Investigating probable causes for predicting catastrophic landslides along NH-60 excavated through semi-arid basaltic terrain of Chandanapuri Ghat, Maharashtra, India

• Published in: Environment, development and sustainability development and sustainability, 2022-02, Vol.24 (2), p.2362-2386
• Main Authors: Khamkar, Dattatray, Aher, Sainath, Gawali, Praveen, Mhaske, Sumedh
• Format: Article
• Language: English
• Subjects: Aridity; Data collection; Earth and Environmental Science; Ecology; Economic activity; Economic conditions; Economic Geology; Economic Growth; Environment; Environmental Economics; Environmental Management; Environmental risk; Evaluation; Field investigations; Field tests; Global positioning systems; GPS; High risk; Imagery; Investigations; Landslides; Landslides & mudslides; Polls & surveys; Prone; Rainfall; Remote sensing; Risk management; Risk reduction; Roads; Roads & highways; Rocks; Satellite imagery; Soil structure; Spatial data; Sustainable Development; Traffic; Traffic information; Traffic surveys; Weighting
• ISSN: 1387-585X; 1573-2975
• DOI: 10.1007/s10668-021-01537-3

Road Cut Slope Catastrophe (RCSC) is a recent menace threatening vehicular traffic and commuter safety in hilly tracts. Reduction of risk along Road Cut Hill Slope (RCHS) needs to be tackled on priority. National Highway (NH) 60 (formerly NH-50) situated in semi-arid basaltic tract within Chandanapuri Ghat (hill) in Maharashtra is being expanded to enhance economic activity in the allied region. To predict RCSC or landslide activity across the Ghat stretch, eleven ( n  = 11) road cut slopes were investigated by collecting data regarding (1) slope, (2) RCHS height, (3) distance from road, (4) rock composition, (5) soil structure, and (6) mass movement. Traffic survey was also carried out to understand the vehicular frequency. Survey of India (SOI) 1:50,000 scale toposheet (47/I/3) and LISS-III satellite imagery were used to identify the pre-expansion road situation of the area. Mean rainfall and temperature data were collected from TRMM data, and worldclime grid, respectively, to evaluate climatic nature of the area. Satellite-derived ASTER GDEM data were used to prepare the topographic information. Field investigations, GPS data and traffic survey, space-based remote sensing (RS) satellite-derived data were all integrated in ArcGIS V.9.2 software to produce the composite spatial database of all samples. After that, RCHS site weighting and weighted factor combination (WFC) were carried out to form the Landslide Risk Intensity (LRI), i.e., Low risk (LR), Moderate Risk (MR), High risk (HR), and Very High risk (VHR). Results indicate that out of 11 samples, 2 (P3, P11) are prone to VHR, 3 (P2, P9, P10) prone to HR, 3 (P5, P7, P8) prone to MR, and 3 (P1, P4, P6) prone to RCSC. The results were validated from rock fall activity even though the cut slopes are protected with security net, confirmed by field visit. Thus, investigated RCSC will be useful to evaluate the risk intensity and help evolve suitable remedial measures for RCSC or landslide reduction in the present and other similar areas. It is also recommended to make highway slope maintenance an integral part of highway management.