Utilization of Multiple Radar Observation Into Real-Time Flood Forecasting (PAP014367)

Código

PAP014367

Autores

Sunmin Kim, Eiichi Nakakita

Tema

Impact of climate change on flood risk

Resumo

This study describes an example of a real-time flood prediction system in Japan, built on a distributed hydrologic model using radar-estimated rainfall data, and a series of procedures for improving the forecast accuracy. This real-time flood prediction system is currently operational for the Yodo River basin (7,281 km2) in Japan, and a distributed hydrologic model is utilized in it. Precipitation input for the hydrologic model is provided by a composite of data from C-band (5 cm wave length) weather radar estimation and the AMeDAS (Automated Meteorological Data Acquisition System) observation, which has 2.5 km of spatial and 10 minutes of temporal resolutions. The real-time flood prediction system is currently being upgraded to improve its forecasting accuracy with the utilization of new input data. The new precipitation input data is estimated by using multiple X-band (3 cm wave length) polarimetric radars, which have just been released in Japan for operational testing. This study provides a series of utilization procedures for the new input data, data quality checking, system modification, and evaluation of forecast accuracy. First of all, the accuracy of the X-band radar observation was determined by comparing its results with the rainfall intensities as observed by ground gauge stations. It was also compared with conventional C-band radar observation. The rainfall information from the new radar network was then provided to a distributed hydrologic model to simulate river discharges. The simulated river discharges were evaluated again using the observed river discharge to estimate the applicability of the new observation network in the context of operations regarding flood forecasting.