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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 生物環境系統工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91590
完整後設資料紀錄
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dc.contributor.advisor張倉榮zh_TW
dc.contributor.advisorTsang-Jung Changen
dc.contributor.author許可昀zh_TW
dc.contributor.authorKo-Yun Hsuen
dc.date.accessioned2024-02-01T16:14:40Z-
dc.date.available2024-02-02-
dc.date.copyright2024-02-01-
dc.date.issued2023-
dc.date.submitted2024-01-17-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91590-
dc.description.abstract高雄港為臺灣最重要的港口,在極端氣候的影響下,災害風險也隨之增加,因此分析未來災害情境並進行危險分析,以有效降低災害發生之衝擊是相當重要的。本研究基於 IPCC 氣候變遷第五次評估報告,以第五階段耦合氣候模式相關氣候資料進 WRF 做動力降尺度,輸出基期(1986-2005)及近期(2021-2040)、中期(2041-2060)三個伴隨的代表性濃度路徑 (RCP 4.5、RCP 6.0 和 RCP 8.5)在颱風季 7、8、9 月西太平洋生成颱風資料,再從中挑選侵臺風速 > 25m/s 的較強颱風與所有侵臺颱風做比較,並以影響高雄港之颱風事件資料,以危險度概念分別進行強風危險分析、暴雨淹水危險分析,一為考量風速及風向與貨櫃之夾角;二為使用臺大細胞自動機快速淹水模式之輸出結果加以評估,將危險分級並繪製危險度地圖。
研究結果顯示,侵襲臺灣颱風中的較強颱風比例增加,且路徑有明顯偏向南部,因此未來情境對於高雄港危險也相對增加,強風危險度在 RCP 8.5 比起 RCP 4.5 及 RCP 6.0 情境下有偏高的趨勢,而中期之颱風事件所造成的雨量、積淹水面積以及積淹水持續時間比基期和近期來的嚴重,但所有時期的淹水危險度均沒有達到高危險度的情形。未來決策者可參考此推估趨勢及危險圖,並依照觀測數據更新進行滾動式評估,以提出合適的調適策略以降低災害風險。
zh_TW
dc.description.abstractKaohsiung Port is one of Taiwan''s most crucial ports, and the impact of extreme weather conditions because of climate change has increased the risks of windy and flooded disasters. Therefore, it is essential to analyze future disaster scenarios and conduct hazard assessments to effectively mitigate the impact of disasters. The present study adopts the climate data from the fifth-phase coupled climate model that is based on the IPCC Fifth Assessment Report for dynamic downscaling with the WRF model. From the WRF model, the typhoon data in the Western Pacific within the typhoon season (July, August, and September) is generated for the base period (1986-2005) and the near-term (2021-2040) and mid-term (2041-2060) periods under three representative concentration pathways (RCP 4.5, RCP 6.0, and RCP 8.5). The typhoons that have affected Taiwan are selected and compared with the typhoons that have influenced Taiwan and with their maximum wind speeds > 25 m/s. Next, the hazard analysis of strong wind and flooding in Kaohsiung Port is conducted by considering the typhoons affecting Kaohsiung Port. Specifically, the strong wind hazard analysis is performed for the essential containers in Kaohsiung Port by using the output wind speed and wind direction data. As to the flooding hazard analysis, the simulated flooding result of the National Taiwan University cellular automaton rapid flooding model (NTU-CAFIM) is used to classify the hazard degree of the essential facilities in Kaohsiung Port. Finally, the analyzed results are displayed as hazard degree maps.
Based on the result, concerning the typhoons affecting Taiwan, it is found that the proportion of stronger typhoons is increasing. Also, the typhoon pathways tend to shift from the northern region towards the southern region. Consequently, a higher risk to Kaohsiung Port is posed under climate change. Specifically, in terms of the hazard degree of strong winds, the RCP 8.5 scenario is higher than the RCP 4.5 and RCP 6.0 scenarios. As for the hazard degree of flooding, the mid-term period has more severe rainfall, accumulated flooded area, and flooding duration than those in the base and near-term periods. However, it is found that the hazard degrees of flooding for all three periods are below the high-risk level. Decision-makers can use these estimated trends and hazard degree maps to propose suitable adaptation strategies to reduce disaster risk in the future.
