2006 Fiscal Year Final Research Report Summary
Development of downscaling technique of global hydrological predicted data and reduction of uncertanty of prediction
| Project/Area Number |
16360250
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
水工水理学
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| Research Institution | Mie University |
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Principal Investigator |
KUZUHA Yasuhisa Mie University, Graduate School of Bioresources, Professor, 大学院生物資源学研究科, 教授 (50373220)
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| Co-Investigator(Kenkyū-buntansha) |
KOMATSU Yosuke Rissho University, Geo-Environmental Science, Senior Lecturer, 地球環境科学部, 講師 (90386516)
KISHII Tokuo Kanazawa Institute of Technology, College of Environmental Engineering and Architecture, Professor, 環境建築学部, 教授 (30360374)
SHO Kenjiro Nagoya Institute of Technology, Graduate School of Engineering, Lecturer, システムマネジメント工学科, 助手 (40283478)
IIZUKA Satoshi National Research Institute for Earth Science and Disaster Prevention, Storm, Flood, and Landsilide Research Department, Senior Researcher, 総合防災研究部門, 主任研究員 (40414403)
NAKAGAWA Katsuhiro National Institute of Information and Communieation Technology, Okinawa Subtropical Environment Remote Sensing Center, Senior Researcher, 沖縄亜熱帯計測技術センター, 主任研究員 (80359009)
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| Project Period (FY) |
2004 – 2006
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| Keywords | PUB / Stochastic model / Regional Flood Frequency Analysis / Scaling / Uncertainty / goodness-of-fit / IDF curve / Downscaling |
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| Research Abstract |
The main objectives of this project are as follows;
(1) Development of prediction technique by which one can predict meteorological and hydrological data in ungauged or poorly-gauged basins (PUB).
(2) Development of method for reduction of various kind of uncertainty in terms of prediction.
As for (1), we tried to downscale relatively (spatially / temporally) coarse data to more fine data. 'Regional flood frequency analysis' is appropriate for the downscaling. Moreover, application of scaling is also effective. These techniques are included in so-cold 'statistical analyses'. We tried to use MM5 (meso-scale meteorological program) and found that combination of statistical analysis and meteorological program is more effective (unpublished). Moreover, we developed new method by which goodness-of-fit is evaluated when IDF curve is obtained, namely, when one evaluate which stochastic distribution is appropriate for hydrological data.
As for (2), we constructed new observation station in Kanto district. However, we have not finished analysis of these data at the stage.
Moreover, we obtained a lot of results on scaling by which one can downscale spatially coarse data. Especially, we constructed new rainfall-runoff model and obtained new result on scaling by using the model. Scaling is potential appropriate method for PUB.
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