Abstract Flooding events are a major contributor to natural disasters across the global tropics. However, reliable flood data are sparse, which limits our ability to understand flood dynamics across spatial and temporal scales. Here, data from the CYGNSS SmallSat constellation are utilized to identify small‐ to regional‐scale flooding events in Sumatra. Three case studies show that CYGNSS‐derived inundation data capture evolution of floods, with increased inundation detected near flood locations 1 day after the event. A comprehensive analysis of 555 floods records in Sumatra identifies key parameters for a flood detection: an inundation anomaly threshold (0.1) and maximum distance between observations and a flood location (15 km). This approach could enhance flood risk assessment and forecasting, benefiting tropical populations. Our methodology, reliant on low‐cost small‐satellites, shows promise for future scalability with a larger satellite constellation, enabling better flood detection and long‐term, near‐real‐time monitoring of floods across the global tropics.

Read original article

Read original article