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Please use this identifier to cite or link to this item: http://nchuir.lib.nchu.edu.tw/handle/309270000/152246

標題: 降雨誘發崩塌與土石流災害風險降低措施之效益分析
The efficiency of risk reduction programs for rainfall-induced landslide and debris-flow disasters
作者: 吳俊毅
Wu, Chun-Yi
Contributors: 陳樹群
水土保持學系所
關鍵字: 崩塌;土石流;風險評估;益本分析
landslide;debris-flow;risk assessment;benefit-cost analysis
日期: 2012
Issue Date: 2013-11-07 13:17:23 (UTC+8)
Publisher: 水土保持學系所
摘要: 本研究旨在建置崩塌風險分析流程,藉以分析集水區區域之崩塌災害風險分布,依序分析崩塌危害、風險元素之易脆弱性及村里之承受能力,來計算崩塌災害事件中可能造成的財產風險、生命風險與總風險值。首先,結合崩塌空間機率、時間機率及崩塌規模機率,來進行崩塌危害分析。崩塌潛勢相關因子經篩選後包含11個內在地形因子及2個外在降雨因子,以建立崩塌潛勢模型;崩塌規模分析則先建立崩塌面積與非累積個數之冪次關係,再以機率密度函數將其轉為崩塌面積累積機率;最後以不同重現期距降雨之超越機率來做為該事件之時間機率,用以估算集水區發生崩塌面積大於一定規模之年計機率。第二,易脆弱性分析包含以地上物為主的財產易脆弱性與以人命為主的生命易脆弱性。土地利用可被分為建築物、住宅、農地、林地、道路、水域及無直接損失等9種風險元素型式,並針對不同風險元素給予其單位面積的價值。再以損害因數代表不同風險元素實際災損值與其本身價值的平均比例,由此分析財產易脆弱性。生命易脆弱性則以生命價值和居民在屋內的死亡率來進行量化分析。第三,由村里防災整備架構可知,村里承受能力係由「舉辦防災演練」、「土石流觀測站」、「民眾自主觀測」與「土石流防災專員」四部分所組成。因此,可由村里檢核表所得到的分數與各項目之權重來計算村里承受能力。最後,依據年計崩壞比、財產易脆弱性計算結果繪製財產風險地圖;而將年計崩壞比、生命易脆弱性與承受能力結合以評估生命風險,並與財產風險相加成總風險地圖。本研究亦針對石門水庫集水區防災管理措施實施前後之風險進行分析,以得到防災措施的效益值;再將效益值與防災措施之成本進行益本分析。防災措施益本比較高之村里有華陵村、義盛村、秀巒村及高義村,均為年計生命風險較高之村里。義盛村益本比雖已達192.19,但承受能力僅0.5716,說明其仍可透過加強防災管理措施來降低生命風險。整體集水區防災措施之益本比遠大於1,代表目前所實施防災措施之效益大於投資成本,為合乎經濟效用的方案。由因子之敏感度分析結果並可知,易脆弱性及死亡率之改變會加大風險值之不確定性,而年利率變大或生命週期變小使得防災措施之益本比變小,但對效益分析而言,並不影響其具有經濟效益之結果。
The purpose of this research is to establish the landslide risk analysis procedures by which the disaster risk distribution within the watershed was analyzed. Orderly, this research analyzed the landslide hazard, the vulnerability of elements at risk, and the resilience capacity of village to calculate the values of property risk, life risk and total risk possibly caused landslide disasters. First, the landslide hazard assessment included the landslide spatial probability, temporal probability and probability of landslide area. Eleven geomorphological factors and two rainfall factors, evaluated as effective factors because of the higher correlation with the landslide distribution, were regarded in the landslide susceptibility model. The probabilities of landslide area were developed by transforming the power law formula in the landslide frequency-area distribution. Then, the landslide spatial probability and exceedance probability of different rainfall events as well as the probability of landslide area were used to predict annual probability of each slope-unit with a landslide area more than a threshold. Second, vulnerability analysis included the vulnerability of property above land and the vulnerability of human life. The land-use layer was divided into building, house, farmland, forestland, road, water area and no-direct-loss, nine types of element at risk, and the value of its unit area was given against different elements at risk. Then, damage factor was used to represent the average proportion between the actual disaster loss of different elements at risk and the values of elements at risk themselves, and by which property vulnerability was analyzed. The life vulnerability was carried out quantitative analysis by assessment life value and the mortality rate of people in buildings. Third, from the framework, the village resilience capacity consisted of four parts: “the participation experience of disaster prevention drill”, “real-time monitoring system”, “the observation of the one’s own rainfall gauge” and “professional debris-flow volunteer”. Therefore, the scores got from village’s checklist, as well as the weight of every item were used to calculate village resilience capacity. Finally, according to the annual landslide probability and vulnerability result of property, the property risk map was drawn; next the annual landslide probability, vulnerability of life, and resilience capacity were combined to assess life risk; then the total risk map was drawn. This research also carried out risk analysis before and after risk reduction measures held in Shihmen reservoir watershed to get benefit value of different measures. Then benefit-cost analysis was conducted based on benefit value and the cost of risk reduction measures. Villages with high benefit-cost ratios of measures are Hua-Ling, Yi-Cheng, Xiu-Luan and Gao-Yi, which also suffer high annual life risk. The Yi-Cheng village with a high benefit-cost ratio of 192.19 and a low resilience capacity of 0.5716 could reduce its life risk by strengthening the risk reduction measures. The benefit-cost ratio of measures for whole watershed is markedly greater than 1.0. Analytical results showed that the risk reduction measures are cost-effective. Based on the results of sensitivity analysis, the change of property vulnerability and mortality rate would increase the uncertainty of risk values. Additionally, the higher interest rate or shorter life term would decrease the benefit-cost ratio. Nevertheless, the replacement of the mentioned factors does not reverse the cost-effective inference.
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