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A massive landslide was triggered on 19 May 2017 at Vishnuprayag near Joshimath, Uttarakhand, India. The landslide blocked the Rishikesh-Badrinath highway and halted traffic for about 24 h till the debris was removed and the road reopened. The Hathi Pahar hill in Vishnuprayag has been a landslide-prone zone because of the presence of loose boulders and large rock blocks on very steep slopes. The site was visited immediately after the landslide and a rapid field assessment of slope stability was carried out. The stability analysis was performed with limited geological and geotechnical data collected from field and laboratory. Based on the two-dimensional finite element analysis, it was inferred that the slope is marginally stable under static load, but fails under seismic loading. The slope could fail in future due to triggering factors such as heavy rainfall, earthquake and anthropogenic activities. This communication presents field observations and the subsequent stability analysis along with possible suggestive control measures. [ABSTRACT FROM AUTHOR]

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and −2 Log likelihood, Cox & SnellR-Square and NagelkerkeR-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making. [ABSTRACT FROM PUBLISHER]

The occurrence of landslide in the hilly region of Darjeeling during monsoon season is a matter of serious concern. Every year this natural hazard damages the major roads at several places and thus disrupts the transport and communication system in this region. This paper tries to prepare a landslide susceptibility zone (LSZ) map for the Gish River basin. A total number of 16 spatial parameters have been taken for this study and these are categorised under six factor clusters or groups for example, triggering factors, protective factor, lithological factors, morphometric factors, hydrological factors and anthropogenic factors. The LSZ map is prepared by integrating all the parameters adopting the weighting base as logistic regression. The landslide susceptibility map shows that nearly 9.11% of the area falls under the very high landslide-susceptible zone while 40.28% of the area of the total basin lies under the very low landslide-susceptible zone. The landslide-susceptible model is validated through the receiver operating characteristic curve. This curve shows 86% success rate in defining landslide-susceptible zones and 83.40% prediction rate for the occurrence of landslides. The spatial relationship between the landslide susceptibility model and other factors’ groups shows that the morphometric factors’ cluster (mainly slope) is the focalone for the determination of landslide-susceptible zone. [ABSTRACT FROM PUBLISHER]

In this paper, we present a state-of-the-art wireless sensor network (WSN) of deep-earth probes (DEPs) that has been deployed to monitor an active landslide in the Western Ghats mountain range of South India. While India has one of the highest incidences of landslides and landslide-induced fatalities-primarily in the Himalayas of North India and in the Western Ghats of Central and South India-our study is perhaps the first comprehensive attempt to instrumentally detect landslides in the Western Ghats. Wireless networks have enabled us, since June 2009, to continuously monitor the deployment site in real time and from anywhere around the globe. There have been a few earlier landslide monitoring WSNs using accelerometers in Emilia Romagna Apennines, Italy; global navigation satellite system (GNSS) sensors to monitor the Hornbergl landslide, Austria; and vibrating wire stress sensors to monitor a slope in China. We improved upon these WSN systems by incorporating a variety of sensors-piezometers, dielectric moisture sensors, strain gauges, tiltmeters, a geophone, and a weather station-and installing some of these sensors as deep as 20 m below the ground surface. We present the salient aspects of the field deployment of DEPs: the selection of sensors and their incorporation in DEPs, the methodology we used in embedding these DEPs into the soil, and a few of the key aspects of the wireless sensor network. We also present a description of the deployment site and some of the results of geotechnical investigations carried out on borehole corings. Finally, we present the more interesting field data collected from the monitoring system during a rainy season in July and August 2009. [ABSTRACT FROM AUTHOR]