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Real-time landslide warning to save lives in Himalayas

Sikkim landslide warning

A custom developed real-time landslide warning system has been installed in landslide prone areas of the Himalayas.

Consisting of over 200 sensors measuring geophysical and hydrological parameters like rainfall, pore pressure and seismic activity, the system will monitor a densely populated area spanning 61ha around the Chandmari Village in Sikkim’s Gangtok District.

The system collects real-time, continuous data from the sensors, performs basic analysis at a field management centre located on the site in Sikkim, and relays it to a data management centre at Amrita Vishwa Vidyapeetham University.

University researchers are using this data to characterise and learn the geological and hydrological nature and response of the hill with respect to the dynamic and real-time meteorological variations to develop the landslide early warning model for the area.

Sikkim landslide warning

Sikkim landslide warning

Amrita Vishwa Vidyapeetham University’s Centre for Wireless Networks and Applications, director Maneesha Sudheer who spearheads landslide research said: “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% of India’s landmass is prone to landslide hazard, including areas like 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.”

To improve the system’s reliability and the early warning timings, 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 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 a landslide detection warning.

Sudheer said: “This multi-level warning system will help disaster management authorities to take steps to mitigate and manage potential landslide threats in a proactive and effective manner. In this regard, Amrita has performed several community engagement programmes to disseminate knowledge regarding the impact of landslides, the working of the proposed warning system and its capability to warn about imminent landslides.

“In the case of landslides, forewarned is forearmed. More accurate landslide databases need to be maintained and regional as well as site-specific rainfall threshold models developed.

”Low-cost in-situ monitoring technologies have to be deployed in landslide prone terrains, but people have to be educated regarding landslides and the risks involved, and social media and mobile phone apps can be developed to collect data about the chances or precursors for landslides from the people and other governmental organisations,” she said.

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