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Global Warming And Climate Change

Early Warning Systems in the Himalayas

 Oct 29, 2025   Admin

The Himalayan region often referred to as the Third Pole, needs robust Early Warning Systems (EWS) to tackle rising climate-induced disasters amid inadequate disaster preparedness.

Rising Vulnerability of the Himalayas

  • According to a report, out of 687 disasters that occurred in India between 1900 and 2022, nearly 240 were concentrated in the Himalayan belt.
  • The Himalayas are warming 0.15°C–0.60°C per decade, faster than the global average, making the region increasingly unpredictable and prone to extreme weather events.
  • NASA’s data shows that between 2007 and 2017, over 1,100 landslides occurred in the Himalayan region.
  • Need for Early Warning Systems (EWS)

  • EWS can monitor and predict glacial lake outburst floods (GLOFs), landslides, snowstorms, and cloudbursts in the Himalayan region.
  • Real-time data enables evacuation, rescue planning, and disaster management at both community and administrative levels.
  • Integration of EWS into mountain governance can strengthen local resilience and reduce economic losses from recurrent disasters.
  • Challenges in Setting up EWS in the Himalayas

  • Geographical Complexity: The Himalayan arc spans over 2,400 km, encompassing varied terrains, elevations, and climatic conditions, making uniform monitoring difficult.
  • Infrastructure and Connectivity Issues: Many valleys remain beyond the reach of mobile networks and satellite connectivity, complicating data transmission.
  • Lack of Indigenous Technology: India lacks low-cost, weather-resistant, easy-to-install EWS systems that can be locally maintained.
  • Institutional Gaps: Coordination between scientific institutions, local governments, and disaster response agencies is weak.
  • Funding for research and field-level implementation is limited.
  • Low Community Involvement: Local communities, often the first responders during disasters, are rarely trained or included in monitoring or response mechanisms.
  • Role of Technology and Artificial Intelligence in EWS

  • AI-based models can transform live data from multiple sensors into predictive warnings, helping local authorities make informed decisions.
  • Satellite monitoring and remote sensing can track glacier movements, rainfall intensity, and temperature anomalies, though high costs remain a concern.
  • Drones, while useful for localised mapping, face limitations in windy and high-altitude terrains.
  • Integration of AI, ground-based sensors, and community networks can offer a hybrid, scalable solution suited to the Himalayas.
  • Indian Initiatives

  • The Ministry of Environment recently funded an AI-assisted hailstorm EWS for apple orchards in Uttarakhand and Himachal Pradesh, capable of sub-kilometre alerts.
  • Projects like the National Mission for Sustaining the Himalayan Ecosystem (NMSHE) and National Disaster Management Authority (NDMA) frameworks encourage the integration of technology and community preparedness.
  • Develop Indigenous, Low-Cost EWS: Promote locally manufactured, weather-resistant systems for easy deployment.
  • Community-Based Disaster Management: Train local populations to maintain and operate EWS and respond effectively to alerts.
  • Data Integration and AI Use: Combine satellite data, ground sensors, and AI-driven models for accurate and timely warnings.
  • Transboundary Cooperation: Since Himalayan rivers and glaciers are shared by multiple countries, regional data-sharing and coordination are vital.
  • Policy and Funding Prioritisation: The central and state governments must treat Himalayan disaster resilience as a national priority, with dedicated funds and institutional focus.
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