Fundamental Study of Real-time Short-term Rainfall Prediction System in Watershed: Case Study of Kinu Watershed in Japan

This study focuses on the improvement of the accuracy and construction of a real-time, short-term rainfall prediction system in watershed, comparing the prediction results with radar observed rainfall intensity, to provide a reliable tool for disaster and water resource management. The short-term prediction of rainfall is very important for hydrologie forecasting for watershed with a short response time, especially under the global warming and extreme weather. Last September 9th (2015), heavy rain came a day after Tropical Storm Etau and triggered widespread flooding in Kinu Watershed. We use the Weather Research and Forecasting Model (WRF) to confirm the uncertainty of the rain prediction in Kinu watershed first, then will modify the WRF to suit the 6h, 12h, 24h rainfall prediction in Kinu watershed. Also, radar rainfall data will be employed to correct the WRF prediction in real-time meaning. Finally, we will check the possibility of general application of the system in other watersheds. We now are working on reproducing the heavy rain in Kinu watershed last September. We tried different microphysics, which describes the formation of cloud, to find one to reproduce the heavy rain in this case. The coverage, location of rain bands and distribution of heavy rainfall are applied to comparisons between calculations and observations by C-band radar. We found no Microphysics does well in this case and the area of heavy rain is underestimated by WRF, but the accumulated precipitation is overestimated. Detail insight at microphysics and modification are required.