Spatial multi-parameter analysis of landslide susceptibility with geological structure integration
DOI:
https://doi.org/10.61511/srsd.v2i2.2025.2013Keywords:
landslide, GIS, overlay, scoring, watershedAbstract
Background: Based on the 2022-2026 disaster risk assessment, nearly all districts in Bali Province are at a high risk of landslides. The Tukad Oos Watershed is one of the river basins in Bali Province, spanning two districts: Gianyar District and Bangli District. Mapping and analysing landslide potential is an important step in disaster mitigation efforts. The objective of this study is to identify the locations of landslide-prone areas in the Tukad Oos Watershed and to assess the impact of the development of the Ubud and Kintamani tourist areas on these landslide-prone areas. Methods: The method used is multi-parameter scoring. This study analyzes landslide potential in Tukad Oos Watershed, Bali, using rainfall, slope, geology, soil, landform, and land use parameters with a weighted scoring method. Findings: The results of the landslide potential estimation analysis indicate a high landslide potential class covering 4.87 hectares or 0.03% of the basin area, a moderate potential class covering 72.97 hectares or 0.5% of the watershed area, a low potential class covering 829.98 hectares or 6.74% of the watershed area, and a non-potential class covering 11,406.05 hectares or 92.62% of the upstream Tukad Oos watershed area. Conclusion: The results of the landslide potential analysis from this study are quite similar to the Inarisk BNPB data, with the difference lying in the level of detail produced, which is influenced by the spatial resolution of the Digital Elevation Model (DEM) used for the analysis. The development of tourism activities in the Ubud and Kintamani areas does not significantly increase the landslide potential in the Tukad Oos watershed. Novelty/Originality of this article: Studies on landslides in Indonesia use several parameters; the main parameter that is often used is slope inclination, but this study adds geological structure parameters as a determining factor in landslide estimation.
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