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dc.description.tableofcontents謝誌 i
摘要 ii
Abstract iii
目次 v
圖次 viii
表次 xix
第一章 緒論 1
1.1 研究背景 1
1.2 文獻回顧 2
1.3 研究目的 10
1.4 論文架構 11
第二章 基本理論 12
2.1 天氣研究和預報模型 12
2.2 強風危險度分析方法 17
2.3 臺大細胞自動機快速淹水模式 18
2.3.1 二維快速漫地流模式 18
2.3.2 雨水下水道模式 26
2.3.3 模式銜接 29
2.4 淹水模式評估方法 32
2.4.1 列聯表 32
2.4.2 準確度 33
2.4.3 敏感度 33
2.4.4 偽陽性率 34
2.4.5 偽陰性率 34
第三章 研究區域概述與淹水模式驗證 35
3.1 研究區域概述 35
3.2 資料蒐集 37
3.2.1 數值高程模型(DEM) 37
3.2.2 土地利用資料 38
3.2.3 水利設施現況 39
3.2.4 雨量站 40
3.3 歷史災害事件 43
3.3.1 歷史強風事件 43
3.3.2 歷史淹水事件 45
3.4 淹水模式檢定驗證 64
第四章 高雄港危險分析方法 68
4.1 氣候模式資料 68
4.2 強風危險分析方法 70
4.3 暴雨淹水危險分析方法 77
第五章 案例探討與分析 78
5.1 動力降尺度分析結果 78
5.2 強風危險分析結果 84
5.3 暴雨淹水危險分析結果 95
第六章 結果與建議 104
6.1 結論 104
6.2 建議 105
參考文獻 106
附錄 A — 危險地圖 113
A.1 不同模式與情境下貨櫃區強風危險圖 114
A.2 不同模式與情境下碼頭區強風危險圖 126
A.3 不同模式與情境下高雄港區淹水結果圖 138
A.4 不同模式與情境下高雄港區淹水危險圖 150
附錄 B — 危險度計算 162
B.1 不同模式與情境下貨櫃區強風危險度計算 163
B.2 不同模式與情境下碼頭區強風危險度計算 186
附錄 C — 各情境較強颱風路徑數量 357
C.1各情境較強颱風路徑數量圖 358
C.2各情境較強颱風路徑數量占比圖 358
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dc.language.isozh_TW-
dc.title氣候變遷情境下高雄港強風以及淹水危險度評估zh_TW
dc.titleWind and Flood Hazard Assessment under Climate Change Scenarios in Kaohsiung Porten
dc.typeThesis-
dc.date.schoolyear112-1-
dc.description.degree碩士-
dc.contributor.coadvisor游晟暐zh_TW
dc.contributor.coadvisorCheng-Wei Yuen
dc.contributor.oralexamcommittee林洙宏;張高華;王嘉和;游翔麟zh_TW
dc.contributor.oralexamcommitteeChu-Hung Lin;Kao-Hua Chang;Chia-Ho Wang;Hsiang-Lin Yuen
dc.subject.keyword氣候變遷,危險分析,淹水評估,動力降尺度,zh_TW
dc.subject.keywordClimate change,Hazard analysis,Flood assessment,Dynamic downscaling,en
dc.relation.page360-
dc.identifier.doi10.6342/NTU202400031-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2024-01-18-
dc.contributor.author-college生物資源暨農學院-
dc.contributor.author-dept生物環境系統工程學系-
dc.date.embargo-lift2027-01-01-
顯示於系所單位:生物環境系統工程學系

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