Change of flood risk under climate change based on Discharge Probability Index in Japan

Water-related disasters under the climate change have recently gained considerable interest, and there have been many studies referring to flood risk at the global scale (e.g. Milly et al., 2002; Hirabayashi et al., 2008). In order to build adaptive capacity, however, regional impact evaluation is needed. We thus focus on the flood risk over Japan in the present study. The output from the Regional Climate Model 20 (RCM20), which was developed by the Meteorological Research Institute, was used. The data was first compared with observed data based on Automated Meteorological Data Acquisition System and ground weather observations, and the model biases were corrected using the ratio and difference of the 20-year mean values. The bias-corrected RCM20 atmospheric data were then forced to run a land surface model and a river routing model (Yoshimura et al., 2007; Ngo-Duc, T. et al. 2007) to simulate river discharge during 1981-2000, 2031-2050, and 2081-2100. Simulated river discharge was converted to Discharge Probability Index (DPI), which was proposed by Yoshimura et al based on a statistical approach. The bias and uncertainty of the models are already taken into account in the concept of DPI, so that DPI serves as a good indicator of flood risk. We estimated the statistical parameters for DPI using the river discharge for 1981-2000 with an assumption that the parameters stay the same in the different climate periods. We then evaluated the occurrence of flood events corresponding to DPI categories in each 20 years and averaged them in 9 regions. The results indicate that low DPI flood events (return period of 2 years) will become more frequent in 2031-2050 and high DPI flood events (return period of 200 years) will become more frequent in 2081-2100 compared with the period of 1981-2000, though average precipitation will become larger during 2031-2050 than during 2081-2100 in most regions. It reflects the increased extreme precipitation during 2081-2100.