Earthquake and rainfall-induced landslide hazard assessment of Kutupalong Rohingya camp using meteorological and geological information

被引:0
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作者
Anika Samm-A
A. S. M. Maksud Kamal
Md. Zillur Rahman
机构
[1] University of Dhaka,Department of Disaster Science and Climate Resilience
来源
Stochastic Environmental Research and Risk Assessment | 2023年 / 37卷
关键词
Earthquake and rainfall; Monte-Carlo simulation; Landslides; Factor of safety;
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学科分类号
摘要
Kutupalong Rohingya camp is one of the largest humanitarian shelters for conflict-fled people. The camp area is susceptible to landslide hazards because of being situated in dynamic tectonic settings and meteorological conditions. Hence, the study aims to assess the earthquake and rainfall-induced landslide hazards in the camp for the worst-case scenario. The landslide triggering parameters (topographic, soil physical property, and contributing factors) are designed in the study to identify the hazard-prone areas through the factor of safety computation. The topographic parameters are prepared by combining field investigation and remote sensing-based information. The soil physical properties are modeled in two ways to account for their uncertainties: normal probabilistic distribution and interpolation-based spatial distribution. The contributing factors (i.e., earthquake and rainfall) have been assessed using the probabilistic approach. The Peak Ground Acceleration (PGA) exceedance of 50, 75, 100, 200, and 475 years return periods are applied in the factor of safety calculation for earthquake-induced landslides. The rainfall intensities of 50 and 75 years return periods are combined with the PGA exceedance of the respective years to assess the earthquake and rainfall-triggered landslide-prone areas. The factor of safety has been measured following two methods: Monte-Carlo simulation and direct estimation method. Multiple scenarios (rainfall with the duration of 1, 2, and 3 days) are also considered to estimate the landslide-prone areas in these models. The study findings are finally validated against field investigation-based landslide inventory with more than 85% accuracy at a 90% confidence interval.
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页码:2777 / 2789
页数:12
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