簡易檢索 / 詳目顯示

研究生: 羅鈞瀚
Lo, Chun-Han
論文名稱: 臺灣周邊海域颱風波浪極值特性分析與設計參數之應用
Typhoon-Driven Extreme Wave Characteristics and Design-Parameter Applications around Taiwan
指導教授: 蕭士俊
Hsiao, Shih-Chun
學位類別: 博士
Doctor
系所名稱: 工學院 - 水利及海洋工程學系
Department of Hydraulic & Ocean Engineering
論文出版年: 2026
畢業學年度: 114
語文別: 英文
論文頁數: 155
中文關鍵詞: 設計波浪參數颱風波浪環境等值線極值分析Copula越波量海堤穩定性
外文關鍵詞: Design wave, Typhoon waves, Environmental contours, Extreme value analysis, Copula, Wave overtopping, Dike stability
相關次數: 點閱:2下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 可靠的設計海況是颱風頻繁地區進行海岸與離岸工程規劃的重要基礎。傳統做法多以單變量極值分析推估特定重現期的顯著波高,再藉由經驗公式估計對應的週期;然而這種方式無法反映波高與週期之間的聯合機率關係,也容易產生不符合波浪物理特性的設計組合。為改善上述問題,本研究以長期浮標觀測為基礎,建立一套結合物理限制與工程反應評估的颱風設計海況分析架構。
    本研究蒐集臺灣周邊十座長期波浪浮標資料,涵蓋東北部、東部、南部、西南部及臺灣海峽沿岸,並分別以年最大值與颱風事件兩種方式建立極值樣本。分析上先建立波高與週期的邊際極值分布,再以聯合機率模型描述兩者的相依關係,據以建構不同重現期的環境等值線。為避免統計外推產生不合理的波浪組合,接著納入波浪尖銳度與水深限制碎波條件,篩除不具物理可行性的設計海況。在各測站完成物理篩選後的五十年重現期颱風環境等值線上,選取最大波高、最大週期與最大波浪能量指標三個代表性設計點,並以非線性淺化與碎波公式將其由離岸傳遞至近岸;再於相同的堤趾水深與結構條件下,分別評估各設計點對波浪越波與海堤護面穩定性的影響。
    結果顯示,臺灣周邊的颱風設計海況呈現明顯的區域差異。主要設計波向隨海岸位置與地理環境系統性改變,波高與週期的聯合極值特性也在面向太平洋的開放海岸、南部過渡區域與臺灣海峽測站之間呈現不同型態。其中蘇澳與鵝鑾鼻受長週期颱風波影響較為顯著,新竹與澎湖的週期分布則較集中,環境等值線主要由波高主導。工程應用方面則發現,沒有任何單一設計點能同時支配波浪越波與海堤穩定性:在本研究設定的淺水堤趾條件下,水深限制碎波使各設計點傳遞至近岸後波高趨於一致,週期因而成為造成工程反應差異的主要因素。整體而言,最大週期設計點多半產生較大的越波量,最大波高設計點則對海堤護面塊石尺寸的需求較高。此差異反映不同工程公式對週期的敏感度並不一致,因此何者為控制設計海況會隨所評估的工程反應而改變。
    綜上所述,設計海況不宜僅以單一波高搭配經驗週期表示,而應自符合物理條件的聯合環境等值線中選取,並依實際工程反應加以判斷。由於本研究在各測站採用一致的結構條件進行比較,所得的控制設計點主要反映統一假設下的初步篩選結果,而非可直接套用於所有工程的通則。整體而言,本研究提出的方法可作為兼顧區域差異、物理合理性與工程應用意義的臺灣颱風設計海況分析基礎。

    Reliable design sea states are essential for coastal and offshore engineering in typhoon-prone regions. Conventional practice estimates a univariate return-level Hs (spectral significant wave height) and assigns an associated Tm (spectral mean zero-crossing wave period) using empirical Hs–Tm relationships, but this cannot represent the joint probability structure of Hs and Tm and may produce design combinations that are not physically admissible. This dissertation develops a buoy-based, physically screened, response-oriented framework for characterizing typhoon-driven design sea states around Taiwan.
    Long-term wave buoy records from ten locations around Taiwan, spanning the northeastern, eastern, southern, southwestern, and Taiwan Strait coasts, are analyzed using both annual-maximum (AM) and typhoon-event (TY) sampling. Marginal extreme-value distributions and copula-based dependence models are fitted to construct inverse first-order reliability method (IFORM) environmental contours, which are then screened for physical feasibility using wave-steepness and depth-limited breaking constraints.
