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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/52592

    Title: 以HHT研究氣候變遷對於濁水溪流域降雨之影響
    Other Titles: A study for influence of climate change on precipitation in Zhuoshuixi watershed based on HHT
    Authors: 林昱廷;Lin, Yu-ting
    Contributors: 淡江大學水資源及環境工程學系碩士班
    虞國興;Yu, Gwo-hsing
    Keywords: 希爾伯特-黃轉換;;氣候變遷;降雨;時頻分析;Hilbert-Huang transform;Entropy;Climate Change;precipitation
    Date: 2010
    Issue Date: 2010-09-23 17:58:04 (UTC+8)
    Abstract: 本研究之主要目的係使用目前最新的時頻分析方法-希爾伯特-黃轉換(Hilbert-Huang Transform, HHT)做為主要時頻分析工具,並將時頻圖以熵值量化,藉以探討氣候變異是否對濁水溪流域之降雨產生影響。
    This study investigated the application of Hilbert-Huang Transform (HHT) in detecting changes in precipitation patterns brought by global climate change. Marginal frequency spectrum analysis, marginal time spectrum analysis, and calculation of time-frequency entropy were applied to precipitation data from Zhuoshuixi watershed, located in Taiwan, to detect and identify possible changes in precipitation patterns. In addition, additional hydrological data such as effective mean rainfall intensity and the distribution of precipitation were also analyzed as other approaches of showing the effects of climate change. As a method of reference for comparison with HHT, the conventional null hypothesis tests were also applied to verify possible changes in the amount of precipitation in different months of the year.

    In the null hypothesis tests, significance values (P-value) were determined to signify the degree of climate change impact on the amounts of precipitations in different months of the year. The results of the null hypothesis tests suggested that the changes in precipitation patterns are only statistically significant in the month of February. In comparison, Hilbert-Huang Transform (HHT) plus the inspection of additional hydrological data were able yield more information about changes in precipitation patterns. Time-frequency entropy value was found to be small for concentrated precipitation with less uncertainty, while large for distributed precipitation with higher uncertainty.
    Appears in Collections:[水資源及環境工程學系暨研究所] 學位論文

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