Early Warning Systems in the Himalayas

Syllabus: GS3/ Environment

Context

• 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.

Way Ahead

• 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.

Source: TH