台北市洪災風險分析

Flood Risk Analysis for Taipei City

10.6342/NTU.2012.00390

林依潔

脆弱度 ； 脆弱度指標 ； 模糊德爾菲 ； 層級分析法 ； 風險地圖 ； Vulnerability ； Social Vulnerability Indices ； Fuzzy Delphi Method ； Analytic hierarchy process ； Risk map

國立臺灣大學生物環境系統工程學系學位論文

2012年

碩士

許銘熙

繁體中文

台灣位於西太平洋地區之颱風路徑上，在七、八月份時常遭受到颱風的衝擊，且颱風常帶來充沛的雨量，導致有嚴重的淹水情況，造成民眾生命與財物損損失。近幾年，人口和社會經濟的發展迅速增長，而伴隨著極端雨量的發生，洪水對整個社會的衝擊也跟隨提高。對於災害衝擊之評估分析，除了運用工程的手段來減少洪澇災害，風險管理的概念也是個重要的解決方法。本研究將發展社會脆弱度指標並與災害作一結合，來定義出洪災之風險大小。 本研究將水災風險的概念應用在台北市中央區，包括士林區、大同區、中山區、松山區、萬華區、中正區、大安區、信義區、南港區和文山區，一共十個區域，為探討台北市地區之水災風險的空間分布關係，本文運用模糊德爾菲法(Fuzzy Delphi Method, FDM)以及層級分析法(Analytic hierarchy process, AHP)，來選擇社會脆弱度因子及訂定這些因子的權重。而在災害的部分，選用40m的網格大小來模擬六種不同重現期距之淹水情況，此六種重現期距為5年、10年、20年、50年、100年及200年。最後將社會脆弱度指標結合淹水潛勢的資訊，以村里為尺度大小來呈現每個村里的風險值，以地圖作展示。考慮村里層級之災害風險分析，其結果可以幫助政府了解在哪些地區是台北市中央區較脆弱之區域，且在此區域規畫更多的資源設備，來減少洪水的衝擊。

Taiwan is on the typhoon path of the East Pacific Ocean Region. Typhoons often bring heavy rainfall in July and August, and cause severe flooding that result in serious losses of life and property. The population and the development of socio economic in urban areas have been grown rapidly in recent years. Along with the increasing extreme rainfall events in Taiwan, the impact of flooding is raising. In addition to apply the structaral methods to reduce the flooding disaster, the concept of risk management is also an important issue for now. The Social Vulnerability Index was developed in the study to determine the flood risk by combining the hazard information. This paper presents the process of constructing a flood risk map in Central Taipei Area (CTA), including ten districts of Shilin, Datong, Zhongshan, Songshan, Wanhua, Zhongzheng, Da’an, Xinyi, Nangang and Wenshan, and applies the FDM (Fuzzy Delphi Method) and AHP (Analytic Hierarchy Process) to select the social vulnerability indices (SVI) and set up the weights of these indices. The SVI is calculated at the district level, which has an area of about 10 km2. For the hazard part, the flood potential information was simulated by a hydraulic model using a regular grid with 40m resolution, and simulates the return period 5-year, 10-year, 20-year, 50-year, 100-year and 200-year for 6 cases. The district level was too coarse to represent the spatial distribution of inundation such that the flood hazard was integrated into village level that has an area about 0.2 km2. The SVI was combined with the flood potential information to determine the flood risk indices for each village. By considering the temporal variation of demographical data, the study further demonstrated that change of social vulnerability indices and the risk. The analyzing results can help the city government to realize the most vulnerable area within the CTA. Hence, the resources for flood damage reduction can be allocated to reduce the risk of community of Taipei City.

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