A five-year research project on flood and drought early warning systems in India, combining satellite data, IoT, machine learning, and community-based validation to improve disaster preparedness, resilience, and policy action.
This project is a five-year longitudinal study on pre-disaster preparedness and early warning systems in India, with a primary focus on Gujarat and comparative benchmarking across other disaster-prone states. It integrates satellite remote sensing, GIS, IoT-based monitoring, community participation, and policy analysis to improve flood and drought preparedness, especially for agricultural drought and urban flood risk.
Details
- Funding agency: Indian Council of Social Science Research(ICSSR).
- Duration: 5 years.
- Total grant amount: ₹99,00,000.
- Budget includes: Research staff, fieldwork, equipment and study material, contingency, and workshop, seminar, and publication costs.
- Study area: Gujarat, with comparative benchmarking across other disaster-prone states in India.
- Themes: early warning systems, floods, droughts, agricultural drought, GIS, remote sensing, IoT, and machine learning.
Key points
- Focuses on strengthening early warning systems for floods and droughts through science-based and community-informed approaches.
- Uses remote sensing indicators such as SPI, SPEI, and NDVI to support drought detection and early alert generation.
- Combines geospatial analysis, IoT sensors, and machine learning for more timely and actionable risk assessment.
- Examines institutional readiness, communication gaps, and policy implementation across Gujarat and comparator states.
- Produces practical outputs such as vulnerability maps, district-level preparedness scores, policy briefs, and stakeholder feedback tools.