多衛星資料分析台灣河口水質指數的時空變化

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楊濬宇(Jiun-Yu Yang) 查詢紙本館藏

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遙測科技碩士學位學程

論文名稱

多衛星資料分析台灣河口水質指數的時空變化
(Spatiotemporal Variations of Taiwan Estuary Water Quality Indices Analyzed Through Multi-Satellite Data)

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至系統瀏覽論文 (2026-7-1以後開放)

摘要(中)

河口羽流在河海交界處扮演著重要的角色，不僅是海水與淡水交換的重要地點，也
是眾多生物聚集的棲息地，更是河流污染物進入海洋的第一道防線。河口羽流的範圍和
變動受多種因素影響，目前尚未有一套固定的界定標準。水質變化是研究河口羽流變動
的一個重要指標，本研究利用多衛星觀測，選定台灣地區的淡水河、蘭陽溪、高屏溪以
及卑南溪四條河流作為研究範圍，進行河口水質分析，以深入瞭解羽流的變化。研究中
使用了可視化光學波長（Apparent Visible Wavelength, AVW）作為基於遙測反射率計算
的指數，來表示水色的變化，並結合葉綠素濃度、漫射衰減係數、有色可溶性有機物、
總懸浮固體以及沙奇盤深度等五種水質指數進行分析。透過1998年至2023年的多衛星
觀測數據和模式整合，使用月平均數據和經驗正交函數分析方法探討河口區域水質的時
空變化。研究發現，淡水河的河口羽流主要向西南方擴散，蘭陽溪則向東南方擴散，高
屏溪向西北方擴散，而卑南溪則向兩側擴散。水質指數與AVW的相關性在高屏溪最為
顯著，其中，總懸浮固體與AVW在所有河口中相關性超過0.5，是與AVW關聯性最強
的參數。此外，本研究也探討了使用500nm、520nm和525nm的AVW閾值來界定河口
羽流範圍，發現520nm雖然適合，但不能與陸地形成封閉區域，525nm在大多數情況下
能與陸地形成封閉區域，因此，525nm是最適合用於界定河口羽流範圍的AVW

摘要(英)

River plumes play a crucial role at the river-ocean interface, serving not only as a site for
the exchange of seawater and freshwater but also as a habitat for numerous organisms and the
first line of defense against riverine pollutants entering the ocean. The dynamics and extent of
river plumes are influenced by various factors, and there is currently no fixed standard for their
delineation. Water quality variation is an important indicator for studying changes in river
plumes. This study utilizes multi-satellite observations to analyze estuarine water quality in four
rivers in Taiwan: the Danshui River, Lanyang River, Gaoping River, and Beinan River, aiming
to gain a deeper understanding of plume dynamics. Apparent Visible Wavelength (AVW), an
index based on remote sensing reflectance calculations, is used to represent changes in water
color, combined with five different water quality indices including chlorophyll concentration,
diffuse attenuation coefficient, colored dissolved organic matter, total suspended solids, and
Secchi disk depth. By integrating data from multi-satellite observations from 1998 to 2023 and
using monthly average data and Empirical Orthogonal Function (EOF) analysis, the study
discusses the spatiotemporal variations in water quality in estuarine regions. The findings
indicate that the river plume from the Danshui River primarily disperses towards the southwest
of the estuary, while the Lanyang River disperses towards the southeast, the Gaoping River
towards the northwest, and the Beinan River disperses on both sides of the estuary. The
correlation between water quality indices and AVW is most significant in the Gaoping River
area, with Total Suspended Matter (TSM) showing the strongest correlation with AVW across
all estuaries, exceeding 0.5. Additionally, the study examines the use of AVW thresholds at 500
nm, 520 nm, and 525 nm for delineating river plume extents. Although 520 nm is suitable, it
does not form a closed area with the land, whereas 525 nm does form a closed area with the
land in most cases, making it the most appropriate AVW threshold for delineating the extent of
river plumes

關鍵字(中)

★ 河口羽流
★ 可視化光學波長
★ 多衛星資料
★ 海洋水色

關鍵字(英)

