Kosei Yamaguchi

Impact Assessment of Uncertainty Propagation of Ensemble NWP Rainfall to Flood Forecasting with Catchment Scale

The common approach to quantifying the precipitation forecast uncertainty is ensemble simulations where a numerical weather prediction (NWP) model is run for a number of cases with slightly different initial conditions. In practice, the spread of ensemble members in terms of flood discharge is used as a measure of forecast uncertainty due to uncertain precipitation forecasts. This study presents the uncertainty propagation of rainfall forecast into hydrological response with catchment scale through distributed rainfall-runoff modeling based on the forecasted ensemble rainfall of NWP model. At first, forecast rainfall error based on the BIAS is compared with flood forecast error to assess the error propagation. Second, the variability of flood forecast uncertainty according to catchment scale is discussed using ensemble spread. Then we also assess the flood forecast uncertainty with catchment scale using an estimation regression equation between ensemble rainfall BIAS and discharge BIAS. Finally, the flood forecast uncertainty with RMSE using specific discharge in catchment scale is discussed. Our study is carried out and verified using the largest flood event by typhoon “Talas” of 2011 over the 33 subcatchments of Shingu river basin (2,360 km2), which is located in the Kii Peninsula, Japan.

Early Detection of Baby-Rain-Cell Aloft in a Severe Storm and Risk Projection for Urban Flash Flood

In July 2008, five people were killed by a tragic flash flood caused by a local torrential heavy rainfall in a short time in Toga River. From this tragic accident, we realized that a system which can detect hazardous rain-cells in the earlier stage is strongly needed and would provide an additional 5 to 10 min for evacuation. By analyzing this event, we verified that a first radar echo aloft, by volume scan observation, is a practical and important sign for early warning of flash flood, and we named a first echo as a “baby-rain-cell” of Guerrilla-heavy rainfall. Also, we found a vertical vorticity criterion for identifying hazardous rain-cells and developed a heavy rainfall prediction system that has the important feature of not missing any hazardous rain-cell. Being able to detect heavy rainfall by 23.6 min on average before it reaches the ground, this system is implemented in XRAIN in the Kinki area. Additionally, to resolve the relationship between baby-rain-cell growth and vorticity behavior, we carried out an analysis of vorticity inside baby-rain-cells and verified that a pair of positive and negative vertical vortex tubes as well as an updraft between them existed in a rain-cell in the early stage.