AI‑Driven Disaster Management Post‑Disaster Management (Amendment) Act, 2025 – Key Initiatives and Institutional Roles
The Disaster Management (Amendment) Act, 2025 has catalysed a technology‑centric approach to the entire disaster management cycle – from preparedness to mitigation. Central agencies are now embedding AI and ML tools in forecasting, risk mapping and decision support.
Key Developments (Bullet Points)
- National Disaster Database – a unified repository of risk assessments, mitigation plans and real‑time disaster data, mandated by the 2025 amendment.
- AI‑enabled weather forecasting – the IMD now uses AI/ML models for seven‑day predictions, including flood simulations and cyclone tracking under Mission Mausam.
- Web‑DCRA & DSS tool – a web‑based Dynamic Composite Risk Atlas and Decision Support System developed by the NDMA, successfully employed during Cyclones Biparjoy and Michaung.
- Flood Hazard Atlas – created by the National Remote Sensing Centre (NRSC) for flood‑prone states (e.g., West Bengal, Bihar) and less‑affected states, providing high‑resolution flood risk layers.
- AI‑based flood forecasting by CWC – the Central Water Commission launched pilot AI/ML short‑range flood models in 2025 and now offers seven‑day advisory forecasts on its portal aff.india-water.gov.in.
- Avalanche forecasting by DRDO – the Defence Research and Development Organisation is developing AI‑driven avalanche hazard forecasting, control structures and an autonomous avalanche forecasting system for the Himalayan region.
Important Facts
• The AI integration covers major hazards – floods, cyclones and avalanches – across diverse geographies.
• Real‑time data feeds from satellite, radar and ground stations feed the AI models, enhancing prediction accuracy up to seven days.
• Funding details for AI‑driven disaster initiatives are not centrally collated, indicating a need for better financial tracking.
• Training and awareness programmes for officers and volunteers are listed in the annexure, underscoring capacity‑building efforts.
UPSC Relevance
Understanding the shift to AI‑enabled disaster management is crucial for GS2 (Polity) – the legal and institutional framework, GS3 (Technology & Economy) – the role of emerging technologies in public governance, and GS4 (Ethics) – the ethical implications of data‑driven decision‑making in life‑saving operations. Questions may probe the effectiveness of the NDMA tools, inter‑agency coordination, or the challenges of integrating AI in a federal structure.
Way Forward
- Establish a centralised fund tracking mechanism for AI‑based disaster projects to ensure transparency and optimal resource allocation.
- Scale up AI pilots to cover all river basins and coastal zones, incorporating local knowledge and community‑based data.
- Institutionalise regular training modules for disaster responders, emphasizing AI literacy and ethical data use.
- Strengthen inter‑agency data sharing platforms to create a seamless, real‑time national disaster monitoring network.
These steps will consolidate India’s move towards a resilient, technology‑forward disaster management system, aligning with global best practices and the nation’s commitment to sustainable development.