    From each physically admissible 50-year TY environmental contour, three representative design points—MaxHs, MaxTm, and MaxHs²Tm—are selected and transformed shoreward using the Goda nonlinear shoaling and breaking formulation. Their engineering implications are then evaluated through wave overtopping and dike-stability calculations at a common design toe depth.
    The results show that typhoon-driven design sea states around Taiwan are strongly site dependent: dominant design wave directions rotate systematically with coastal setting, and the joint Hs–Tm tail structure differs between exposed Pacific-facing coasts, southern transition areas, and Taiwan Strait sites, with long-period typhoon influence most pronounced at Suao and Eluanbi and height-dominated, compact contours at Hsinchu and Penghu. No single contour-based design point governs both the overtopping and dike-stability responses: at the shallow design toe depth used for this screening comparison, depth-limited breaking compresses the transformed Hs of the three candidates to a nearly common value at every site, leaving wave period as the deciding factor. As a result, MaxTm typically governs wave overtopping, whereas MaxHs typically governs dike armor stability, reflecting the opposite sensitivity of the two response formulas to wave period once the waves reach the surging regime.
    These findings indicate that design sea states should be selected from physically admissible joint environmental contours and interpreted according to the engineering response of interest, rather than a single empirical Hs–Tm pair; because the reported governing design points reflect one fixed structural configuration applied uniformly across all sites, they represent a screening-level, assumption-dependent comparison rather than a universally applicable design rule. The proposed framework nonetheless provides a regionally differentiated and physically consistent basis for typhoon-driven coastal design sea states around Taiwan.

    摘要 I ABSTRACT III ACKNOWLEDGMENTS V CONTENTS VI LIST OF TABLES IX LIST OF FIGURES X ABBREVIATION AND SYMBOL LIST XV 1 INTRODUCTION 1 1.1 Motivation 1 1.2 Research gaps 2 1.3 Research objectives 4 1.4 Scope of the dissertation 5 2 LITERATURE REVIEW AND THEORETICAL FRAMEWORK 6 2.1 Extreme value theory 6 2.2 Bivariate joint probability 12 2.3 Environmental contour 16 3 STUDY AREA AND DATA INVENTORY 21 3.1 Taiwan sea environment 21 3.2 Data source 21 3.3 Sampling strategy and physical filters 26 3.4 Design point selection and nearshore wave height transformation 33 4 BUOY-BASED ANALYSIS 36 4.1 Wave characteristics 37 4.1.1 Longdong 37 4.1.2 Suao 39 4.1.3 Hualien 42 4.1.4 Taitung 45 4.1.5 Eluanbi 47 4.1.6 Xiaoliuqiu 50 4.1.7 Mito 53 4.1.8 Qigu 56 4.1.9 Penghu 58 4.1.10 Hsinchu 61 4.2 Bivariate statistics and uncertainty assessment 66 4.2.1 Longdong 67 4.2.2 Suao 68 4.2.3 Hualien 69 4.2.4 Taitung 70 4.2.5 Eluanbi 71 4.2.6 Xiaoliuqiu 72 4.2.7 Mito 73 4.2.8 Qigu 74 4.2.9 Penghu 75 4.2.10 Hsinchu 76 4.3 Design conditions from environmental contours 78 4.3.1 Longdong 78 4.3.2 Suao 80 4.3.3 Hualien 81 4.3.4 Taitung 83 4.3.5 Eluanbi 85 4.3.6 Xiaoliuqiu 86 4.3.7 Mito 87 4.3.8 Qigu 89 4.3.9 Penghu 91 4.3.10 Hsinchu 93 4.4 Regional contrasts in design sea states around Taiwan 95 5 ENGINEERING APPLICATIONS OF CONTOUR-BASED DESIGN WAVE CONDITIONS 101 5.1 Overtopping 106 5.2 Dike stability 114 5.3 Engineering implications of the three design scenarios 122 6 CONCLUSION 123 REFERENCES 125 APPENDIX 130

    Campos, R. M., Guedes Soares, C., Alves, J. H. G. M., Parente, C. E., & Guimaraes, L. G. (2019). Regional long-term extreme wave analysis using hindcast data from the South Atlantic Ocean. Ocean Engineering, 179, 202–212. https://doi.org/10.1016/j.oceaneng.2019.03.023
    Chen, Y., Li, J., Pan, S., Gan, M., Pan, Y., Xie, D., & Clee, S. (2019). Joint probability analysis of extreme wave heights and surges along China's coasts. Ocean Engineering, 177, 97–107. https://doi.org/10.1016/j.oceaneng.2018.12.010
    Chi, S.-Y., Liu, C.-J., Tan, C.-H., & Chen, Y.-H. (2020). Study of typhoon impacts on the foundation design of offshore wind turbines in Taiwan. Proceedings of the Institution of Civil Engineers - Forensic Engineering, 173(1), 35–47. https://doi.org/10.1680/jfoen.19.00011
    Clarindo, G., & Guedes Soares, C. (2024). Environmental contours of sea states by the I-FORM approach derived with the Burr-Lognormal statistical model. Ocean Engineering, 291. https://doi.org/10.1016/j.oceaneng.2023.116315
    Coles, S. (2001). An introduction to statistical modeling of extreme values. Springer Series in Statistics.
