Ensemble flash flood predictions using a high-resolution nationwide distributed rainfall-runoff model: case study of the heavy rain event of July 2018 and Typhoon Hagibis in 2019

Abstract

The heavy rain event of July 2018 and Typhoon Hagibis in October 2019 caused severe flash flood disasters in numerous parts of western and eastern Japan. Flash floods need to be predicted over a wide range with long forecasting lead time for effective evacuation. The predictability of flash floods caused by the two extreme events is investigated by using a high-resolution (~ 150 m) nationwide distributed rainfall-runoff model forced by ensemble precipitation forecasts with 39 h lead time. Results of the deterministic simulation at nowcasting mode with radar and gauge composite rainfall could reasonably simulate the storm runoff hydrographs at many dam reservoirs over western Japan for the case of heavy rainfall in 2018 (F18) with the default parameter setting. For the case of Typhoon Hagibis in 2019 (T19), a similar performance was obtained by incorporating unsaturated flow effect in the model applied to Kanto Region. The performance of the ensemble forecast was evaluated based on the bias ratios and the relative operating characteristic curves, which suggested the higher predictability in peak runoff for T19. For the F18, the uncertainty arises due to the difficulty in accurately forecasting the storm positions by the frontal zone; as a result, the actual distribution of the peak runoff could not be well forecasted. Overall, this study showed that the predictability of flash floods was different between the two extreme events. The ensemble spreads contain quantitative information of predictive uncertainty, which can be utilized for the decision making of emergency responses against flash floods.

Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop

“…Flash flood modelling [CB-P, MY-P, TS-P] is also a key area that benefits from (and requires) high resolution models due to the ability to resolve convection and capture the variability in soil moisture (Loval et al, 2019;Hapuarachchi et al, 2011). Sayama et al [TS-P] showed that a 150 m resolution national rainfall-runoff model was able to predict two flash flood events reasonably well, although with large uncertainty in some locations due to the 5 km meteorological forecast being unable to confidently predict the location of the storm (Sayama et al, 2020). Sandu [IS-K] noted how high-resolution models made scaling effects and computational efficiency key considerations for current and future projects ([GS-P], Bauer et al, 2021;Donahue et al, 2020;Yepes-Arbós et al, 2022).…”

A methodological framework for the evaluation of short-range flash-flood hydrometeorological forecasts at the event scale

“…After an initial analysis of the performance of the three rainfall forecast products, the evaluation procedure proposed in this paper focused on the capacity of the hydrological forecasts to anticipate the exceedance of selected discharge thresholds. Several authors have suggested using thresholds and contingency tables to perform a robust regional evaluation of hydrological 535 ensemble forecasts (Silvestro and Rebora, 2012;Anderson et al, 2019;Sayama et al, 2020). In this study, a step further is proposed towards (i) focusing only on the rising limb phase of the flood hydrograph -i.e.…”

River discharge prediction for ungauged mountainous river basins during heavy rain events based on seismic noise data

“…The RRI is a two-dimensional model that has the advantage of simultaneously modeling runoff and flood inundation (Sayama et al 2012(Sayama et al , 2020P.C. et al 2020a, 2020bNguyen et al 2021).…”