PS 26071SOFTWAREDisaster ManagementHidden GemModerate Scope

AI/ML-Based Integrated heavy rainfall Early Warning and Inundation Prediction System using Satellite, Radar, observational Weather and numerical weather prediction model data.

Ministry of Earth Sciences (MoES)India Meteorological Department
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30-Second Plain English Summary

Extreme monsoon downpours in major Indian cities (Mumbai, Chennai, Bengaluru, Delhi) cause catastrophic urban flooding within 60 minutes due to outdated stormwater drain capacities and lack of integrated hydraulic modeling. Build an AI-driven integrated heavy rainfall early warning and 2D urban inundation prediction system coupling Doppler weather radar rainfall nowcasts with municipal drainage networks to forecast street-level water logging depth.

5-Dimension Strategic ScorecardOverall Score: 3.8 / 5.0
Innovation
4 / 5
36h Feasibility
4.3 / 5
Uniqueness
3.5 / 5
Jury Appeal
3.5 / 5
Tech Depth
3.7 / 5
Recommended System Architecture Pipeline
Doppler Radar Feeds + IoT Drain Sensors -> Radar ConvLSTM Rainfall Nowcaster -> Neural Surrogate SWMM Flood Model -> PostGIS -> City Disaster Inundation Console
Recommended Tech StackClick to search similar
Official Government Problem Description
AI/ML-Based Integrated heavy rainfall Early Warning and Inundation Prediction System using Satellite, Radar, observational Weather and numerical weather prediction model data.
AI & PPT Citation Format

Smart India Hackathon 2026 Problem Statement PS-26071: "AI/ML-Based Integrated heavy rainfall Early Warning and Inundation Prediction System using Satellite, Radar, observational Weather and numerical weather prediction model data.", Ministry: Ministry of Earth Sciences (MoES). Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26071)

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