India is a country prone to different types of landslides. This calamity can cause significant destruction in terms of loss of lives and property. As per the Geological Survey of India (GSI), about 0.42 million km2 (covering nearly 12.6% of the land area of our country) is prone to landslides.
The mountainous region of the north-western Himalayas (Jammu & Kashmir, Himachal Pradesh, Uttarakhand), the sub-Himalayan terrain of the north-east (Sikkim, West Bengal-Darjeeling, Assam, Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Tripura), the Western Ghat areas (Maharashtra, Goa, Karnataka, Kerala) and the Eastern Ghat areas (Araku area of Andhra Pradesh, Tamil Nadu) are prone to landslides.
Landslides occur frequently in the Himalayan and other landslide prone hilly areas in the country especially during the monsoon as a result of heavy rainfall. The majority of the landslide-prone areas in India happen to be located in regions that are also earthquake prone. Thus, these areas are susceptible to earthquake-triggered landslides, which happened, for example, during the Sikkim (2011), Kashmir (2005), Chamoli (1999) and Uttarkashi (1991) earthquakes.
Landslide incidence has increased - a major challenge for technocrats
In recent years, the incidence of landslides has increased due to extreme weather events, environmental degradation due to human interference and other anthropogenic activities, resulting in heavy loss of human lives, livestock and property.
It is estimated that economic loss due to landslides may amount to much as 1% to 2% of the Gross National Product in many developing countries. In fact, 80% of the reported fatalities due to landslides occur in developing countries. Therefore, evaluation and mitigation of this hazard and risk is a major challenge for the technocrats and decision makers in the developing world.
In recent years, the incidence of landslides has increased due to extreme weather events, environmental degradation due to human interference and other anthropogenic activities, resulting in heavy loss of human lives, livestock and property. This is also an opportunity for the technocrats to create technology solutions through application of artificial intelligence to minimize the impacts of landslides in the future. Since local communities are the first responders in any disaster, the technological solutions should be tailored keeping in mind their needs and requirements.
Guidelines from NDMA
In June 2009, the National Disaster Management Authority released the Guidelines on Management of Landslides and Snow Avalanches, laying down national policy for the management of landslides and related activities in the country. The guidelines were formulated in consultation with the Ministry of Mines, Geological Survey of India and other concerned Central and state departments, as well as academia. Even though the guidelines were issued in 2009, progress by way of their implementation was limited in the landslide-affected states/union territories.
The Landslide Risk Mitigation Scheme
The most important requirement for landslide mitigation was the participation of the state governments and other stakeholder agencies. On 19 December 2014, NDMA conducted a state-level meeting with landslide-prone states/UTs and concerned departments and institutes to discuss the ‘Landslide Risk Mitigation Scheme’ (LRMS) and other landslide-related issues. Representatives from fourteen states and nine departments participated in the meeting.
Detailed deliberations were held on the draft template for the preparation of detailed project reports (DPRs) for site-specific landslide risk mitigation.
Based on this consultation, NDMA released a template for preparation of DPRs for site-specific landslide risk mitigation in June 2015 and circulated it to all the landslide affected states and union territories.
Landslide-risk mitigation was highlighted in the National Disaster Management Plan of 2016, which was updated in 2019. The importance of preparing their individual holistic disaster management plans was impressed upon all State/UT governments and other agencies.
In July 2019, NDMA launched the LRMS to provide financial and technical support to landslide-prone states for site-specific landslide mitigation. The LRMS is a pilot scheme to demonstrate the benefits of landslide treatment measures by application of different methods of slope stabilization, along with landslide monitoring, awareness generation and capacity building/training, etc.
Memorandum of understanding (MOU) was signed with the state disaster management authorities (SDMAs) of Sikkim, Mizoram, Nagaland and Uttarakhand for implementation of the schemes and landslide treatment works that were in progress at the sites of Mangan (Sikkim), Hunthar Veng (Mizoram), Kohima-Thizama road (Nagaland), Kempty-Chadogi road and Hardiyanala-Karnprayag road (Uttarakhand).
