India’s Multi-Hazard Early Warning Decision Support System

1. At a Glance

2. Why in the News

3. Background & Evolution

4. Core Static Facts

5. Multi-Dimensional Analysis

Scientific / Technological - Built on open-source stack, in-house IMD expertise; integrates numerical weather prediction with GIS-based impact layers [S1][S2]. - Forecast preparation time cut by 50%; accuracy improved by 30% [S1].

Economic - Evacuation costs reduced to one-third between 1999 and 2024 owing to lower cyclone landfall point forecast error in 3–5 day lead-time forecasts [S1]. - Import substitution savings: ₹250 crore + ₹5.5 crore/yr O&M avoided [S1].

Administrative / Governance - Bridges central (IMD, NDMA) and state (SDMA) silos via standardised CAP alerts [S2]. - Supports Sendai Framework disaster risk reduction goals (implicit international alignment) [S1].

Social - Impact-based, location-specific warnings reach last-mile vulnerable groups (fishermen, farmers, coastal poor) across ~80% of India's population [S1].

6. Recent Developments (last 12-18 months)

7. Prelims Hooks

8. Mains Relevance

9. Related Topics to Study Next

10. Common Errors / Trap Areas

11. Sources