PREDICTING FLOOD INUNDATION AREA BY RAINFALL-RUNOFF-INUNDATION MODEL EMULATOR

• SEKIMOTO Taisei

  三井共同建設コンサルタント株式会社 河川・砂防事業部 水文・水理解析部

• WATANABE Satoshi

  東京大学 大学院工学系研究科

• KOTSUKI Shunji

  千葉大学 環境リモートセンシング研究センター

• YAMADA Masafumi

  京都大学 防災研究所

• ABE Shiori

  三井共同建設コンサルタント株式会社 河川・砂防事業部 水文・水理解析部

• WATANUKI Akira

  株式会社建設環境研究所 河川計画部

Bibliographic Information

Other Title

• 降雨流出氾濫モデル・エミュレータによる浸水範囲予測

Abstract

 A rainfall-runoff-inundation model emulator was developed by machine larning using outputs from large ensemble climate simulations as a training dataset. The prediction of flood inundation area by the emulator was evaluated in the Omono river basin, which has been freaquently flooded in the past. The experimental results show that the inundation area near the river channel can be reproduced by the enulator with about 80 to 90% accuracy. We applied the machine to the actual flood inundation case in July 2017, and found that the result of prediction by the emulator is comparable to that by the results using rainfall-runoff-inundation model although the reproducibility differs according to the training data of machine learning.

Journal

• Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering)

  Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) 76 (2), I_547-I_552, 2020

  Japan Society of Civil Engineers

Keywords

• Flood
• RRI model
• Large ensemble climate simulations as a training dataset
• Emulator

Details

• CRID: 1390571704642855552
• NII Article ID: 130008122712
• DOI: 10.2208/jscejhe.76.2_i_547
• ISSN: 2185467X
• Web Site: https://www.jstage.jst.go.jp/article/jscejhe/76/2/76_I_547/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed