Detailed Inventory and Spatial Distribution Analysis of Rainfall-Induced Landslides in Jiexi County, Guangdong Province, China in August 2018
-
Published:2023-09-19
Issue:18
Volume:15
Page:13930
-
ISSN:2071-1050
-
Container-title:Sustainability
-
language:en
-
Short-container-title:Sustainability
Author:
Xie Chenchen123, Huang Yuandong234ORCID, Li Lei23, Li Tao23, Xu Chong23ORCID
Affiliation:
1. Institute of Disaster Prevention, Sanhe 065201, China 2. National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China 3. Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China 4. School of Emergency Management Science and Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
Abstract
In recent years, with the intensification of climate change, the occurrence of heavy rain events has become more frequent. Landslides triggered by heavy rainfall have become one of the common geological disasters around the world. This study selects an extreme rainfall event in August 2018 in Jiexi County, Guangdong province, as the research object. Based on high-resolution remote sensing images before and after the event, visual interpretation is conducted to obtain a detailed distribution map of rainfall-induced landslides. The results show that a total of 1844 rainfall-induced landslides were triggered within Jiexi County during this rainfall event. In terms of triggered scale, the total area of the landslides is 3.3884 million m2, with the largest individual landslide covering an area of 22,300 m2 and the smallest one covering an area of 417.78 m2. The landslides are concentrated in the northeastern, central, and southwestern parts of the study area, consistent with the distribution trend of rainfall intensity. To investigate further the influence of the regional environment on landslide distribution, this study selects eight influencing factors, including elevation, slope aspect, slope angle, topographic wetness index (TWI), topographic relief, lithology, distance to river, and accumulated rainfall. The landslide number density (LND) and landslide area percentage (LAP) are used as evaluation indicators. Based on statistical analysis using a data analysis platform, the relationship between landslide distribution and influencing factors triggered by this event is revealed. The results of this study will contribute to understanding the development law of regional rainfall-induced landslides and provide assistance for disaster prevention and mitigation in the area. The research results show that the elevation range of 100–150 m is the high-risk zone for landslides. In addition, this study has verified previous findings that slopes in the southeast direction are more prone to landslides. The steeper the slope, the more significant its influence on landslide development. When the topographic wetness index (TWI) is less than 4, landslides tend to have a high-density distribution. Greater variation in terrain relief is more likely to trigger landslides. The instability of lithology in Mesozoic strata is the main cause of landslides. The farther away from the water system, the fewer landslides occur. An increase in cumulative rainfall leads to an increase in both the number and area of landslides.
Funder
National Natural Science Foundation of China National Key Research and Development Program of China
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
Reference76 articles.
1. On the impact of climate change and population growth on the occurrence of fatal landslides in South, East and SE Asia;Petley;Q. J. Eng. Geol. Hydrogeol.,2010 2. Rong, G., Li, K., Han, L., Alu, S., Zhang, J., and Zhang, Y. (2020). Hazard mapping of the rainfall–landslides disaster Chain based on GeoDetector and Bayesian Network Models in Shuicheng County, China. Water, 12. 3. Use of satellite remote sensing data in the mapping of global landslide susceptibility;Hong;Nat. Hazards,2007 4. Ma, S., Shao, X., and Xu, C. (2022). Characterizing the distribution pattern and a physically based susceptibility assessment of shallow landslides triggered by the 2019 heavy rainfall event in Longchuan County, Guangdong Province, China. Remote Sens., 14. 5. Lithological and seasonal control on rainfall thresholds for the possible initiation of landslides in central Italy;Peruccacci;Geomorphology,2012
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|