博碩士論文 104690002 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:8 、訪客IP:107.21.85.250
姓名 楊筑方(Chu-Fang Yang)  查詢紙本館藏   畢業系所 國際研究生博士學位學程
論文名稱 以寬頻地震儀及分壓計之波形分析環境變動過程:與流體力學相關
(Broadband Seismic and Differential Pressure Gauge Waveform Analysis of Environmental Processes: Implication of Hydrodynamics)
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摘要(中) 摘要

偏遠地區觀測資料的缺乏為環境監測困難因素之一。高敏感度現代地震觀測儀器記錄的連續波形反應環境演化過程。此種環境訊號或許能提供有用之觀測資料。本研究利用寬頻地震儀及海底分壓計所記錄的環境訊號,探討與流體運動相關之環境過程,並舉三種於台灣及其附近海域所觀測之環境訊號為例:寬頻地震儀觀測之河川水位水壓造成的地傾訊號、海底地震儀觀測之紊流擾動訊號,以及海底分壓計感測之海洋內波引起的溫度波動。

範例一,由台灣寬頻地震網(Broadband Array in Taiwan for Seismology;BATS)之馬仕(MASB)測站資料顯示,頻率< 0.3 mHz的傾斜訊號振幅與當地降水量及附近河川之水位高度呈現正相關。推測此訊號是由於豪雨期間,測站附近河川水位增加,造成荷重,進而地表變形。利用此地傾訊號之波形以經驗格林函數(empirical Green’s function;eGF)方法可成功定量豪雨期間之降水時間序列。範例二,海底地震儀(Ocean bottom seismometer;OBS)及繫纜溫度計串(Thermistor string;T-string)組合之密集陣列觀測資料顯示,OBS感測之動能變化量與T-string計算之紊流動能消散率相關。推測OBS觀測的訊號是由位於三千公尺深之海洋內波破碎引起的紊流所導致。陣列方法分析結果顯示,由颱風引起之慣性內波遇大陸斜坡地形而破碎,其產生之紊流擾動由陣列北北東方下坡處向南南西方上坡處以0.2至0.5 m s^-1之速度移動。而陣列內的小尺度地形亦激起局部的內波破碎及小尺度的紊流運動,並導致陣列內各OBS記錄之紊流訊號有不同程度的時空變化。範例三,海底分壓計(Differential pressure gauge;DPG)陣列觀測記錄顯示,介於0.002至0.1 mHz之低頻DPG訊號與鄰近溫度探針測量之溫度變化有顯著正相關。推測此訊號是由深海內波引起之環境溫度變化傳導至分壓計內傳感器所造成。由陣列分析方法得知,通過此陣列之海洋內波多數來自於西北、北至東北方,以0.13至2 m s^-1之速度行進,其中亦有於陣列內攪動及震盪的小尺度內波及紊流運動。

一系列的研究結果顯示,藉由分析地震觀測儀器記錄之環境訊號有助於了解大氣圈、水圈及岩石圈間交互作用的過程,並提供額外觀測資料,測量及量化此類環境過程。若更進一步地應用這些環境訊號,過去的資料紀錄透露環境變遷的年季變化,而即時資料有利於自然環境監測。
摘要(英) Abstract

Lack of observations in remote areas is a problem for monitoring the earth environments comprehensively. Environmental signals recorded by high-sensitivity modern seismic instruments may help shed light on observing both near- and far-field environmental processes. This study presents three examples of hydrodynamic environmental processes using environmental signals from Taiwan, fluvial water loads-induced tilt signals, ocean turbulence-induced signals, and internal wave-generated temperature fluctuations, recorded by an on-land broadband seismometer, an ocean bottom seismometer (OBS) array, and a deep-sea differential pressure gauge (DPG) array, respectively.