★ River plume
★ Apperant Visible Wavelength
★ Multi-Satellite Data
★ Ocean Color

論文目次

摘要 ........................................................................................................................................................... i
Abstract ................................................................................................................................................... ii
誌謝 ......................................................................................................................................................... iii
目錄 ......................................................................................................................................................... iv
圖目錄 ..................................................................................................................................................... vi
表目錄 ..................................................................................................................................................... ix
第一章緒論 ........................................................................................................................................... 1
1-1文獻回顧 ...................................................................................................................................... 1
1-2研究動機 ...................................................................................................................................... 5
第二章資料與方法 ............................................................................................................................... 7
2-1遙測反射率 .................................................................................................................................. 7
2-1-1 中解析度成像分光輻射計 .................................................................................................. 7
2-1-2 可見光紅外線成像輻射儀 .................................................................................................. 7
2-1-3 海洋與陸地顏色儀 .............................................................................................................. 7
2-2可視化光學波長 .......................................................................................................................... 8
2-3水質指數 ...................................................................................................................................... 9
2-3-1 葉綠素濃度 .......................................................................................................................... 9
2-3-2 漫射衰減係數 .................................................................................................................... 10
2-3-3 有色可溶性有機物 ............................................................................................................ 10
2-3-4 總懸浮固體 ........................................................................................................................ 11
2-3-5 沙奇盤深度 ........................................................................................................................ 11
2-4 經驗正交函數 ........................................................................................................................... 12
第三章研究結果 ................................................................................................................................. 13
3-1 長時間再分析資料的水質指數變化........................................................................................ 13
3-1-1 淡水河口 ............................................................................................................................ 14
3-1-2 蘭陽溪口 ............................................................................................................................ 29
3-1-3 高屏溪口 ............................................................................................................................ 44
v

3-1-4 卑南溪口 ............................................................................................................................ 59
3-2 個案分析 ................................................................................................................................... 74
3-2-1 淡水河口 ............................................................................................................................ 74
3-2-2 蘭陽溪口 ............................................................................................................................ 76
3-2-3 高屏溪口 ............................................................................................................................ 78
3-2-4 卑南溪口 ............................................................................................................................ 80
第四章結果討論 ................................................................................................................................. 82
4-1 不同環境條件下水質指數的相關性........................................................................................ 82
4-2 可視化光學波長與河口羽流面積............................................................................................ 85
第五章結論 ......................................................................................................................................... 91
第六章參考文獻 ................................................................................................................................. 93

