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

Abstract 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 landsl...

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Bibliographic Details
Main Authors: Joynal Abedin, Yasin Wahid Rabby, Ikramul Hasan, Humaira Akter
Format: Article
Language:English
Published: SpringerOpen 2020-08-01
Series:Geoenvironmental Disasters
Subjects:
Online Access:http://link.springer.com/article/10.1186/s40677-020-00161-z
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Summary:Abstract 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 m2 with a standard deviation of 546.1 m2). Size of 62.30% of the landslides was < 100 m2. The probability density of 50–100 m2 landslides is the highest and with the increase of the size of landslides, probability density decreases. It indicates the chance of large landslides (> 1000 m2) 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.
ISSN:2197-8670