Real-time data enhances flood forecasting accuracy in Japan

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Japan is among the countries prone to typhoons and floods. Around 20% of its population lives in flood-prone areas. Early warning systems and accurate flood predictions that provide hours of lead time are crucial for giving communities enough time to prepare and act, which can reduce losses of life and property.

Thanks to improvements in model detail, how physical processes are represented, how unknowns are estimated, and computing power, weather and hydrological forecasts are better.

The study, “Application of real-time data assimilation system to improve streamflow forecasts in Japan”, published in the Journal of Hydrology in September 2026, presents findings from researchers at the Institute of Industrial Science, The University of Tokyo (UTokyo-IIS) who have developed a real-time data assimilation system that has significantly improved streamflow and flood forecasting accuracy across Japan and outperformed the country’s current early warning systems.

The new data assimilation system employs the Local Ensemble Transform Kalman Filter (LETKF) to integrate real-time river gauge readings into the larger river model, improving forecasts and making flood predictions more accurate and useful for issuing timely warnings.

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