Landslide susceptibility mapping and risk assessment using total estimated susceptibility values along NH44 in Jammu and Kashmir, Western Himalaya

Riyaz Ahmad Mir (), Zahid Habib, Ajay Kumar and Nadeem Ahmad Bhat
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Riyaz Ahmad Mir: Naional Institute of Hydrology, Western Himalayan Regional Centre
Zahid Habib: Geological Survey of India, UTs: Jammu & Kashmir and Ladakh
Ajay Kumar: Geological Survey of India, UTs: Jammu & Kashmir and Ladakh
Nadeem Ahmad Bhat: Geological Survey of India, UTs: Jammu & Kashmir and Ladakh

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 5, No 10, 4257-4296

Abstract: Abstract Domain-specific mesoscale landslide susceptibility mapping (LSM) and risk assessment was carried out along National Highway (NH44) of Jammu and Kashmir, Western Himalaya. The methodology proposed in this study broadly consist three stages including the (1) pre-field component for preliminary thematic map preparation, (2) field component for ground data collection and validation, and (3) post-field component for data updating, processing, and integration. High-resolution Earth Observation (EO) images (Cartosat-DEM-10 m, Cartosat-1 PAN image-2.5 m, Google Earth image-4 m) and other ancillary datasets (SoI topographic, and geological maps) supplemented with extensive field survey were used to generate main causative geo-factor maps for analysis. Slope facet used as a basic unit of mapping preliminarily classified the area into rocky (65.7%) and overburden covered (34.2%) slopes, respectively. An updated inventory of 117 landslide incidence zones comprising 50 debris slides, 34 rockfalls, 20 rock slides, 5 rock topples, 2 debris flows and 6 old slide zones was generated. Depending upon the type and nature of material involved in the slope failure, facets were further classified into debris slide domain, rock slide domain, cut-slope domain and no slide domain for detailed analysis and treatment. The geo-factor maps were weighted using knowledge driven ratings for each factor class as per domain-specific facet using Landslide Susceptibility Estimated Rating (LSER) scheme. The sum up of LSER values for individual causative factors calculated the Total Estimated Susceptibility Values (TESV) that classified the entire area into low, moderate and high susceptibility classes covering an area of 39.8%, 40.0% and 20.1%, respectively. The validation of LSM against high-resolution landslide inventory indicated a higher level of performance of the adopted methodology for the study area. About 80.0% and 10.4% of slope failure incidences coincided perfectly well with high and moderate susceptibility classes. Moreover, the human settlements, agriculture land, roads and bridges, stone crushers and other strategic civil structures (i.e., tunnels, electric line poles and towers, etc.) are the main elements at high risk in the area.

Keywords: Banihal; Ramban; Landslide; Susceptibility; Risk; Management; Himalaya (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11069-023-06363-6

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