Syllabus: Disaster and disaster management
Recent Himalayan Disasters
- Mount Everest (Tibetan side): sudden blizzard, torrential snowfall, lightning strikes trapped 1,000 trekkers recently.
- Heavy downpour, snowfall caused floods, landslides killing scores in Nepal and Darjeeling simultaneously.
- 687 disasters (1900-2022) in India; 240 were in the Himalayas per 2024 Down To Earth report.
- Disasters include glacial lake outbursts, landslides, floods, wildfires, earthquakes increasing frequency alarmingly.
- 1902-1962: only 5 disasters recorded; 2013-2022: highest at 68 disasters (44% of India’s total).
- 1,121 landslide events between 2007-2017 per NASA’s landslide data showing rapid increase.
Climate Change Impact
- The Himalayas are experiencing a faster warming rate than global average: 0.15° to 0.60°C per decade.
- Climate change makes seismically vulnerable ranges increasingly unpredictable, threatening lives and livelihoods.
- 90% of the Himalayas will experience drought lasting over a year if global warming increases 3°C predicted.
- Wildlife trapped in “altitude squeeze”: warming pushes musk deer, snow trout to higher ground.
Need for Early Warning Systems (EWS)
- Current Gaps
- Abysmally poor number of EWS in world’s most volatile regions despite urgent need.
- Need EWS in each valley across the entire Himalayan arc covering 12 Indian States/UTs.
- Lack indigenous low-cost EWS: weather-proof, easy-to-install/operate, using multiple parameters, transmitting live data.
- Many valleys remote, out of mobile network reach posing data transmission challenges significantly.
- Technological Challenges
- Drones have scale problem: only good for localized studies, hard to fly in glacierized, windy, rugged conditions.
- Satellite links very expensive, may not be scalable; data collection needs to be rapid.
- Monitoring 2,400 km range poses significant logistical and technological challenges for comprehensive coverage.
Potential Solutions
- AI and Technology
- Artificial Intelligence (AI) models can transform live data to credible warnings effectively.
- Systems based on melding local data, AI-aided predictions, rigorously downscaled atmospheric models capturing local processes.
- Sub-kilometre scale hailstorm alerts (few hundred metres) for apple orchards in Uttarakhand, Himachal Pradesh.
- Successful Examples
- Swiss Alps Blatten village: shepherd’s call to downstream village saved hundreds from glacier-collapse/debris flow.
- Chinese Academy of Sciences (2022): created EWS for GLOFs in Cirenmaco (central Himalayas) using unmanned boat.
- System monitors lake-level change, end-moraine displacement, ice collapse, downstream runoff transmitting via satellites/mobile network.
- Hazard map created: flood depth/velocity translated into four intensity levels for evacuation planning.
- Implementation Requirements
- Involve and train local people to maintain, operate EWS, react to warnings ensuring community participation.
- The Environment Ministry funded an operational system providing advanced hailstorm alerts to orchard managers recently.
- Network of rugged, easy-to-operate EWS essential to monitor activity across Himalayan mountains comprehensively.
- Priority and Urgency
- Himalayan catastrophes are not given priority by scientists, engineers, funding agencies, industry, policymakers at central/local levels.
- Dr. Banerjee emphasizes “Himalayan people need it urgently”; should be a national priority immediately.
- A functional early warning system can clearly save lives preventing humanitarian crises in vulnerable regions.