Improvement of flow and water quality simulation using data assimilation and development of parameter optimization method in water quality model
Project/Area Number |
25709042
|
Research Category |
Grant-in-Aid for Young Scientists (A)
|
Allocation Type | Partial Multi-year Fund |
Research Field |
Hydraulic engineering
|
Research Institution | Osaka University |
Principal Investigator |
Irie Masayasu 大阪大学, 工学(系)研究科(研究院), 准教授 (00379116)
|
Project Period (FY) |
2013-04-01 – 2017-03-31
|
Project Status |
Completed (Fiscal Year 2016)
|
Budget Amount *help |
¥23,660,000 (Direct Cost: ¥18,200,000、Indirect Cost: ¥5,460,000)
Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2015: ¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2014: ¥11,440,000 (Direct Cost: ¥8,800,000、Indirect Cost: ¥2,640,000)
Fiscal Year 2013: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
|
Keywords | 4次元変分法 / アンサンブルカルマンフィルタ / データ同化 / 大阪湾 / 多項式カオス展開 / 4D-Var / 水質シミュレーション / ROMS / 水質モデル / 沿岸域 / 沿岸域の環境 / 流動水質シミュレーション / 環境水理学 / 海洋レーダ / 沿岸域の流動 / 流動水質モデル |
Outline of Final Research Achievements |
In this research project, we performed data assimilation using the four-dimensional variational method and the Ensemble Kalman Filter method (EnKF) to obtain the better representation of flow and water quality distributions in coastal areas and to develop the estimation method of various model parameters and conditions used in the water quality model. We assimilated data of surface current velocity collected by HF radar and temperature, salinity, chlorophyll, and dissolved oxygen (DO) collected by Osaka Bay Water Quality Automatic Observation System. Both the four-dimensional variational method and the ENKF significantly improved the distributions of water quality horizontally and vertically. In addition, methods for estimating model parameters in the water quality model using both data assimilation methods was developed and evaluated.
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Report
(5 results)
Research Products
(29 results)