    Curceac, S., Atkinson, P. M., Milne, A., Wu, L., & Harris, P. (2020). An evaluation of automated GPD threshold selection methods for hydrological extremes across different scales. Journal of Hydrology, 585. https://doi.org/10.1016/j.jhydrol.2020.124845
    CWA. (2024). Typhoon Track Classifications and Frequency Statistics. Central Weather Administration.
    De Leo, F., Besio, G., Briganti, R., & Vanem, E. (2021). Non-stationary extreme value analysis of sea states based on linear trends. Analysis of annual maxima series of significant wave height and peak period in the Mediterranean Sea. Coastal Engineering, 167. https://doi.org/10.1016/j.coastaleng.2021.103896
    Durap, A. (2025). Thresholds and trends in wave steepness: A data-driven study of coastal wave breaking risk. Marine Science and Technology Bulletin, 14(2), 80–93. https://doi.org/10.33714/masteb.1649969
    Eldrup, M. R., Lykke Andersen, T., & Burcharth, H. F. (2019). Stability of Rubble Mound Breakwaters—A Study of the Notional Permeability Factor, Based on Physical Model Tests. Water, 11(5). https://doi.org/10.3390/w11050934
    Fang, F., Zhu, L., & Luo, Y. (2025). Non-stationary extreme value models to account for the intensification of extreme typhoon waves. Ocean Engineering, 324. https://doi.org/10.1016/j.oceaneng.2025.120672
    Gao, Y., Li, X., Chen, X., & Wang, L. (2025). Extreme wave and storm surge characteristics in the southeastern coastal and offshore regions of China. Sci Rep, 15(1), 26915. https://doi.org/10.1038/s41598-025-09737-x
    Goda, Y. (2000). Random Seas and Design of Maritime Structures (Second ed.). World Scientific Publishing Company.
    Goda, Y. (2003). Revisiting Wilsons forumulas for simplified wind wave prediction. Journal of Waterway, Port, Coastal, Ocean Engineering.
    Goda, Y. (2012). Design wave height selection in intermediate-depth waters. Coastal Engineering, 66, 3–7. https://doi.org/10.1016/j.coastaleng.2012.03.005
    Haixia, Z., Meng, C., & Weihua, F. (2023). Joint probability analysis of storm surges and waves caused by tropical cyclones for the estimation of protection standard: a case study on the eastern coast of the Leizhou Peninsula and the island of Hainan in China. Natural Hazards and Earth System Sciences, 23(8), 2697–2717. https://doi.org/10.5194/nhess-23-2697-2023
    Hiles, C. E., Robertson, B., & Buckham, B. J. (2019). Extreme wave statistical methods and implications for coastal analyses. Estuarine, Coastal and Shelf Science, 223, 50–60. https://doi.org/10.1016/j.ecss.2019.04.010
    Hu, X., Fang, G., & Ge, Y. (2024). Joint probability analysis and mapping of typhoon-induced wind, wave, and surge hazards along southeast China. Ocean Engineering, 311. https://doi.org/10.1016/j.oceaneng.2024.118844
    ISO. (2015). ISO 19901-1 PETROLEUM AND NATURAL GAS INDUSTRIES—SPECIFIC REQUIREMENTS FOR OFFSHORE STRUCTURES—PART 1: METOCEAN DESIGN AND OPERATING CONSIDERATIONS.
    James, J. P., & Panchang, V. (2024). Assessment of joint distributions of wave heights and periods. Ocean Engineering, 313. https://doi.org/10.1016/j.oceaneng.2024.119501
    James, P. I. (1975). Statistical inference using extreme order statistics. Annual Statistic, 3(1), 119–131.
