日本地球惑星科学連合2021年大会

講演情報

[E] ポスター発表

セッション記号 A (大気水圏科学) » A-HW 水文・陸水・地下水学・水環境

[A-HW20] 水循環・水環境

2021年6月5日(土) 17:15 〜 18:30 Ch.07

コンビーナ:林 武司(秋田大学教育文化学部)、福士 圭介(金沢大学環日本海域環境研究センター)、榊原 厚一(信州大学理学部理学科)、山崎 大(東京大学生産技術研究所)

17:15 〜 18:30

[AHW20-P05] Hydrological Hindcasts and Parameterizations for Flash Floods Real-Time Forecasting in the Chugoku Region of Japan

*Josko Troselj1、Han Soo Lee1 (1.Graduate School of Advanced Science and Engineering, Hiroshima University)

キーワード:extreme river discharge, 2018 Japanese flash floods, CDRM hydrological model, SCE-UA optimization method, real-time flood forecasting

As a result of climate change, unprecedented heavy rainfall disasters are increasingly occurring worldwide. It is therefore important to develop Early Warning Systems for real-time forecasting of extreme river water levels and discharges. This study applies the Cell Distributed Runoff Model version 3.1.1 (CDRM) hydrological model calibrated by the Shuffled Complex Evolution optimization method developed at the University of Arizona (SCE-UA) for seven first-class river basins in the Chugoku region of Japan, to obtain hydrological parameterizations and hindcasts of river mouth discharge hydrographs during the Heavy Rainfall Event of in July 2018. This study evaluates hypothesis that calibrated river basin parameters from historical extreme rainfall-induced extreme river discharge events can be used to accurately forecast extreme river discharge hydrographs from future events of similar scales by introducing an innovative historical extreme rainfall event classification methodology based on similarities between the events on the way that the classification criterion is meaningful for future real-time forecasting application. Using this approach, this study produced cumulative ensemble mean validation results with very high reproducibility metrics for the two evaluated methods, using 5 and 7 calibrated parameters. This methodology can therefore be used for accurate real-time forecasting of future flash floods caused by extreme rainfall in the region and similarly also worldwide.