • 收稿日期:2017-06-28 出版日期:2018-03-20 发布日期:2018-03-23
  • 基金资助:
    国家自然科学基金项目(41371493) [Foundation: National Natural Science Foundation of China, No.41371493]

Multi-scenario-based risk analysis of precipitation extremes in China during the past 60 years (1951-2011)

YIN Zhan'e,TIAN Pengfei,CHI Xiaoxiao   

  1. Department of Geography, Shanghai Normal University, Shanghai 200234, China
  • Received:2017-06-28 Online:2018-03-20 Published:2018-03-23

摘要:

随着全球气候变暖,极端降水的风险评估研究成为学界和各国政府广泛关注的热点问题,开展中国极端降水的风险评估研究可以为中国防灾减灾提供参考依据。本文从灾害风险评估视角,依据国际减灾战略(ISDR)的灾害风险评估模型,开展了中国极端降水的风险评估研究。首先,利用1951-2011年全国各站点逐日降水数据,采用Pearson-III方法,模拟不同重现期情景下极端降水量和频次分布,评估中国不同重现期下的极端降水危险性及空间分布;其次,基于人口和GDP指标,分析极端降水脆弱性及空间分布特征;在此基础上,评估了5年、10年、50年、100年一遇情景下中国极端降水风险及其空间分布特征。结果表明:① 中国极端降水危险性等级从东南沿海向西北内陆递减,5年一遇情景下,极端降水高危险区和低危险区的分界线大致与400 mm等降水线相同。② 中国极端降水脆弱性高的地区主要分布在人口稠密且经济发达的东部沿海大城市地区,特别是经济发达的长三角、珠三角和京津冀等城市群地区,以及中部地区的一些大城市。③ 不同情景下,中国极端降水风险等级均呈现由东南向西北方向降低。风险等级高和较高的地区主要位于黑河—腾冲线以东,中和低风险区位于该线以西,这与中国人口密度分布的胡焕庸线大体一致。

关键词: 极端降水, 风险评估, 危险性分析, 脆弱性分析, 中国

Abstract:

Precipitation extremes are expected to become more frequent and intense under global warming in the coming decades. Risk analysis of precipitation extremes has become a hot issue in academic circles and governments. In this paper, we use the data recorded at 756 meteorological stations from 1951 to 2011. Data were first processed to generate a coherent set of precipitation datasets. Pearson-III frequency analysis method was used to define the thresholds of different rainfall return periods. We chose total extreme precipitation amount and extreme precipitation frequency as indices, and scenarios with return periods of 5, 10, 50 and 100 years were designed to analyze precipitation extremes. The vulnerability of economy and population to precipitation extremes was analyzed. Precipitation extremes and the associated vulnerability were evaluated using the risk assessment model of ISDR to assess the risk pattern of precipitation extremes in China, mapping the risk distribution of precipitation extremes under different return periods in China during the past 60 years (1951-2011). Results show that: (1) the magnitude of extreme precipitation decreases from the southeastern coastal areas to the northwestern inlands. The high-risk areas of extreme precipitation in the 5-year scenario are mainly located in southeastern coastal China. The boundary between high-risk and low-risk areas nearly coincides with the isohyet of 400 mm; (2) China's extreme precipitation is mainly observed in densely populated and economically developed eastern coastal metropolitan areas, especially in Yangtze River Delta urban agglomeration, Pearl River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration and several large cities in the western region of China. The western region of the country, which is resource-scarce and economically less developed, is associated with lower-risk precipitation extremes; (3) under each return period, the extreme precipitation risk level decreases from southeastern coastal areas to northwestern inland areas. The high-risk level areas are distributed in South China, southeastern coastal China, middle and lower reaches of the Yangtze River, Huang-Huai-Hai Plain, Bohai Rim and Sichuan Basin. The areas with high risk are mainly distributed to the east of the Heihe-Tengchong Line (Hu Line), and the medium and low risk areas are located to the west of the Hu Line, which is roughly consistent with the Hu Line of population density distribution in China. This research presents a novel approach to evaluating national-scale precipitation extremes and the associated socio-economic risks. Findings obtained herein can be used as scientific references for governments at all levels in disaster prevention and reduction of extreme precipitation in China.

Key words: precipitation extremes, risk assessment, hazard analysis, vulnerability analysis, China