An investigation of the characteristics, causes, and consequences of June 13, 2017, landslides in Rangamati District Bangladesh

Geoenvironmental Disasters(2020)

引用 23|浏览7
暂无评分
摘要
The primary purpose of this study is to find out and discuss the characteristics, causes, and consequences of the landslides of June 13, 2017, in the Rangamati district Bangladesh. Since rainfall triggered the landslides, debris flow accounts for 40.45% of the landslides. Most of the landslides are small (mean 274. 2 m 2 with a standard deviation of 546.1 m 2 ). Size of 62.30% of the landslides was < 100 m 2 . The probability density of 50–100 m 2 landslides is the highest and with the increase of the size of landslides, probability density decreases. It indicates the chance of large landslides (> 1000 m 2 ) is low. Frequency ratio, logistic regression, and Spearman’s rank correlation were used to find out the relationship between 15 landslide causal factors including elevation, slope, rainfall, aspect, land use/land cover, land use/land cover change and distance to the road network with the occurrences and size of landslides. Among the land use/land cover types built-up areas [frequency ratio (FR) = 5.67], among land-use land-cover change types: vegetation to built-up (FR = 5.31) are the most prone areas to landslides. Logistic regression models found six causal factors were statistically significant, including slope (Coefficient, ß = 1.05), and distance to the road network (ß = 0.44). The size of the landslides had a significant relationship with five causal factors, including annual rainfall (ρ = 0.52), and elevation (ρ = 0.24). Paired sample t-test on pre-event and post-event monthly incomes revealed that landslides had a significant impact on different occupations of the local people. People involved in primary economic activities like the slash and burn agriculture (locally known as jhum cultivation) and fishing are the worst sufferers of landslides as they experienced a significant fall of income after the landslides. The findings of the study would help the policymakers to mitigate landslide hazards in the Rangamati district.
更多
查看译文
关键词
Landslides, Rangamati, Probability density, Frequency ratio, Logistic regression
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要