| Budget Amount *help |
¥2,300,000 (Direct Cost: ¥2,300,000)
Fiscal Year 1997: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1996: ¥1,700,000 (Direct Cost: ¥1,700,000)
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| Research Abstract |
In the 1st paper, a method for estimating the probable 1-hour rainfall based on time concentration of heavy rainfall is proposed. The method makes use of the Slade type III normal transformation approach and estimates are obtained from the frequency analysis of time concentration of heavy rainfall. By knowing how heavy rainfalls are concentrated, it would be possible to select a suitable type of 1-hour rainfall to be used for the design of hydraulic structures. Although the present work focuses on 1-hour rainfall, the procedure presented herein can easily be used for a wide range of rainfall duration.
The time concentration C were transformed using the same equation but allowing a limit greater than 1. In addition, the characteristics of the parameters in the equation was discussed. It appears that the probable values of the time concentration and maximum depth of 1 hour rainfall, which were estimated based on the method presented herein were better estimates than those previously obtai
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ned from the first method especially for 24 hours rainfall of less than 300 mm.
By the 2nd paper, using the normal variables which are transformed from the time concentration of a rainfall based on the annual maximum 24-hours rainfall depth, a method is proposed to estimate the annual maximum 1-hour rainfall depth. Comparing the observed annual maximum 1-hour rainfall depth and the estimated one, we proposed two equations and discussed how to obtain the normal variable and how to determine its upper and lower limit values in order to estimate the annual maximum 1-hour rainfall depth. Methods are much different from the former studies on the point of view for obtaining the annual maximum 1-hour rainfall depth. Utilizing the estimated annual maximum 1-hour rainfall depth, it is possible to estimate the return period of probable one. Estimated cumulative probability distributions have reproduced any of the observed one with quite good agreement. To utilize this method, however, it is necessary to know the statistical parameters in advance. Then, provided the annual maximum 24-hours rainfall depth for any district in Japan, it is possible to estimate the annual maximum 1-hour rainfall depth without the observed one.
Using the available annual maximum 1-hour rainfall from the Japan Meteorological Stations (120 stations), the 3rd paper presents the calculated probability range and the necessary regional parameters required for the Gumbel distribution to generate the variable x for estimating the annual maximum 1-hour rainfall. In addition, some regional distribution characteristics of the parameters are described. The estimated annual maximum depths for each station were in good sgreement with the observed ones with the same return period. Thus, the general suitability and wide applicability of the method was verified. Less
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