參考文獻

[1] Horner-Devine, A. R., Hetland, R. D., & MacDonald, D. G. (2015). Mixing and transport
in coastal river plumes. Annual Review of Fluid Mechanics, 47, 569-594.
[2] Osadchiev, A., & Yankovsky, A. (2022). River plumes and estuaries. Frontiers in Marine
Science, 9, 986114.
[3] Kang, Y., Pan, D., Bai, Y., He, X., Chen, X., Chen, C. T. A., & Wang, D. (2013). Areas of
the global major river plumes. Acta Oceanologica Sinica, 32, 79-88.
[4] M. Dagga, R. Bennerb, S. Lohrenzc, D. Lawrencea. 2004 Transformation of dissolved and
particulate materials on continental shelves influenced by large rivers: plume processes.
Continental Shelf Research 24 (2004) 833–858
[5] Jonathan A. Warrick A Leal A. K. Mertes. Libe Washburn A David A. Siegel. 2004.
Dispersal forcing of southern California river plumes, based on field and remote sensing
observations. Geo-Mar Lett (2004) 24: 46–52
[6] Lega, M., & Endreny, T. (2016). Quantifying the environmental impact of pollutant plumes
from coastal rivers with remote sensing and river basin modelling. International Journal
of Sustainable Development and Planning, 11(5), 651-662.
[7] Petus, C., da Silva, E. T., Devlin, M., Wenger, A. S., & Alvarez-Romero, J. G. (2014).
Using MODIS data for mapping of water types within river plumes in the Great Barrier
Reef, Australia: Towards the production of river plume risk maps for reef and seagrass
ecosystems. Journal of environmental management, 137, 163-177.
[8] Warrick, J. A., DiGiacomo, P. M., Weisberg, S. B., Nezlin, N. P., Mengel, M., Jones, B.
H., ... & Farnsworth, K. L. (2007). River plume patterns and dynamics within the Southern
California Bight. Continental Shelf Research, 27(19), 2427-2448.
[9] Molleri, G. S., Novo, E. M. D. M., & Kampel, M. (2010). Space-time variability of the
Amazon River plume based on satellite ocean color. Continental Shelf Research, 30(3-4),
342-352.
[10] Bai, Y., He, X., Pan, D., Chen, C. T. A., Kang, Y., Chen, X., & Cai, W. J. (2014).
Summertime Changjiang River plume variation during 1998–2010. Journal of
Geophysical Research: Oceans, 119(9), 6238-6257.
[11] Falcieri, F. M., Benetazzo, A., Sclavo, M., Russo, A., & Carniel, S. (2014). Po River plume
pattern variability investigated from model data. Continental Shelf Research, 87, 84-95.
[12] Hopkins, J., Lucas, M., Dufau, C., Sutton, M., Stum, J., Lauret, O., & Channelliere, C.
(2013). Detection and variability of the Congo River plume from satellite derived sea
surface temperature, salinity, ocean colour and sea level. Remote sensing of environment,
139, 365-385.
[13] Kubryakov, A., Stanichny, S., & Zatsepin, A. (2016). River plume dynamics in the Kara
Sea from altimetry-based lagrangian model, satellite salinity and chlorophyll data. Remote
sensing of environment, 176, 177-187.
[14] Chung, H. W., Liu, C. C., Chiu, Y. S., & Liu, J. T. (2014). Spatiotemporal variation of
Gaoping River plume observed by Formosat-2 high resolution imagery. Journal of Marine
Systems, 132, 28-37.
[15] Hsu, P. C., Lee, H. J., & Lu, C. Y. (2021). Impacts of the Kuroshio and Tidal currents on
the hydrological characteristics of Yilan Bay, Northeastern Taiwan. Remote Sensing,
13(21), 4340.
[16] Mestres, M., Sierra, J. P., & Sanchez-Arcilla, A. (2007). Factors influencing the spreading
of a low-discharge river plume. Continental Shelf Research, 27(16), 2116-2134.
[17] Nakada, S., Kobayashi, S., Hayashi, M., Ishizaka, J., Akiyama, S., Fuchi, M., & Nakajima,
M. (2018). High-resolution surface salinity maps in coastal oceans based on geostationary
ocean color images: quantitative analysis of river plume dynamics. Journal of
oceanography, 74, 287-304.
[18] Osadchiev, A., & Zavialov, P. (2019). Structure and dynamics of plumes generated by
small rivers. Estuaries and Coastal Zones: Dynamics and Response to Environmental
Changes, 87843, 125-144.
[19] Lavrova, O. Y., Soloviev, D. M., Strochkov, M. A., Bocharova, T. Y., & Kashnitsky, A. V.
(2016, October). River plumes investigation using Sentinel-2A MSI and Landsat-8 OLI
data. In Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions
2016 (Vol. 9999, pp. 125-136). SPIE.
[20] Lebedev, S. A., Kostianoy, A. G., Soloviev, D. M., Kostianaia, E. A., & Ekba, Y. A. (2020).
On a relationship between the river runoff and the river plume area in the northeastern
Black Sea. International Journal of Remote Sensing, 41(15), 5806-5818.
[21] Devlin, M. J., Petus, C., Da Silva, E., Tracey, D., Wolff, N. H., Waterhouse, J., & Brodie,
