臺灣位於西北太平洋颱風主要通道上，每年夏秋季常常受到颱風的侵襲，風暴潮為颱風期間沿海地區最主要之災害之一，其成因為強風以及低氣壓系統導致海水位上升，往往對沿海地區造成極大的破壞，人民流離失所，因此建立風暴潮危害分析方法，對於沿海地區防災規劃具有重要意義。臺灣西南部沿海為地層下陷較為嚴重之區域，因此本研究將其作為研究區域。
有別於傳統上較常使用之定論式方法，本研究主要使用機率式方法，將不同合成颱風情境發生的可能性及分析過程中之不確定性納入考量，並以聯合機率法（Joint Probability Method, JPM）及最佳取樣法（Joint Probability Method with Optimal Sampling, JPM-OS）為核心，利用歷史颱風資料建立風暴參數之統計特性，並透過貝氏求積法選取具代表性之合成颱風情境；同時參考臺灣常見颱風路徑型態，設定登陸型與掠過型合成颱風路徑。合成颱風之風場與氣壓場則以 Holland 參數風場模型建立，並輸入 SCHISM-WWMIII 耦合模式進行水位與波浪模擬。
本研究完成機率式風暴潮危害度分析流程之建立，並將其應用於塭豐村，以探討不同合成颱風情境下，風暴潮對塭豐村之影響，而未來可進一步應用於不同沿海地區之風暴潮風險評估與防災規劃。

Taiwan is frequently affected by typhoons from the western North Pacific, and storm surge is one of the major coastal hazards during typhoon events. The southwestern coast of Taiwan is particularly vulnerable due to severe land subsidence; therefore, it was selected as the study area.This study develops a probabilistic storm surge hazard analysis framework using the Joint Probability Method (JPM) and the Joint Probability Method with Optimal Sampling (JPM-OS). Historical typhoon data are used to establish the statistical characteristics of storm parameters, and representative synthetic typhoon scenarios are selected through Bayesian quadrature. Landfalling and bypassing synthetic typhoon tracks are constructed based on common typhoon track patterns affecting Taiwan. The Holland parametric wind model is then used to generate wind and pressure fields, which are applied to the coupled SCHISM-WWMIII model to simulate water levels and waves.The proposed framework is applied to Wenfeng Village to evaluate storm surge hazards under different synthetic typhoon scenarios. The method can also be extended to other coastal areas for storm surge risk assessment and disaster prevention planning.

1. 內政部(2017)。《整體海岸管理計畫》。
2. 交通部央氣象署，海象環境資訊平台。
3. 交通部中央氣象署，颱風資料庫。
4. 陳子捷(2021)：《颱風風場之波高推算對侵台颱風路徑之合適性分析》國立成功大學水利及海洋工程系碩士論文，台南。
5. 經濟部水利署(2020)。《彰化縣一級海岸防護計畫》。
6. 經濟部水利署(2020)。《屏東縣一級海岸防護計畫》。
7. Atkinson, G. D., and Holliday, C. R. Tropical cyclone minimum sea level pressure/maximum sustained wind relationship for the Western North Pacific. Monthly Weather Review 105, 4 (1977), 421–427.
8. Battjes, J. A., and Janssen, J. P. F. M. Energy loss and set-up due to breaking of random waves. Coastal Engineering 1978: Proceedings of the 16th International Conference on Coastal Engineering (1978), American Society of Civil Engineers, 569–587.
9. Chouinard, L. E., and Liu, C. Model for recurrence rate of hurricanes in Gulf of Mexico. Journal of Waterway, Port, Coastal, and Ocean Engineering 123, 3 (1997), 113–119.
10. Der Kiureghian, A., and Ditlevsen, O. Aleatory or epistemic? Does it matter? Structural Safety 31 (2009), 105–112.
11. Egbert, G. D., and Erofeeva, S. Y. Efficient inverse modeling of barotropic ocean tides. Journal of Atmospheric and Oceanic Technology 19, 2 (2002), 183–204.
12. Electric Power Research Institute. Probabilistic flooding hazard assessment for storm surge with an example based on historical water levels. Tech. Rep. 3002008111, Electric Power Research Institute, 2016.
13. Federal Emergency Management Agency. Region II storm surge project: Joint probability analysis of hurricane and extratropical flood hazards. Risk Assessment, Mapping, and Planning Program, Federal Emergency Management Agency, 2014.
14. Gonzalez, V. M., Nadal-Caraballo, N. C., Melby, J. A., and Cialone, M. A. Quantification of uncertainty in probabilistic storm surge models: Literature review. Tech. Rep. ERDC/CHL SR-19-1, U.S. Army Engineer Research and Development Center, 2019.
15. Hasselmann, K., Barnett, T. P., Bouws, E., Carlson, H., Cartwright, D. E., Enke, K., Ewing, J. A., Gienapp, H., Hasselmann, D. E., Kruseman, P., Meerburg, A., Müller, P., Olbers, D. J., Richter, K., Sell, W., and Walden, H. Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). Deutsches Hydrographisches Institut, 1973.
