| Summary: | 碩士 === 國立臺灣大學 === 生物環境系統工程學研究所 === 104 === The equation for evaluating rainfall kinetic energy currently used in Taiwan is not derived from the local rainfall data. Because rainfall kinetic energy is quite related to the region, it is necessary to develop an equation of rainfall kinetic energy for each area. The main purposes of this study are to measure the rain drop size distribution in northern Taiwan using disdrometer and to establish the equation for evaluating rainfall kinetic energy using the measured data.
In this study, the data of rainfall and rain drop size distribution collected at three observation stations, namely, National Central University station, Xiayun station and Feitsui station, using disdrometer from 2012 to the Jun. of 2016 were used to evaluate the rainfall kinetic energy. To accomplish this, three methods for evaluating rainfall kinetic energy were applied. The first is the method of energy per unit volume (KEmm ), a conventional method, and its coefficient of determination( R2) between rainfall kinetic energy and rainfall intensity is approximately 0.6. The second is the method of energy per unit time (KEtime ), a relatively newly developed method, and the coefficient of determination( R2) between rainfall kinetic energy and rainfall intensity is greater than 0.97. The third is the method using attribute characteristics such as drop size distribution, precipitation types and the rainfall intensity to categorize the rainfall events and develop the KE-I relationship. While the rainfall is categorized with the drop size distribution (DSD), the KEmm remains constant over various rainfall intensities, and the results are very good. However, while the precipitation types and the rainfall intensity are used for categorizing, the results are not satisfactory.
In this study, several methods are used to develop the equations for evaluating rainfall kinetic energy using the local rainfall data. Among these, the results of the KEtime method and the third method using the drop size distribution (DSD) to categorize the rainfall are much better. Accordingly, the findings in this study are expected to be useful for evaluating rainfall kinetic energy and rainfall erosion index in the future.
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