Landslide susceptibility zonation mapping using geospatial technologies and multi criteria evaluation techniques in the upper Didessa sub-basin, Southwest Ethiopia

Abstract

Landslides have a profound impact on landscape geology, resulting in extensive devastation and loss of human lives. Mapping landslide susceptibility is crucial for effective land use planning in mountainous country like Ethiopia. This study was conducted in the upper Didessa sub-basin, southwestern parts of Ethiopia using Geographic Information System (GIS) and multi criteria evaluation (MCE) technique. This study employed a blend of primary data, encompassing field surveys and interviews with experts, as well as secondary data derived from diverse source, such as remote sensing data, digital soil maps, and geological maps. A total of eleven critical factors were employed to assess the triggers of landslides. These factors include slope, aspect, drainage density, topographic wetness index (TWI), stream power index (SPI), topographic ruggedness index (TRI), hypsometric integral, lithology, land use land cover (LULC), soil texture, and distance from roads. The analytical hierarchy process (AHP) method was used to determine the significance of each indicator through pairwise comparison matrix. The study area was categorized into different zones based on the susceptibility to landslides, namely very high, high, moderate, low, and very low. Results revealed that cultivated land had the highest likelihood of experiencing landslides, with a total of nine incidents out of 25, followed by built-up areas with seven landslides. Conversely, dense forests, sparse forests, and grazing land experienced a lower likelihood of landslides. Out of the 11 factors contributing to landslides, 24% of the surveyed region was deemed to have a moderate susceptibility, with 12% and 6% falling into the categories of high and very high susceptibility to landslides, respectively. The findings of this research provide important information for policymakers to develop efficient measures for preventing and reducing the risks of landslides.

Keywords

• Analytical hierarchy process
• Landslide
• Multi-criteria evaluation
• weighted linear combination