    Jin, W., Guan, S., Chen, L., Tang, Z., Huang, M., Xu, X., & Zhao, W. (2025). Joint risk analysis of typhoon hazards based on coupled ADCIRC-SWAN model simulations around Hainan, China. Journal of Sea Research, 205. https://doi.org/10.1016/j.seares.2025.102587
    Kang, H., Chun, I., & Oh, B. (2020). New procedure for determining equivalent deep-water wave height and design wave heights under irregular wave conditions. International Journal of Naval Architecture and Ocean Engineering, 12, 168–177. https://doi.org/10.1016/j.ijnaoe.2019.09.002
    Kendall, M. G. (1938). A New Measure of Rank Correlation. Biometrika, 30(1/2), 81–93. https://doi.org/10.2307/2332226
    Kwon, K., Lee, J., Choi, Y., Paik, J. G., Choi, Y., & Kong, J.-S. (2025). Environmental contour correction using Bayesian inference for areas with limited metocean data. Ocean Engineering, 342. https://doi.org/10.1016/j.oceaneng.2025.123000
    Li, J., Liang, B., Shao, Z., & Gao, H. (2025). Joint probability analysis of significant wave height and wind speed under extreme weather conditions. Ocean Engineering, 334. https://doi.org/10.1016/j.oceaneng.2025.121664
    Li, J., Shao, Z., Liang, B., Du, S., & Gao, H. (2025). Regional frequency analysis of extreme significant wave heights with long return periods based on complete distribution characteristics. Applied Ocean Research, 158. https://doi.org/10.1016/j.apor.2025.104566
    Liang, B., Shao, Z., Li, H., Shao, M., & Lee, D. (2019). An automated threshold selection method based on the characteristic of extrapolated significant wave heights. Coastal Engineering, 144, 22–32. https://doi.org/10.1016/j.coastaleng.2018.12.001
    Lin, Y., Dong, S., & Tao, S. (2020). Modelling long-term joint distribution of significant wave height and mean zero-crossing wave period using a copula mixture. Ocean Engineering, 197. https://doi.org/10.1016/j.oceaneng.2019.106856
    Liu, G., Yang, B., Yu, Z., & Jin, G. (2025). Analysis of wave height return period based on joint probability analysis of different typhoon disaster factors. Applied Ocean Research, 158. https://doi.org/10.1016/j.apor.2025.104584
    Lucas, C., & Guedes Soares, C. (2015). Bivariate distributions of significant wave height and mean wave period of combined sea states. Ocean Engineering, 106, 341–353. https://doi.org/10.1016/j.oceaneng.2015.07.010
    Martzikos, N. T., Prinos, P. E., Memos, C. D., & Tsoukala, V. K. (2021). Statistical analysis of Mediterranean coastal storms. Oceanologia, 63(1), 133–148. https://doi.org/10.1016/j.oceano.2020.11.001
    Montes-Iturrizaga, R., & Heredia-Zavoni, E. (2015). Environmental contours using copulas. Applied Ocean Research, 52, 125–139. https://doi.org/10.1016/j.apor.2015.05.007
    Noh, Y., & Sun, M. (2025). Environmental contours using copulas for extreme load estimate of offshore wind turbines. Ocean Engineering, 326. https://doi.org/10.1016/j.oceaneng.2025.120919
    Qiao, C., & Myers, A. T. (2021). A new IFORM-Rosenblatt framework for calculation of environmental contours. Ocean Engineering, 238. https://doi.org/10.1016/j.oceaneng.2021.109622
    Rosenblatt, M. (1952). Remarks on a multivariate transformation. The Annals of Mathematical Statistics, 23(3), 470–472.
    Ross, E., Astrup, O. C., Bitner-Gregersen, E., Bunn, N., Feld, G., Gouldby, B., Huseby, A., Liu, Y., Randell, D., Vanem, E., & Jonathan, P. (2020). On environmental contours for marine and coastal design. Ocean Engineering, 195. https://doi.org/10.1016/j.oceaneng.2019.106194
    Salvadori, G., Tomasicchio, G. R., & D'Alessandro, F. (2014). Practical guidelines for multivariate analysis and design in coastal and off-shore engineering. Coastal Engineering, 88, 1–14. https://doi.org/10.1016/j.coastaleng.2014.01.011
    Shui, Y., Kieviet, J., Erfort, G., Cheng, Z., Ma, Y., & Chen, P. (2025). Long-term joint distribution of environmental conditions at four sites in South China and South African Seas: A comparative study for offshore wind applications. Ocean Engineering, 337. https://doi.org/10.1016/j.oceaneng.2025.121742
    Sklar, A. (1959). Fonctions de Répartition à n Dimensions et Leurs Marges. Publications de l'Institut Statistique de l'Université de Paris(8), 229–231.
