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 ›› 2018, Vol. 34 ›› Issue (4): 98-104.doi: 10.3969/j.issn.1673-503X.2018.04.013

• 论文 • 上一篇    下一篇

降水引发的中国公路损毁灾害时空变化特征

王志1  田华1  狄靖月2  许凤雯2   

  1. 1. 中国气象局公共气象服务中心,北京 100081;2. 国家气象中心,北京 100081
  • 收稿日期:2017-03-14 修回日期:2017-11-27 出版日期:2018-08-31 发布日期:2018-09-03

Research on the tempo-spatial characteristics of road damage induced by precipitation

WANG Zhi1  TIAN Hua1  DI Jing-yue2  XU Feng-wen2   

  1. 1. Public Meteorological Service Center, China Meteorological Administration, Beijing 100081, China; 2. National Meteorological Center, Beijing 100081, China
  • Received:2017-03-14 Revised:2017-11-27 Online:2018-08-31 Published:2018-09-03

摘要:

本文基于全国干线公路灾情资料分析了降水引发公路损毁灾害的时间与空间分布特征,并对诱发公路损毁灾害的高程、坡度、高程差、断层密度、工程岩组等环境因子及最大小时雨强、强降雨发生频次、强降雨持续时间等降水因子采用信息量法进行了分析对比。结果表明:坡度、强降雨持续时间、高程差、断层密度、强降雨发生频次等因子对公路损毁灾害发生的影响作用最大。依据综合信息量将全国干线公路损毁灾害危险性划分为极高、高、较高、低和极低5个等级。经过检验,采用信息量法划分公路损毁灾害危险性等级能较好地反映公路损毁灾害的潜在空间分布,本文研究结果可以为公路损毁灾害预报预报及工程建设提供参考。

关键词: 公路损毁, 降水, 危险性, 信息量模型

Abstract:

Based on the national trunk road disaster data, the tempo-spatial distribution characteristics of road damages induced by precipitation were analyzed. According to the information value method, the environmental factors (elevation, slope, relief, fault density, and lithology) and the precipitation factors (maximum hourly rain intensity, intensive rainfall frequency, and intensive rainfall duration) were analyzed and compared. The results show that the factors such as slope, intensive rainfall duration, relief, fault density and intensive rainfall frequency have the greatest effect on road damage. According to the comprehensive information value of the national trunk, road damage disaster risk is divided into five grades. It is tested that the risk classification can express the potential spatial distribution of the disaster. The study can supply a reference to road damage prevention, risk forecasting and road construction.

Key words: Road damages, Tempo-spatial distribution, Hazard, Information value model

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