| Project/Area Number |
18K04370
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 22040:Hydroengineering-related
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| Research Institution | Okayama University |
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Principal Investigator |
YOSHIDA KEISUKE 岡山大学, 環境生命科学研究科, 准教授 (50436721)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2019: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 航空レーザー測深 / 河道の地被条件 / 洪水位の数値予測 / ALB / 植生消長 / 河床変動 / 物理環境評価 / データ同化 |
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| Outline of Final Research Achievements |
Woody vegetation establishing thickly in rivers has recently posed a threat to our lives because of enhancing the risk of river flooding. For accurate risk estimation, this study developed a methodology for extracting efficiently the data of both river bed levels and vegetation conditions along a long river section, using techniques of airborne laser bathymetry (ALB) in practical use. For more precise numerical simulations of flood water levels, this study also proposed a simple sub-model that incorporates the mechanism of vegetation wash-out attributable to flood flows. Results showed that the method yields useful data from ALB in the targeted reach of the Asahi River, Japan, comparing the field observation data. Results also showed that the sub-model performs well for reproduction of actual vegetation situation observed after the Asahi River flooding that occurred during the 2018 western Japan heavy rainfall event.
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| Academic Significance and Societal Importance of the Research Achievements |
近年，河川の洪水氾濫は河道弱部より生じており，長区間の河道の中で洪水疎通能力が低下し，また河川堤防が局所的に低下している箇所を早期に把握することが求められる．本研究の成果より，航空レーザー測深によって河川における広域・高解像度の植生特性量や水陸連続の地形および地被状況が一度に把握できる．その結果，研究成果は洪水位の広域・高精度な予測のみならず，今後，河床変動や植生動態の解析においても有用なデータとなることが期待される．
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