Development of low-cost landslide monitoring and early warning system
The difficulties in preventing landslides are further compounded by the fact that existing landslide monitoring and early warning technologies cost crores of rupees, and that these technologies may not be capable of generating advisories for weather and slope movements ahead of time. The Himalayas and other mountain regions of India are vast and varying in nature, and the need for a low-cost landslide early warning system (EWS) has been long recognized.
In December 2017, NDMA launched a pilot project, ‘Development & Evaluation of Low-Cost Landslide Monitoring Solutions’, in collaboration with IIT Mandi and Defence Terrain Research Laboratory (DTRL)-DRDO. The project aimed to develop low-cost sensors and other instruments for landslide monitoring, using micro electro mechanical systems (MEMS)-based sensor technology and artificial intelligence. After detailed studies and experimentation, the project successfully developed a low-cost landslide monitoring, warning and prediction system.
Innovations and Artificial Intelligence
The system developed under this project addresses some of the issues in the existing technologies, such as their high cost and their lack of predictive capacity. The new system detects whether there is significant soil movement and activates roadside blinkers and hooters wirelessly so that vehicular road traffic can be alerted. The blinkers and hooters come on for 10-15 seconds with lights and sound each time soil movement is recorded at the deployment site.
In addition, the system also sends SMS messages about soil movements to disaster managers and the local people on their mobile phones. Recently, the system was been able to generate predictive messages about impending soil movements one day ahead of time as well as issue severe-weather advisories two hours ahead of severe weather events. The predictions of soil movements and severe weather are triggered by artificial intelligence (AI) algorithms running on a cloud-based server.
The developed system predicts the amount and magnitude of soil movement. While the information as to the number of landslides is useful for research, the information about their magnitude is most helpful in generating alerts for different stakeholders ahead of an event. The predictive algorithms are currently being refined, and the team from IIT Mandi is testing the system. Due to its low cost and predictive abilities, the system provides immense possibilities for deployment at a number of landslide sites in India.
The earlier systems had been developed for monitoring surface-based movements, but recently the system has also been perfected for detecting sub-surface movements. For this purpose, boreholes are made at the landslide site and a chain of multiple sensor nodes inserted into them for recording sub-surface movements. Each sensor node measures accelerations and displacements via an accelerometer, soil moisture via a capacitive soil moisture sensor, and soil stress s via a piezoelectric pressure sensor.
The data collected from the system is sent to the cloud server via GSM mobile technology. Also, the patented system runs autonomously on solar power and does not depend on grid power. The system’s electronics have been optimized to consume very low amounts of energy, where the battery can help sustain the system for days when there is no sunlight.
Landslide Strategy
The National Landslide Risk Management Strategy document addresses all the components of landslide disaster risk reduction and management, such as hazard mapping, monitoring and early warning systems, awareness programmes, capacity building and training, regulations and policies, stabilization and mitigation of landslides, etc. The document envisages specific recommendations for the concerned nodal agencies, ministries, departments, states, civil society organizations (CSOs) and other stakeholders, to avert or reduce the impact of future landslide calamities.
Outcomes of NDMA Initiatives
Landslide Risk Mitigation Scheme (LRMS): The LRMS scheme will benefit landslide-prone states and union territories by helping them prevent future landslides by taking proactive initiatives through the lessons learnt under the scheme.
Training programmes on Landslide Mitigation and DPR preparation: The training programme has been greatly beneficial to the landslide affected states/UTs, with the master trainers turned out by the programme assisting them in the preparation of DPRs for landslide treatment and in building the capacities of other stakeholders in their respective States/UTs. The DPRs received from the concerned States/UTs will be executed and implemented through LRMS.
Development of low-cost landslide monitoring and EWS: Calibration and validation of data obtained at different landslides sites are in progress to generate a reliable early warning model to save precious lives. This low-cost landslide monitoring technology will be beneficial in saving lives and property in the future by providing early warning alerts to the community members and local administration.
The outcomes of this project will be shared with all landslide-affected states for replication of the low-cost landslide monitoring system and generation of early warnings in a cost-effective manner in collaboration with their own local communities and authorities.
The full report can be accessed here
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