Distribution Characteristics and Hazard Analysis of Mountain Torrent Disaster in Guangdong Province, China
- DOI
- 10.2991/rac-18.2018.41How to use a DOI?
- Keywords
- mountain torrent disaster, distribution characteristics, contribution rate, hazard assessment, Guangdong province
- Abstract
Based on the mountain torrent disaster data, a GIS database was established to analyze the distribution characteristics of mountain torrent disasters in Guangdong province, China. Factors such as lithology, slope, elevation, aspect, slope pattern, and distance to river networks were selected to assess hazard degree by a method of factor contribution rate. It is found that the mountain torrent disaster was mainly the medium-sized scale. The Hanjiang River basin has the most disaster and Chaozhou City has the largest disaster distribution density. The Jurassic strata, slope from 10 to 20°, elevation from 300 to 400 m, sunny slope, linear slope pattern, and distance to river networks less than 5 km have the largest factor contribution rate which are the most prone areas to mountain torrent disasters. The calculated hazard index is between 0.0189 and 0.2592. The hazard zones can be divided into five zones: safety, low, middle, high and higher zones. The result can provide a basis for mountain torrent disaster mitigation of Guangdong province, China.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jun Wang AU - Qinghau Gong AU - Shaoxiong Yuan AU - Haixian Xiong AU - Xiaoling Yin PY - 2018/10 DA - 2018/10 TI - Distribution Characteristics and Hazard Analysis of Mountain Torrent Disaster in Guangdong Province, China BT - Proceedings of the 8th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2018) PB - Atlantis Press SP - 265 EP - 271 SN - 2352-5428 UR - https://doi.org/10.2991/rac-18.2018.41 DO - 10.2991/rac-18.2018.41 ID - Wang2018/10 ER -