このアイテムのアクセス数: 184

このアイテムのファイル:
ファイル 記述 サイズフォーマット 
JDR_8(1)_167.pdf416.95 kBAdobe PDF見る/開く
タイトル: Flood Estimation and Prediction Using Particle Filters
著者: Tachikawa, Yasuto  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-1647-8899 (unconfirmed)
Noh, Seong Jin
Kim, Yeon Su
Shiiba, Michiharu
著者名の別形: 立川, 康人
キーワード: data assimilation
MPI-OHyMoS
hydrologic modeling framework
発行日: Feb-2013
出版者: Fuji Technology Press
誌名: Journal of Disaster Research
巻: 8
号: 1
開始ページ: 167
終了ページ: 168
抄録: Data assimilation methods have received increased attention to accomplish uncertainty assessment and enhancement of forecasting capability in various areas. Despite their potential, applicable software frameworks for probabilistic approaches and data assimilation are still limited because most hydrologic modeling software are based on a deterministic approach. In this study, we developed a hydrologic modeling framework for data assimilation, namely MPI-OHyMoS. While adapting object-oriented features of the original OHyMoS, MPI-OHyMoS allows user to build a probabilistic hydrologic model with data assimilation. In this software framework, sequential data assimilation based on particle filtering is available for any hydrologic models considering various sources of uncertainty originating from input forcing, parameters, and observations. Ensemble simulations are parallelized by a message passing interface (MPI), which can take advantage of high-performance computing (HPC) systems. Structure and implementation processes of data assimilation via MPI-OHyMoS are illustrated using a simple lumped model. We apply this software framework for uncertainty assessment of a distributed hydrologic model in synthetic and real experiment cases. In the synthetic experiment, dual state-parameter updating results in a reasonable estimation of parameters to cover synthetic true within their posterior distributions. In the real experiment, dual updating with identifiable parameters results in a reasonable agreement to the observed hydrograph with reduced uncertainty of parameters.
著作権等: (C) 2013 Fuji Technology Press Co, . Ltd.
この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
This is not the published version. Please cite only the published version.
URI: http://hdl.handle.net/2433/172457
関連リンク: http://www.fujipress.jp/JDR/DSSTR00080001.html
出現コレクション:学術雑誌掲載論文等

アイテムの詳細レコードを表示する

Export to RefWorks


出力フォーマット 


このリポジトリに保管されているアイテムはすべて著作権により保護されています。