| Issue |
E3S Web Conf.
Volume 677, 2025
The 3rd International Conference on Disaster Mitigation and Management (3rd ICDMM 2025)
|
|
|---|---|---|
| Article Number | 06011 | |
| Number of page(s) | 7 | |
| Section | Physical Infrastructure Management and Recovery | |
| DOI | https://doi.org/10.1051/e3sconf/202567706011 | |
| Published online | 12 December 2025 | |
Statistical analysis of runout distance with slope angle based on weathered soil type on slopes
1 Department of Civil Engineering, Faculty of Engineering, Universitas Andalas, Padang, 25163, Indonesia
2 Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Andalas, Padang, 25163, Indonesia
3 Department of Civil Engineering, Mangalore Institute of Technology and Engineering, Mangaluru, Karnataka, India
4 Department of Civil Engineering, Faculty of Engineering, Padang Institute of Technology, Padang, 25173, Indonesia
* Corresponding author: abdulhakam2008@gmail.com
The slope angle and the type of weathered soil present are key factors in determining runout distance. This study aimed to classify slope angle values based on vulnerability, analyse the types of weathered soil present on slopes that have collapsed, and examine the relationship between runout distance (¸) and slope angle (¸) for each type of weathered soil on the slope. Data were analysed using a simple linear regression method, where the dependent variable is runout distance (L) measured in meters, and the independent variable is the slope angle (¸) measured in degrees. The results indicated that a slope angle ranging from 35° to 45° poses the highest risk for slope instability in most landslides in Indonesia. The predominant soil type contributing to these landslides is clay (CL/CH). While the slope angle alone is not sufficient to accurately predict runout distance, both slope angle and soil type are important factors in assessing landslide susceptibility, although the correlation is generally weak. Therefore, it is essential to incorporate additional variables into the prediction model, such as landslide depth, soil moisture, landslide volume, vegetation type, and rainfall.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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