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  • 學位論文

低尾線性動差法於低流量頻率分析之應用

Use of LL-moments Method for Low-Flow Frequency Analysis

指導教授 : 虞國興

摘要


近年來全球暖化及氣候變遷等因素,極端洪水或枯旱現象日趨頻繁,旱澇交替現象愈來愈明顯,週期也愈來愈短,發生乾旱現象過於頻繁時,常會面臨水資源短缺或嚴重匱乏之窘況衝擊。水文統計或頻率分析之方法由來已久,乾旱分析方面受限於乾旱現象為持續性水文量偏低之極端事件,無法以一般洪水頻率分析之方式進行。極端低流量乾旱事件乃屬特殊水文頻率分析方法,應適度增加分析權重,來因應近年氣候變遷極端事件加劇頻繁之現象。 本研究引入低尾線性動差法(LL-moments)及通用極端值分布(generalized extreme value, GEV),針對加入極端低流量值修正權重係數(m)之影響進行探討,研究中,選取淡水河、大甲溪、高屏溪、荖濃溪、立霧溪及秀姑巒溪流域內共計9個流量測站,並利用不同GEV參數為 、 及 共七種不同參數組合,進而探討LL-moments適用時機,最後建議LL-moments之修正權重係數妥適性。 由研究結果顯示,資料長度為29時,加入一筆極端值資料( 0.3, 0.5, 0.9),不論是 100年或200年,以m= 2 ,3可獲致最佳之參數推估結果。惟當資料長度為49時,加入一筆 200年極端值資料之參數推估結果,均較加入 100年之結果為佳。同時,由於資料長度較長,即使已修正權重至m=4仍然無法推估到極端值其真正之參數值,表示資料長度愈長需要更高的修正權重係數(m),才能反應因極端水文事件發生所造成之低流量頻率分析之影響。因此,建議本方法未來可作為低流量頻率分析與水文情勢研判之參考與應用。

並列摘要


In recent decades, the frequency of extreme flood and drought events has increased in many parts of the world, signifying a shift in global climatic pattern. Conventional flood frequency analysis methods are not readily applicable to drought frequency analysis due to large variability in drought duration. The low-end linear moment method (LL-moments), which assign correction factors (m) to extreme value data, had been suggested for the analysis of low flow observations. In this study, the LL-moments is applied to the fitting of empirical time series data from nine stream gages in Taiwan to the general extreme value (GEV) distribution model. Three out of the nine sets of data demonstrated good fit with the general extreme value distribution (GEV) model. LL-moments method was then reapplied to simulated time series generated from known GEV model to investigate the effect of varying the value of correction factors on the reliability of parameter estimation. It was found that for data length less then 29, applying the correction factor of 2 or 3 yielded good parameter estimations, even when an extreme value data of return period of 100 or 200 years was added to the time series. For data length 49, applying the correction factor of 2, 3 or even 4 did not yield good parameter estimation. Further study about applying correction factor greater than 4 would be recommended when data length is greater than 49.

參考文獻


1.張宗烜,2009,低尾線性動差法於乾旱頻率分析之應用,淡江大學水資源及環境工程學系碩士論文。
5.楊志傑,2006,以線性動差法探討台灣地區乾旱頻率分析,淡江大學水資源及環境工程學系碩士論文。
6.蕭政宗、楊志傑,2006,台灣地區之區域乾旱頻率分析,農業工程學報,第52卷,第2期,第83-101頁。
11. Greenwood, J. A., Landwehr, J. M., Matalas N. C., and Wallis J. R., October, 1979, Probability weighted Moments: Definiition and Relation to parameters of Several Distributions Expressable in Inverse Form. Water Resources Research, 15, 1049-1054.
15. Landwehr, J. M., Matalas N. C., and Wallis J. R., 1979, Probability-weighted Moments Compared with Some Traditional Techniques in Estimating Gumbel Parameters and Quantiles. Water Resources Research, 15, 1055-1064.

被引用紀錄


張家芸(2012)。高尾線性動差法於氣候變遷下極端暴雨頻率分析之研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2012.01315

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