Context:
The Himalayan region is increasingly vulnerable to climate-induced disasters such as floods, landslides, glacial lake outburst floods (GLOFs), and avalanches, prompting scientists to emphasize the urgent need for a robust Early Warning System (EWS) to reduce human and economic losses.
Rising Disaster Trend in the Himalayas
- Between 1900–2022, India faced 687 disasters, with 240 occurring in the Himalayan belt (Down To Earth, 2024).
- Disasters have risen sharply — from only 5 incidents before 1962 to 68 between 2013–2022, accounting for 44% of India’s total disasters.
- NASA data (2007–2017) recorded 1,121 landslide events, indicating increasing instability.
- The Himalayas are warming at 0.15°C–0.60°C per decade, faster than the global average, accelerating snowmelt and flash floods.
- Frequency and intensity of cloudbursts, avalanches, and GLOFs have grown significantly, affecting both mountain communities and downstream river basins.
Importance of Early Warning Systems (EWS)
- Life-saving Mechanism:
- Early alerts enable timely evacuation, reducing casualties in flood- and landslide-prone zones.
- Disaster Preparedness:
- Facilitates real-time hazard detection (GLOFs, cloudbursts, avalanches), enabling rapid emergency response.
- Scientific Data Backbone:
- Builds a data-driven record for risk modeling, improving infrastructure safety and climate adaptation planning.
- Community Resilience:
- Involving local communities in EWS management enhances awareness, accountability, and swift ground-level action.
- Proven Global Success:
- International experience from Switzerland and China shows EWS combined with community participation can prevent glacier-related disasters.
Successful Examples of EWS Implementation
- Switzerland: Local coordination and real-time alerts have prevented several glacier-collapse disasters.
- China (Cirenmaco Lake): Satellite-fed EWS with unmanned monitoring boats tracks glacial lake fluctuations.
- India: The Ministry of Environment, Forest and Climate Change (MoEFCC) has funded AI-based hailstorm early warning systems for apple farmers in Himachal Pradesh and Uttarakhand.
Role of Artificial Intelligence and Technology
- AI Models: Process real-time data for predictive warnings with sub-kilometre precision.
- Satellite Integration: Monitors lake levels, glacier shifts, and snowmelt patterns in real time.
- Drone Surveillance: Offers localized risk assessments, though limited by terrain, weather, and cost.
- AI-based Prototypes: Currently under pilot testing in Uttarakhand and Himachal Pradesh for predicting cloudbursts and hailstorms.
Challenges in Establishing EWS in the Himalayas
- Rugged Terrain: Difficulties in installing and maintaining sensors across remote, steep landscapes.
- Poor Connectivity: Limited internet and telecom infrastructure obstructs real-time data transmission.
- High Costs: Lack of affordable, indigenous EWS technology hampers large-scale deployment.
- Fragmented Governance: Overlapping institutional roles lead to delayed coordination and execution.
- Low Community Participation: Without local training and awareness, alerts often fail to trigger timely evacuation.
