Landslides: The need for early warning systems, Pg17

Key Highlights:

• Recent landslides in the Western Ghats, including a devastating event in Wayanad in 2024 that killed over 250 people, have underscored the urgent need for effective Landslide Early Warning Systems (LEWS) in India.
• Amrita Vishwa Vidyapeetham successfully deployed a sensor-based A-LEWS in Munnar, Kerala, which helped evacuate residents and prevent casualties during recent landslides.
• IIT Mandi has developed a LEWS for the Indian Himalayan Region (IHR), utilizing probabilistic forecasting based on satellite data and localized rainfall.
• The India Meteorological Department (IMD) is working on higher-resolution rainfall forecasts crucial for enhancing the accuracy and lead time of these warning systems.
• India's National Disaster Management Authority (NDMA) has established guidelines and a National Landslide Risk Management Strategy to address landslide hazards, with the Geological Survey of India (GSI) acting as the nodal agency.

Detailed Insights:

• The 2024 Wayanad landslide, triggered by over 400 mm of rainfall in 24 hours, highlighted the vulnerability of the Western Ghats to extreme weather events.
• Amrita Vishwa Vidyapeetham's A-LEWS in Munnar uses intelligent wireless probes to monitor critical parameters like rainfall, soil moisture, and ground vibrations.
• This sensor-based approach provides real-time data, enabling timely evacuations and demonstrating the system's efficacy in saving lives.
• IIT Mandi's LEWS for the IHR integrates historical landslide data, terrain susceptibility, and machine learning for daily forecasts and issues alerts via a web portal and WhatsApp.
• A separate IIT Mandi team has developed a low-cost, AI-powered EWS capable of predicting landslides up to three hours in advance with over 90% accuracy, deployed in Himachal Pradesh.
• The effectiveness of probabilistic forecasting models is directly linked to the availability of highly localized and high-resolution rainfall data from agencies like the IMD.
• Vulnerable regions in India include the Western Ghats (with over 60% of Karnataka's stretch being landslide-prone), the Indian Himalayan Region, and parts of Manipur and Mizoram.
• The NDMA's National Landslide Risk Management Strategy aims for comprehensive hazard mapping, monitoring, and capacity building to reduce landslide risks.
• The GSI has established the National Landslide Forecasting Centre (NLFC) and is testing regional LEWS prototypes in collaboration with the British Geological Survey.
• A comprehensive national LEWS could be established within two years with dedicated resources, focusing on identifying and instrumenting high-risk zones.

Scientific/Technical Concepts Involved:

• Landslide Early Warning System (LEWS): A system designed to predict and monitor the likelihood of landslides by combining terrain susceptibility with real-time data.
• Wireless Sensor Network (WSN): A network of spatially distributed autonomous sensors to monitor physical or environmental conditions, like ground movement and moisture.
• Probabilistic forecasting: A method that uses statistical models and historical data to estimate the probability of a future event, such as a landslide.
• Tilt meters, pressure gauges, accelerometers: Instruments used in sensor-based EWS to measure ground deformation, pore water pressure, and ground vibrations, respectively.