Takunori KOGURE
Endeavor for Synthesizing Storage Function Model by Geographical Data
Minjiao Lu
Recently, the disasters in the medium- or small-sized river basin caused by typhoons and rain front occurred very frequently. The disaster prevention measures of the river are hurried in each place. A method which makes the runoff analysis possible in ungauged or poorly gauged basins becomes necessary even though its accuracy is somewhat lower.
The storage function model is a rainfall runoff model widely used in many river basins in Japan. This model needs comparatively few data. If we can calibrate some of the parameters, This model becomes available in ungauged or poorly gauged basins. The method to get the parameters of the storage function model is called the synthesizing. However, as for these methods, problems in the practical use are pointed out because the basin area is limited.
This study is aimed at the synthesizing parameter estimate equation of the storage function model which can used in a medium- or small-sized river basins with few data. In this study, the River Classification Indices are used as a newly parameter estimate equation variable. Applying this equation to Tsunekanebashi basin in Doki river, results as good as the average of the whole events used in derivation of the equation are obtained. Consequently it was proved that practical use was possible to some extent.
Keywords: Synthesizing Storage Function ModelĄ¤Geographical Data
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