    Spearman, C. (1904). The Proof and Measurement of Association between Two Things. The American Journal of Psychology, 15(1), 72–101. https://doi.org/10.2307/1412159
    Suh, K.-D., Kwon, H.-D., & Lee, D.-Y. (2010). Some statistical characteristics of large deepwater waves around the Korean Peninsula. Coastal Engineering, 57(4), 375–384. https://doi.org/10.1016/j.coastaleng.2009.10.016
    Teena, N. V., Sanil Kumar, V., Sudheesh, K., & Sajeev, R. (2012). Statistical analysis on extreme wave height. Natural Hazards, 64(1), 223–236. https://doi.org/10.1007/s11069-012-0229-y
    USACE. (1984). Shore Protection Manual (Vol. I). CERC Dept. of the Army, U.S. Army Corps of Engineers.
    USACE. (2002). Coastal Engineering Manual. CERC Dept. of the Army, U.S. Army Corps of Engineers.
    Van der Meer, J. W. (1988). Rock slopes and gravel beaches under wave attack [Delft University of Technology]. Delft, The Netherlands.
    Van der Meer, J. W., Allsop, N. W. H., Bruce, T., De Rouch, J., Kortenhaus, A., Pullen, T., Schuttrumpf, H., Troch, P., & Zanuttigh, B. (2018). EurOtop (Second ed.).
    Vanem, E. (2016). Joint statistical models for significant wave height and wave period in a changing climate. Marine Structures, 49, 180–205. https://doi.org/10.1016/j.marstruc.2016.06.001
    Vanem, E. (2020). Bivariate regional extreme value analysis for significant wave height and wave period. Applied Ocean Research, 101. https://doi.org/10.1016/j.apor.2020.102266
    Vanem, E., Zhu, T., & Babanin, A. (2022). Statistical modelling of the ocean environment – A review of recent developments in theory and applications. Marine Structures, 86. https://doi.org/10.1016/j.marstruc.2022.103297
    Vousdoukas, M. I., Mentaschi, L., Voukouvalas, E., Bianchi, A., Dottori, F., & Feyen, L. (2018). Climatic and socioeconomic controls of future coastal flood risk in Europe. Nature Climate Change, 8(9), 776–780. https://doi.org/10.1038/s41558-018-0260-4
    Wang, J., Liu, J., Wang, Y., Liao, Z., & Sun, P. (2021). Spatiotemporal variations and extreme value analysis of significant wave height in the South China Sea based on 71-year long ERA5 wave reanalysis. Applied Ocean Research, 113. https://doi.org/10.1016/j.apor.2021.102750
    Wrang, L., Katsidoniotaki, E., Nilsson, E., Rutgersson, A., Rydén, J., & Göteman, M. (2021). Comparative Analysis of Environmental Contour Approaches to Estimating Extreme Waves for Offshore Installations for the Baltic Sea and the North Sea. Journal of Marine Science and Engineering, 9(1). https://doi.org/10.3390/jmse9010096
    Zhang, Y., Kim, C.-W., Beer, M., Dai, H., & Soares, C. G. (2018). Modeling multivariate ocean data using asymmetric copulas. Coastal Engineering, 135, 91–111. https://doi.org/10.1016/j.coastaleng.2018.01.008
    Zhao, M., Deng, X., & Wang, J. (2022). Description of the Joint Probability of Significant Wave Height and Mean Wave Period. Journal of Marine Science and Engineering, 10(12). https://doi.org/10.3390/jmse10121971
    Zhao, Y., & Dong, S. (2023). Multivariate probability analysis of wind-wave actions on offshore wind turbine via copula-based analysis. Ocean Engineering, 288. https://doi.org/10.1016/j.oceaneng.2023.116071
    Zhao, Y., Xie, D., Pan, J., Liu, Q., & Wang, Z. (2025). A threshold determination method for extreme value analysis based on the tail least squares estimation. Ocean Engineering, 335. https://doi.org/10.1016/j.oceaneng.2025.121696

    QR CODE