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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/105861

    Title: 應用雷達定量降水於水庫入庫流量推估模式之研究
    Other Titles: Studies on reservoir inflow estimating model by using the radar-based quantitative precipitation
    Authors: 郭秀筠;Kuo, Hsiu-yun
    Contributors: 淡江大學水資源及環境工程學系碩士班
    虞國興;蘇騰鋐;Yu, Gwo-hsing;Su, Teng-hung
    Keywords: 水庫入庫流量推估模式;逐步迴歸分析;雷達定量降水;Reservoir Inflow Estimating Model;Stepwise Regression Analysis;Radar-based Quantitative Precipitation Estimation
    Date: 2015
    Issue Date: 2016-01-22 15:07:07 (UTC+8)
    Abstract: 近年來,颱風及豪雨發生之頻率及強度日益增加,降雨季節分配不均情況更加嚴重,且防洪程度會因降雨強度增強而降低,使洪災發生機率提高。在颱風侵襲之過程中,利用颱洪事件之總累積雨量及不同平均降雨強度資料,以快速掌握水庫入庫流量,進而爭取水庫操作上之時效,提供操作人員最即時水庫調節之參考。
    In recent years, the typhoons and extreme rainfall days increases, the precipitation is unsteady in different places and during different seasons, and it usually concentrates in moist season. The typhoon causes results in severe flood inundation. During the typhoon hit, using the rainfall intensity data of typhoon flood events, to quickly grasp the reservoir inflow, it is expected that results of this study could be used for online reservoir operation in the future.
    In this study, we focus on the Shihmen reservoir upstream catchment area, using the relationship of rainfall factor and reservoir inflow to separately establish of cumulative inflow before peak flow, cumulative inflow after peak flow, total cumulative inflow and peak inflow estimating models. The study use the stepwise regression analysis to built model, with 95% confidence interval and cross-validation test the model, and finally using the radar-based quantitative precipitation estimation data verify the model.
    The results shows that using the stepwise regression analysis to establish reservoir inflow estimating model, the t-test are less than 0.05. The study found that four kinds of inflow are related to the total cumulative rainfall factor, and adding the average rainfall intensity factor, its coefficient of determination R2 value of 0.85 or more are up to. In this study, the cross-validation results showed that only three events are extreme value, the other 30 events of results are satisfactory.
    In this study, we use the radar-based quantitative precipitation estimation data in 4 reservoir inflow estimating models, the results shows that the peak inflow validation results is the four kinds of best estimate type.
    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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