Computational modeling platform demonstrates real-time flood risk forecasting across global catchments, highlighting scalable early warning capabilities for ungauged regions.
Flash floods pose significant risks to communities lacking dedicated ground sensor networks. HydroPulse is an open-access software engine that combines 72-hour weather forecasts from the Open-Meteo API with Copernicus 30-meter digital elevation models to compute real-time flood risk metrics. The system evaluates Topographic Wetness Index (TWI), Manning-based flow velocities, and time-to-peak surge arrivals to classify hazard levels across global catchments. Built with Python and Streamlit, it features 3D terrain visualization, low-bandwidth data exports, and a fallback data generator to ensure continuous operation during network drops. Additionally, it includes an architectural design for integrating localized IoT ultrasonic water level sensors via MQTT.Live Interactive Web Application: [https://hydropulse-analytics.streamlit.app/]
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Yeabsera Gezahegn (2026) studied this question.
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