| Project/Area Number |
07660322
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Irrigation, drainage and rural engineering/Rural planning
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| Research Institution | Okayama University |
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Principal Investigator |
NAGAI Akihiro Okayama University, Faculty of Environmental Science and Technology Department of Environmental Management Engineerign, Professpr, 環境理工学部, 教授 (80093285)
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| Project Period (FY) |
1995 – 1997
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| Project Status |
Completed (Fiscal Year 1997)
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| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1997: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1996: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1995: ¥800,000 (Direct Cost: ¥800,000)
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| Keywords | Flood Forecasting / Real-Time Forecasting / Long-and Short-Term Runoff Model / Tank Model / Reservoir Operation / Rainfall Forecasting / 渇水予測 / 流水管理 / 流出解析 / 水文観測 |
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| Research Abstract |
Main results obtained in this study are as follows :
1. A questionnaire on actual circumstances of reservoir operation was carried out in cooperation with government agencies. It is outlined by summarizing the information on 201 reservoirs with catchment over 50km^2 that real-time forecasting up to 3 hours ahead is of critical importance for flood flow, and that runoff models are used for flood forecasting in about half of the reservoirs, but the filtering techniques are rarely used in actual reservoir operation.
2. In order to examine the performance of Long-and Short-Term Runoff model (LST-II) and Tank model used in real-time flood forecasting, both runoff models were applied to the data of 18 years (1979-1996) observed in the Kuroki Dam basin. It is shown that observed hydrographs both in long-term runoff and flood runoff were simulated with good accuracy by both runoff models.
3. Such filtering techniques as extended Kalman filter, statistical linearization techniques and back calculation method were applied to real-time flood forecasting with lead time of 1 and/or 3 hours in the Kuroki Dam basin. The results of 19 floods in the basin demonstrate that more accurate flood prediction is attained by adopting the filtering techniques, and that the accuracy evaluated by relative error of predicted discharge by each technique is almost same.
4. The performance of several methods for rainfall prediction in real-time flood forecasting was compared by using flood data in the Kuroki Dam basin. It is shown that the simplest method, in which future rainfall are assumed to be constant with the present intensity, gives best results, and that setting the limitations of values of coefficients is necessary for applysing the AR (auto-regressive) method.
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