16. Ho, F. P., and Myers, V. A. Joint probability method of tide frequency analysis applied to Apalachicola Bay and St. George Sound, Florida. Tech. Rep. NWS 18, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1975.
17. Ho, F. P., Schwerdt, R. W., and Goodyear, H. V. Some climatological characteristics of hurricanes and tropical storms, Gulf and East Coasts of the United States. Tech. Rep. NWS 38, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1987.
18. Holland, G. J. An analytic model of the wind and pressure profiles in hurricanes. Monthly Weather Review 108, 8 (1980), 1212–1218.
19. Imani, M., Kuo, C.-Y., Chen, P.-C., Tseng, K.-H., Kao, H.-C., Lee, C.-M., and Lan, W.-H. Risk assessment of coastal flooding under different inundation situations in southwest of Taiwan (Tainan City). Water 13, 6 (2021), 880.
20. Li, S. H., and Hong, H. P. Use of historical best track data to estimate typhoon wind hazard at selected sites in China. Natural Hazards 76, 2 (2015), 1395–1414.
21. Lin, W., and Fang, W. Regional characteristics of Holland B parameter in typhoon wind field model for Northwest Pacific. Tropical Geography 33, 2 (2013), 124–132.
22. Myers, V. A. Joint probability method of tide frequency analysis applied to Atlantic City and Long Beach Island, N.J. Tech. Rep. WBTM HYDRO 11, U.S. Department of Commerce, Environmental Science Services Administration, Weather Bureau, 1970.
23. Nadal-Caraballo, N. C., Melby, J. A., Gonzalez, V. M., and Cox, A. T. North Atlantic Coast Comprehensive Study: Coastal storm hazards from Virginia to Maine. Tech. Rep. ERDC/CHL TR-15-5, U.S. Army Engineer Research and Development Center, 2015.
24. Niedoroda, A. W., Resio, D. T., Toro, G. R., Divoky, D., Das, H. S., and Reed, C. W. Analysis of the coastal Mississippi storm surge hazard. Ocean Engineering 37, 1 (2010), 82–90.
25. Powell, M. J. D. The NEWUOA software for unconstrained optimization without derivatives. Tech. Rep. DAMTP 2004/NA05, Department of Applied Mathematics and Theoretical Physics, University of Cambridge, 2004.
26. Resio, D. T. White paper on estimating hurricane inundation probabilities. In Performance evaluation of the New Orleans and Southeast Louisiana hurricane protection system: Volume VIII—Engineering and operational risk and reliability analysis, Appendix 8-2. U.S. Army Corps of Engineers, Interagency Performance Evaluation Task Force, 2007.
27. Resio, D. T., Asher, T. G., and Irish, J. L. The effects of natural structure on estimated tropical cyclone surge extremes. Natural Hazards 88, 3 (2017), 1609–1637.
28. Roland, A., Zhang, Y. J., Wang, H. V., Meng, Y., Teng, Y. C., Maderich, V., Brovchenko, I., Dutour-Sikiric, M., and Zanke, U. A fully coupled 3D wave-current interaction model on unstructured grids. Journal of Geophysical Research: Oceans 117 (2012), C00J33.
29. Schloemer, R. W. Analysis and synthesis of hurricane wind patterns over Lake Okeechobee, Florida. Hydrometeorological Rep. No. 31, U.S. Department of Commerce, Weather Bureau, 1954.
30. Toro, G. R., Niedoroda, A. W., Reed, C. W., and Divoky, D. Quadrature-based approach for the efficient evaluation of surge hazard. Ocean Engineering 37, 1 (2010), 114–124.
31. U.S. Nuclear Regulatory Commission. Probabilistic flood hazard assessment research plan. Version 2014-10-23, ADAMS Accession No. ML14296A442, U.S. Nuclear Regulatory Commission, 2014.
32. Vickery, P. J. Simple empirical models for estimating the increase in the central pressure of tropical cyclones after landfall along the coastline of the United States. Journal of Applied Meteorology 44, 12 (2005), 1807–1826.
33. Vickery, P. J., and Wadhera, D. Statistical models of Holland pressure profile parameter and radius to maximum winds of hurricanes from flight-level pressure and H*Wind data. Journal of Applied Meteorology and Climatology 47, 10 (2008), 2497–2517.
34. Willoughby, H. E., and Rahn, M. E. Parametric representation of the primary hurricane vortex. Part I: Observations and evaluation of the Holland (1980) model. Monthly Weather Review 132, 12 (2004), 3033–3048.
35. Willoughby, H. E., Darling, R. W. R., and Rahn, M. E. Parametric representation of the primary hurricane vortex. Part II: A new family of sectionally continuous profiles. Monthly Weather Review 134, 4 (2006), 1102–1120.
36. Zhang, Y., and Baptista, A. M. SELFE: A semi-implicit Eulerian–Lagrangian finite-element model for cross-scale ocean circulation. Ocean Modelling 21, 3–4 (2008), 71–96.
37. Zhang, Y. J., Ye, F., Stanev, E. V., and Grashorn, S. Seamless cross-scale modeling with SCHISM. Ocean Modelling 102 (2016), 64–81.