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タイトル
  • ja 長期水循環に基づく流域の湿潤状態を考慮した洪水流出解析の研究
  • en RESEARCH ON FLOOD RUNOFF ANALYSIS THAT TAKES INTO ACCOUNT SOIL WATER STORAGE ESTIMATED BY LONG-TERM HYDROLOGIC PROCESS
作成者
    • ja 谷口, 陽子 en TANIGUCHI, Yoko ja-Kana タニグチ, ヨウコ
    • ja 中津川, 誠 en NAKATSUGAWA, Makoto ja-Kana ナカツガワ, マコト
    • ja 臼谷, 友秀 en USUTANI, Tomohide ja-Kana ウスタニ, トモヒデ
アクセス権 open access
権利情報
  • ja © 2016 土木学会
主題
  • NDC 517
  • Other en long-term hydrological assessment model considering snow processes
  • Other en soil water storage
  • Other en storage routing model
  • Other en parameter optimization
  • Other en parameters fixed
内容注記
  • Other application/pdf
  • Abstract en This study aims at improving the accuracy of a currently used flood runoff model by taking into account the soil water storage (SWS) before flooding and continuously changing the effective rainfall input into the model. In this study, SWS was estimated by using a "long-term hydrological assessment model considering snow process" (LoHAS) first. Then, the runoff rate, which is changing hour to hour, was determined by using the estimated SWS as the initial value of the runoff. Next, the estimated effective rainfall was input into the storage function model. Compared to the accuracy of the current flood runoff model, the accuracy of the new model in terms of the reproduced hydrograph was improved. The accuracy in reproducing the second peak of a two-peak flood and in reproducing flood runoff caused by snowmelt and rainfall was particularly improved.
出版者 ja 土木学会
日付
    Issued2016
言語
  • jpn
資源タイプ journal article
出版タイプ VoR
資源識別子 HDL http://hdl.handle.net/10258/00010081 , URI https://muroran-it.repo.nii.ac.jp/records/10134
関連
  • isIdenticalTo NAID 130005312032
  • isIdenticalTo DOI https://doi.org/10.2208/jscejhe.72.I_163
  • isVersionOf URI https://www.jstage.jst.go.jp/article/jscejhe/72/4/72_I_163/_pdf/-char/ja
収録誌情報
    • EISSN 2185-467X
      • ja 土木学会論文集B1（水工学） en Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering)
      • 巻72 号4 開始ページ163 終了ページ168
ファイル
コンテンツ更新日時 2024-01-12