博碩士論文 109624601 詳細資訊




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姓名 阮雅静(Thi-Rin-Gan Nguyen)  查詢紙本館藏   畢業系所 應用地質研究所
論文名稱
(A Three-Step Time-Series Method for Assessing the Barometric Efficiency in the Donggang River Watershed, Taiwan)
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摘要(中) 氣壓效率(barometric efficiency, BE)定義為地下水位與大氣壓力之比,是地下 水文學中的一個重要估計值,它評估含水層的封閉性,並可用於估計儲水係數值。 BE 的機制為大氣壓力通過未飽和帶中的孔隙並傳遞到地下水面而影響地下水系 統。然而,原始地下水位變化是許多不同因子的組合,如何從地下水位資料提取 合適的訊號來評估 BE 是一個重要的問題。在過去的研究中,如何準確評估 BE 值 常被忽視,影響了含水層封閉性與儲水係數評估的準確性。因此,本研究提出了 三步驟時間序列分析法(three-step time-series method, TTM),用以評估與量化合理 的 BE 值。首先,將採用時間窗的移動平均法(moving average, MA)用於 BE 的 時間序列計算,找出適合 BE 評估的時間段;之後採用希爾伯特黃轉換(Hilbert- Huang Transform, HHT),將選定時間段內的地下水位和氣壓分解為幾個固有模態 函數(intrinsic mode functions, IMF);最後,使用快速傅立葉轉換法(Fast Fourier Transform, FFT)計算每個 IMF 的頻率,以確定哪個 IMF 具有氣壓訊號。依據上述 的評估和選擇程序後,便可透過選擇的地下水位和氣壓的 IMF 來計算 BE 值。本 研究使用了東港流域 8 個地下水位觀測井和 1 個氣壓觀測井的 10 分鐘採樣率資 料,並於分析中考慮了不同時間尺度進行評估與計算,以瞭解採樣率對分析結果 的影響。研究結果顯示,旱季是 BE 計算較合適的時間段,而 IMF3 中每個樣本 6 小時的時間尺度最適合進行 BE 之計算。藉由本計畫提出方法計算所得的 BE 時 空分佈成果,便可估算儲水係數值並提供地下水資源管理的評估參考。本研究提
vi
出了一個能較準確評估 BE 值的方法,結果並證明了含水層特性的不確定性,為 地下水文學領域提供了重要參考。
摘要(英) The barometric efficiency (BE), defined as the ratio of groundwater level to barometric pressure, is an important estimation in groundwater hydrology, which assesses the confinement of aquifers and can be used to estimate the storativity. The mechanism of BE states that barometric pressure propagates through porous media in the vadose zone and impacts the groundwater system. However, groundwater level variations are a combination of numerous variables embedded in the raw data. How to extract the suitable signal from the groundwater level data to assess the BE is thus a crucial issue. Accurate evaluation of the BE value was commonly ignored in the previous researches, which affects the accuracy of the aquifer confinement assessment. Therefore, this study proposed a three-step time-series method (TTM) for quantifying the BE value. The moving average (MA) method with an adopted time window was firstly applied to the time series calculation of BE to find out the suitable time period for BE assessment. Hilbert-Huang Transform (HHT) was then adopted to decompose the groundwater levels and barometric pressure into several intrinsic mode functions (IMFs) within the selected time period. Finally, the Fast Fourier Transform (FFT) approach was used to assess the frequency of each IMF to confirm which IMF has the signal of barometric pressure. After the evaluation and selection procedure, BE can be calculated by the seleceted IMF of groundwater level and barometric pressure. The data with 10- minute sampling rate from eight groundwater level observation wells along with one barometric pressure observation in the Donggang River watershed were used. Multiple time scales were also considered to check the influence of sampling rate. The study results showed that dry season is a suitable time period for BE calculation, and a time scale of six hours per sample in IMF3, calculated from HHT, is suitable for BE evaluation. By assessing the spatiotemporal distribution of BE, storativity can be estimated for groundwater resource management. This study proposed a procedure to accurately assess the BE values and demonstrated the uncertainty property of aquifers, which provided an important reference in groundwater hydrology.
關鍵字(中) ★ 氣壓效率
★ 地下水位
★ 移動平均值
★ 希爾伯特-黃轉換
★ 快速傅立葉轉換
★ 多時間尺度
關鍵字(英) ★ Barometric efficiency,
★ Groundwater level
★ Moving Average
★ Hilbert-Huang Transform
★ Fast Fourier Transform
★ Multiple time scales
論文目次 摘要 vi
Abstract viii
Acknowledgments ix
List of Contents x
List of Figures xii
List of Tables xvii
List of Abbreviations xviii
CHAPTER 1. INTRODUCTION 1
1.1. Literature review 1
1.2. Motivation and Objectives 3
1.3. Thesis structure 6
CHAPTER 2. BACKGROUND 7
2.1. Study area 7
2.2. Monitoring systems 12
2.2.1. Groundwater observation 12
2.2.2. Barometric pressure observation 14
2.3. Theory 14
2.3.1. Water Level Frequency Response Theory 14
2.3.2. Barometric Loading Analysis Theory 15
2.3.3. Barometric Efficiency 16
2.3.4. Tide Analysis Theory 18
2.3.5. Specific storage 18
CHAPTER 3. METHODOLOGY 20
3.1. Traditional method 20
3.2. A Three-step Time-series method 20
3.2.1. Moving Average 21
3.2.2. Hilbert-Huang Transform 22
3.2.3. Fast Fourier Transform 26
CHAPTER 4. RESULTS AND DISCUSSION 27
4.1. Traditional method results 27
4.2. A Three-step Time-series method results 31
4.2.1. The results of moving average 31
4.2.2. The results of Hilbert-Huang Transform 36
4.2.3. The results of Fast-Fourier Transform 39
CHAPTER 5. CONCLUSIONS 66
APPENDIX 68
REFERENCE 78

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指導教授 王士榮(Shih-Jung Wang) 審核日期 2023-1-13
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