J. (2015). Water quality and river plume monitoring in the Great Barrier Reef: an overview
of methods based on ocean colour satellite data. Remote Sensing, 7(10), 12909-12941.
[22] Patricio-Valerio, L., Schroeder, T., Devlin, M. J., Qin, Y., & Smithers, S. (2023).
Meteorological Satellite Observations Reveal Diurnal Exceedance of Water Quality
Guideline Thresholds in the Coastal Great Barrier Reef. Remote Sensing, 15(9), 2335.
[23] Dupouy, C., Wattelez, G., Lefevre, J., Juillot, F., Andreoli, R., Lille, D., ... & Frouin, R.
(2018, October). Rain-derived particles and CDOM distribution along the east coast of
New Caledonia. In Remote Sensing of the Open and Coastal Ocean and Inland Waters
(Vol. 10778, pp. 86-96). SPIE.
[24] Parida, C., Baliarsingh, S. K., Lotliker, A. A., Dash, M., Srichandan, S., & Sahu, K. C.
(2019). Seasonal variation in optically active substances at a coastal site along western
Bay of Bengal. SN Applied Sciences, 1, 1-8.
[25] Du, C., Li, Y., Wang, Q., Liu, G., Zheng, Z., Mu, M., & Li, Y. (2017). Tempo-spatial
dynamics of water quality and its response to river flow in estuary of Taihu Lake based on
GOCI imagery. Environmental Science and Pollution Research, 24, 28079-28101.
[26] Turner, J. S., Fall, K. A., & Friedrichs, C. T. (2022). Clarifying water clarity: A call to use
metrics best suited to corresponding research and management goals in aquatic ecosystems.
Limnology and Oceanography Letters.
[27] Yuan-Fong Su., Yii-Chen Wu., Ming-Daw Su., Ke-Sheng Cheng. (2009). Assessment of
Coastal Water Quality Estimation Models Using SPOT Imagery. Journal of Taiwan
Agricultural Engineering
[28] Shi, W., & Wang, M. (2012). Satellite views of the bohai sea, yellow sea, and East China
Sea. Progress in Oceanography, 104, 30-45.
[29] Gardel, A., Anthony, E. J., Santos, V. F., Huybrechts, N., Lesourd, S., Sottolichio, A., &
Maury, T. (2022). A remote sensing-based classification approach for river mouths of the
Amazon-influenced Guianas coast. Regional Environmental Change, 22(2), 65.
[30] Basu, A., McCullough, G., Belanger, S., Mukhopadhyay, A., Doxaran, D., Sydor, K., ... &
Ehn, J. (2023). Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using
satellite remote sensing of CDOM and suspended sediment. Elem Sci Anth, 11(1), 00076.
[31] Kim, H. C., Son, S., Kim, Y. H., Khim, J. S., Nam, J., Chang, W. K., ... & Ryu, J. (2017).
Remote sensing and water quality indicators in the Korean West coast: Spatio-temporal
structures of MODIS-derived chlorophyll-a and total suspended solids. Marine Pollution
Bulletin, 121(1-2), 425-434.
[32] Miller, R. L., Liu, C. C., Buonassissi, C. J., & Wu, A. M. (2011). A multi-sensor approach
to examining the distribution of total suspended matter (TSM) in the Albemarle-Pamlico
estuarine system, NC, USA. Remote Sensing, 3(5), 962-974.
[33] 林聖烈. (2006). 淡水河口環流與淡水舌之研究. 中央大學水文與海洋科學研究所學
位論文, 2006, 1-53.
[34] 鮑俊宏, 陳佳琳, 施孟憲, & 廖敬元. (2022). 結合近海漂沙觀測與 ROMS 模式探
討河口泥沙傳輸過程—以卑南溪為例. 土木水利, 49(6), 72-79.
[35] Sauda, S., Weitzel, E., Gates, E., Guttman, M., Vorster, A., Choi, C. T. H., ... & Engelstad,
P. (2022). Monitoring Water Quality and Evaluating Potential Drivers of Algae Blooms in
the Upper Yampa River Watershed.
[36] 臧傳凱, 沈芳, & 楊正東. (2021). 基於無人機高光譜遙感的河湖水環境探測. 自然
資源遙感, 33(3), 45-53.
[37] Zhao, Y., Shen, Q., Wang, Q., Yang, F., Wang, S., Li, J., ... & Yao, Y. (2020). Recognition
of water colour anomaly by using hue angle and Sentinel 2 image. Remote Sensing, 12(4),
716.
[38] Matek, A., Bosak, S., ?upraha, L., Neeley, A., Vi?i?, H., Cetini?, I., & Ljube?i?, Z. (2023).
Phytoplankton diversity and chemotaxonomy in contrasting North Pacific ecosystems.
PeerJ, 11, e14501.
[39] Sherman, J., Tzortziou, M., Turner, K. J., Goes, J., & Grunert, B. (2023). Chlorophyll
dynamics from Sentinel-3 using an optimized algorithm for enhanced ecological
monitoring in complex urban estuarine waters. International Journal of Applied Earth
Observation and Geoinformation, 118, 103223.
[40] Valerio, A. D. M., Kampel, M., Vantrepotte, V., Ward, N. D., & Richey, J. E. (2021).
Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3
Ocean and Land Color Instrument Imagery. Remote Sensing, 13(16), 3057.
[41] Vandermeulen, R. A., Mannino, A., Craig, S. E., & Werdell, P. J. (2020). 150 shades of
green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the
ocean. Remote Sensing of Environment, 247, 111900.

指導教授

許伯駿(Po-Chun Hsu)

審核日期

2025-2-13

推文