Real-Time Landslide Warning System to Save Lives in Himalayan Region

Amrita Vishwa Vidyapeetham, ranked as India’s eighth best university in the 2018 NIRF rankings, is on a mission to save lives in mountainous regions by installing systems that give advance warnings of landslides so that people can be safely evacuated before disaster strikes. After successfully commissioning India’s first such system in Kerala’s Western Ghats, it is now readying a second installation in Sikkim to guard against rainfall-induced landslides in the Sikkim-Darjeeling belt. The project is jointly funded by the Ministry of Earth Sciences, Govt. of India, and Amrita Vishwa Vidyapeetham.

Landslides are the third most deadly natural disasters on earth, killing over 300 people every year globally. The number of fatal landslides in India is higher compared to other countries. A report by Indian Roads Congress estimates that 15 percent of India’s landmass is prone to landslide hazard, including areas like the Western Ghats and Konkan Hills, Eastern Ghats, North East Himalayas, and North West Himalayas. In North East Himalayas, the Sikkim-Darjeeling belt is at the most risk of landslides, which is why we chose this area to install our landslide detection system, said Maneesha Sudheer, Director, Center for Wireless Networks & Applications, Amrita Vishwa Vidyapeetham. Sudheer spearheads landslide research at the university.

As per David Petley’s global database on landslides, the world’s top two landslide hotspots exist in India: the southern edge of the Himalayan arc, and the coast along south-west India where the Western Ghats are situated. Not only is tectonic activity higher in the southern Himalayan arc, monsoon rains and manmade changes to the slopes have made these hills much more prone to landslides.

Venkat Rangan, Vice Chancellor, Amrita Vishwa Vidyapeetham said that under the direct guidance of our Chancellor, Sri. Mata Amritanandamayi Devi, Amrita Vishwa Vidyapeetham deployed a unique system in the Western Ghats in 2009 in Kerala’s Munnar district, with the noble objective of saving human lives. This system has been actively monitoring the area for landslides and has issued several successful warnings to date. Impressed by this success story, the Govt. of India approached Amrita to develop a similar system for the Sikkim-Darjeeling region which is very active geologically and is vulnerable to rainfall-induced landslides. Accordingly, we have deployed this new system in collaboration with the Sikkim State Disaster Management Authority and are being co-funded by the Ministry of Earth Sciences, Govt. of India.

Amrita’s new IoT (Internet of Things) system for landslides, being installed in Sikkim, is custom developed for Himalayan geology. The IoT system with more than 200 sensors, can measure geophysical and hydrological parameters including rainfall, pore pressure and seismic activity. It will be monitoring a densely populated area in and around the Chandmari Village in Sikkim’s Gangtok District 24x7. This area has seen landslides in the past, the first one being reported in 1997.

The system collects real-time, continuous data from the sensors, performs basic analysis at the Field Management Center (FMC) located on the site in Sikkim, and relays it to the Data Management Center (DMC) at Amrita Vishwa Vidyapeetham in Kerala’s Kollam district. The university researchers are using this data to characterize and learn the geological and hydrological nature and response of the hill with respect to the dynamic and real-time meterological variations to develop the Landslide Early Warning Model for that area.

To improve the system’s reliability and enhance the early warning duration, a three-level Landslide Early Warning Model has been developed. The first level, based on rainfall threshold, has successfully completed the testing phase and is ready to go live and issue alerts for potential landslides at the state level. In the second level, the system would generate a Factor of Safety (FOS) value for various points on the hill in real-time that will provide a more specific warning for the Chandmari region based on the rainfall, moisture and pore pressure sensor data from the field. In the third level, the system would use data derived from the movement and vibrational sensors to issue landslide detection warning.