Ensemble flood simulation for a small dam catchment in Japan using 10 and 2km resolution nonhydrostatic model rainfalls

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This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMANHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a highresolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMANHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the positionshifted rainfalls shows much better results than the original ensemble discharge simulations.




Kobayashi, K., Otsuka, S., Apip, & Saito, K. (2016). Ensemble flood simulation for a small dam catchment in Japan using 10 and 2km resolution nonhydrostatic model rainfalls. Natural Hazards and Earth System Sciences, 16(8), 1821–1839. https://doi.org/10.5194/nhess-16-1821-2016

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