2004 Fiscal Year Final Research Report Summary
Prediction for disaster based on Rader rain gage and characteristics of heavy rain in Chugoku region.
| Project/Area Number |
14550513
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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 |
水工水理学
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| Research Institution | HIROSHIMA UNIVERSITY |
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Principal Investigator |
WATANABE Akihide Hiroshima University, Graduate School of Engineering, Associate Professor, 大学院・工学研究科, 助教授 (00240474)
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| Co-Investigator(Kenkyū-buntansha) |
FUKUOKA Shoji Chuo University, Research and Development Initiative, Professor, 研究開発機構, 教授 (30016472)
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| Project Period (FY) |
2002 – 2004
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| Keywords | Hiroshima disaster in 1999 / heavy rain / prediction for disaster / Rader rain gage / GMS images / GPV data / cold front lines / tank model |
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| Research Abstract |
(1)Moving velocity vectors of clouds in GMS image were obtained by using PIV method. From divergence and rotation of these vectors, positions of front lines were cleared. There were front lines from GMS image at heavy areas in Rader rain gage. Hiroshima disaster in 1999 was caused by heavy rain. It was caused by the convergence due to front lines and geometric conditions. This disaster occurred at small-scale area. Therefore, it is shown that the information of Rader rain gage is significance for countermeasure against disaster due to the heavy rain.
(2)Numerical simulation for wind velocities over the Chugoku region based on GPV data was performed. Temporal changes in converging areas of ground wind were cleared. From this analysis, convergence due to geometric condition of mountains and strong velocity area were found.
(3)Multi-tanks model to predict soil moisture based on Rader rain gage for small-scale area was developed and its validity for prediction was examined from runoff analysis by this model. As the result of analyzing the hazard potential index expressed by the soil moisture at Yahata and Kure area, it is shown that disaster due to the heavy rain will be predicted by using this model.
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Research Products
(6 results)
