Landslide Susceptibility assessment using GIS on Rock-Soil Slope along Zabidar Mountain Road Corridors, Ethiopia

Document Type : Research Paper

Authors

1 Wolkite University, Institute of Technology, Department of Civil Engineering, Tel: +251912377796, Wolkite, Ethiopia

2 Jimma University, Institute of Technology, Department of Civil Engineering, Tel: +251913969689, Jimma, Ethiopia

3 Jimma University, Institute of Technology, Department of Civil Engineering, Tel: +251912883113, Jimma, Ethiopia

Abstract

Landslides are deceitful natural disasters, resulting in the loss of human life, collapse of engineering structures, and the natural environment on the earth. Therefore, the aims of this study to assess, predict and mapping of susceptible landslide hazard map using GIS based software. Six landslide causative factors including aspect, distance from stream, lithology, plan curvature, slope and elevation selected as influencing factor for landslide occurrences. The landslide frequency ratio calculated using the probability technique. The controlling elements graded using a statistical and frequency ratio methodology based on GIS. The landslide hazard map shows 27% (4.8 km2) is no-danger zone, with 588 (41%) families living there. A medium to landslide danger zone covers 29% (5.2 km2), with 555 families (38.7%) living. A low-risk landslide zone covers 23% (4.1 km2), with 228 (16%) families living. A high-risk landslide zone covers 21% (3.8 km2), with 61 (4.3%) families living. The prediction rate of all factors revealed that, the highest landslide occurrence associated with Lithology and plan curvature. When these are added with high rainfall intensity, the magnitude of the landslide increases. The highest prediction accuracy of 89.58% found from combination of all causative factors which depicts how well the model and factors accurately forecast landslides.

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Article Title [Persian]

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Geopersia
Volume 12, Issue 2
November 2022
Pages 201-222

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History

  • Receive Date: 22 January 2022
  • Revise Date: 10 March 2022
  • Accept Date: 19 March 2022

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