近年來由於氣候變遷與全球暖化影響,極端事件發生頻率逐漸增加。台灣地處北半球颱風路徑要衝所在,然而面對洪災所造成的威脅,政府之經費資源有限,故對治水措施優先順序之管理是迫切需要的。有鑑於此,本研究旨在應用多重指標淹水風險模式,評估研究區域在未來氣候變遷衝擊下,淹水風險之變異程度,並從評估指標之權重關係,有助於未來洪水管理措施的制定及優先次序的安排。 本研究整理相關災害與風險評估之文獻,建立淹水災害風險因子分析方法,再應用非典型層級分析法,除彙整專家意見外,更將淹水災區之民眾意見納入,以決定各評估因子間的權重關係。研究首先應用水文水理及淹水模式模擬蘭陽溪流域5、10、25、50、100和200年重現期,分別在平均潮位及歷年來最大暴潮位邊界條件下之淹水災害風險圖,接著再從國科會TCCIP計畫所提供研究區域未來氣候變遷條件下之模擬颱風降雨事件,挑選近未來(2015-2039年)及21世紀末(2075-2099年)兩時期中超過100年重現期之颱風降雨,進而模擬分析其淹水危害性、脆弱性、暴露量及風險地圖,最後並將風險區分為低、中、高、極高四級,以評估氣候變遷衝擊下風險變化之趨勢。 研究結果顯示,隨著重現期增加高淹水風險村里主要集中於蘭陽溪流域以北之村里,在氣候變遷後蘭陽溪流域以南之村里淹水風險有上升之趨勢,此風險分佈與變化分析可供相關單位做為管理決策參考,以適度提高地方對淹水災害抵抗能力,在資源配置及災救上作更合理化的運用,減輕淹水災害所帶來的衝擊。
Typhoons and severe storms usually result in inundation and tremendous loss of lives and properties in Taiwan due to the non-uniformly distributed rainfall both in space and time with the fragile geographic conditions. However, government funding resources are limited, so the priority management of the flood control measures is urgently needed. . Therefore, this study aims to assess the impacts of climate change on regional flood risk and vulnerability by employing a multi-index model. Moreover, the risk maps established by this model could provide beneficial information for authorities and agencies to enhance the local resistance of flooding, manage the rescuing resources more effectively, and propose appropriate improvements for further disaster mitigation in the future. This study utilizes AHP to quantify the relative importance of nine indices that construct the inundation risk model. Unlike typical AHP approach to integrate various opinions of experts, this study additionally adopts flooding experiences from local residents to enrich the experts judgments for the better weight assignment. First, this study established flooding risk maps of 5, 10, 25, 50, 100, and 200 year of return periods in Lan-yang Basin. Finally, rainfall magnitude over 100 return period were selected to perform and produce the distribution maps of flooding risk, vulnerability, hazard, exposure, which represent the inundation characteristics under the impacts of climate change. The study results indicate that risk map established by this model could provide beneficial information for authorities and agencies to enhance that local resistance of flooding, manage the rescuing resources more effectively, and propose appropriate improvements for further disaster mitigation in the future.