In the first example, the tilt signals < 0.3 mHz at MASB station of Broadband Array in Taiwan for Seismology correlate with precipitation and water level in a nearby river, indicating that the ground tilts were induced by rising of water level in the river during the heavy rainfall events. In addition, the time series of precipitation were successfully quantified by the empirical Green’s function (eGF) method using the seismic waveforms. In the second example, the OBS-calculated time derivative of kinetic energy correlates with the thermistor-string-calculated turbulent kinetic energy dissipation rate, suggesting that the signals were induced by near-seafloor turbulent motions in deep (> 3000 m) waters. The turbulence generated by breaking of the inertial internal waves propagated south-southwestward to upslope of the OBS array. Besides, the small-scale topography in the array induced localized breaking of the waves and caused varying turbulence-induced signals. In the third example, the DPG data between 0.002 and 0.1 mHz correlate with the temperature variations measured by a nearby thermistor. The temperature fluctuations were induced by deep-sea internal waves. The propagation directions and phase speeds of the internal waves can be tracked using array analysis methods.

This line of studies shows that the environmental processes detected by the seismic instruments reveal interactions among the atmosphere, hydrosphere, and lithosphere. The seismic data provide complementary observations to quantify these processes. Thus, the historical seismic and real-time seismic datasets may help for studying decadal environmental changes and monitoring the earth environments, respectively.
關鍵字(中) ★ 地震儀感測環境訊號
★ 寬頻地震儀
★ 海底地震儀
★ 分壓計
★ 地傾
★ 深海內波
★ 深海紊流
★ 視波源時間函數
★ 經驗格林函數
★ 陣列分析
關鍵字(英) ★ Seismically detected environmental signals
★ Broadband seismometers
★ Ocean bottom seismometers (OBSs)
★ Differential pressure gauges (DPGs)
★ Ground tilts
★ Deep-sea internal waves
★ Deep-sea turbulence
★ Apparent source time function (ASTF)
★ empirical Green′s function (eGF)
★ Array analysis
論文目次 Table of Contents

摘要 i
Abstract ii
Acknowledgments iii
List of Figures vii
List of Tables ix
Explanation of Symbols x
Chapter 1 Introduction 1
1.1 Instrument Background 1
1.2 Scientific Background 3
1.2.1 On-land environmental processes and signals 4
1.2.2 Ocean environmental processes and signals 5
1.2.3 Seismic array analysis 8
1.3 Objective 8
1.4 Structure of Dissertation and Relationship with Each Chapter 9
Chapter 2 On-land Environmental Signals: Seismically Detected Ground Tilts Induced by Precipitation and Fluvial Processes 11
2.1 Introduction 12
2.2 Data 14
2.3 Results 15
2.3.1 Time series analysis 15
2.3.2 Interpretation and hypothesis 21
2.3.3 Testing the Hypothesis 22
2.3.4 ASTF and eGF precipitation 29
2.4 Discussion 36
2.5 Conclusions 39
Chapter 3 Ocean Environmental Signals: Deep-sea Turbulence Evolution Observed by Multiple Closely Spaced Instruments 41
3.1 Introduction 42
3.2 Data and Methods 46
3.2.1 Array deployments and instrument setting 46
3.2.2 Data processing 48
3.3 Results 50
3.3.1 Data overview 50
3.3.2 Energy calculated from seismic and temperature data 52
3.3.3 Turbulent motion in the small array 55
3.3.4 Local effects 57
3.4 Discussion and Conclusions 60
Chapter 4 Ocean Environmental Signals: Tracking Deep-sea Internal Wave Propagation Using Array Analysis 64
4.1 Introduction 65
4.2 Data and Methods 68
4.3 Results 70
4.3.1 Temperature-induced DPG variations 70
4.3.2 Propagation of internal waves calculated from FK analysis 73
4.3.3 Propagation of internal wave calculated from linear regression 77
4.4 Discussion and Conclusions 78
Chapter 5 Concluding Remarks and Future Works 82
5.1 Concluding Remarks 82
5.2 Future Works 84
References 87
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指導教授 戚務正 林靜怡(Wu-Cheng Chi Jing-Yi Lin) 審核日期 2021-7-1
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