主办单位：中国气象局沈阳大气环境研究所
国际刊号：ISSN 1673-503X
国内刊号：CN 21-1531/P
气象与环境学报

气象与环境学报 ›› 2014, Vol. 30 ›› Issue (5): 141-145.doi:

• 简报 • 上一篇    下一篇

吉林省重大暴雨过程影响损失评估模型的建立

袭祝香1 纪玲玲1 张硕2   

  1. 1. 吉林省气象台，吉林 长春 130062；2. 辽宁省气象灾害监测预警中心，辽宁 沈阳 110166
  • 出版日期:2014-11-01 发布日期:2014-11-01

Development of a model for evaluation of disaster loss due to heavy rainstorm in Jilin province

XI Zhu-xiang1  JI Ling-ling1  ZHANG Shuo2   

  1. 1. Jilin Meteorological Observatory ,Changchun 130062, China; 2. Liaoning Meteorological Disaster Monitoring and Warning Center, Shenyang 110166, China
  • Online:2014-11-01 Published:2014-11-01

PDF (PC)

279

被引次数

3

摘要：

利用1961—2012年吉林省逐日降水资料、暴雨灾情资料、逐年GDP和人口资料采用灰色关联度分析方法建立重大暴雨过程指数及灾损指数，利用相关分析法对重大暴雨过程造成损失的影响因素进行探讨，采用多元回归法建立重大暴雨过程影响损失评估模型，并进行拟合和试评估检验。结果表明：吉林省重大暴雨过程造成的损失与前7 d雨量及重大暴雨过程指数相关显著；利用前7 d雨量和重大暴雨过程指数建立的影响损失评估模型拟合和试评估效果均较好，可在实际业务中应用；由于在重大暴雨过程发生前，评估因子就可获得，因此，可以对其灾害损失进行定量预评估，在实际业务中指导意义较大。

关键词: 重大暴雨过程, 影响损失, 评估模型

Abstract:

Based on daily precipitation data, rainstorm disaster data, annual GDP data and population data from 1961 to 2012 in Jilin province, a heavy rainstorm process index and a disaster loss index were established by a grey correlative degree analysis method. The influence factors of loss caused by the heavy rainstorm process were discussed using a correlation analysis method. A loss evaluation model of heavy rainstorm was established by a multivariate regression method, and its fitting and evaluate test were carried out. The results show that losses caused by the heavy rainstorm process in Jilin province have significant correlations with rainfall during the previous 7 days of the heavy rain and the heavy rainstorm process index. The above two factors are used to establish a loss evaluation model of heavy rain, and it has better effect of fitting and evaluation test. Thus, this model can be applied in operational business. The evaluation factors could be obtained before a heavy rain occurs, so disaster loss could be predicted in advance, which is important for operational business.

Key words: Heavy rainstorm process, Impact loss, Evaluation model