Slope stability assessment and landslide susceptibility mapping in the Lesser Himalaya, Mussoorie, Uttarakhand

被引：0
作者：
Swati Mandal [1 ]
Ashish Mani [2 ]
Anugrah Rohini Lall [3 ]
Dharmendra Kumar [4 ]
机构：
[1] Banasthali Vidhyapith,Post Graduate Student, Department of Earth Science
[2] Amity School of Natural Resources and Sustainable Development (ASNRSD),Department of Humanities and Social Sciences
[3] Amity University Uttar Pradesh (AUUP),Geoweb Services, IT and Distance Learning (GIT&DL) Department
[4] Graphic Era Deemed to Be University,undefined
[5] Indian Institute of Remote Sensing (IIRS),undefined
[6] ISRO,undefined
[7] Department of Space,undefined
[8] Government of India,undefined
来源：
Discover Geoscience | / 2卷 / 1期
关键词：
Landslide; Rock Mass Rating (RMR); Slope Mass Rating (SMR); Geological Strength Index (GSI); Kinematic analysis; Frequency Ratio (FR);
D O I：
10.1007/s44288-024-00055-9
中图分类号：
学科分类号：
摘要：
The present study aims to assess slope stability and landslide susceptibility mapping of road-cut slopes along Mussoorie road in the Lesser Himalayan region. A total of 18 suspected unstable slope sites were selected for the investigation, and performed geo-mechanical classification techniques, including Rock Mass Rating (RMR), Slope Mass Rating (SMR), Geological Strength Index (GSI), and kinematic analysis. For the Landslide susceptibility mapping, the Frequency Ratio (FR) method was employed using the weightage of various causative factors which includes slope, aspect, curvature, elevation, distance from streams, distance from lineaments, lithology, and rainfall. The finding indicates that out of 18 selected slopes, 4 slopes are bad slope or unstable, which includes slope 3,4 and 6 in the lower part of the Mussoorie area near Jharipani, while slope 10 near Hathi Paon-Mussoorie Road is also unstable. The slopes around Junu waterfall are stable. Partially unstable slopes may vulnerable to slope failure in the future due to heavy rainfall and unstructured construction. Additionally, the Area Under Curve (AUC) and predictive rate curve values are 61% and 78% respectively, indicating acceptable overall accuracy. This study highlights the landslide issues in Mussoorie region due to rapid urbanization & climate change and demonstrates the effectiveness of the employed methods for future risk analysis.
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