坡地災害社會脆弱度指標評估與應用

Assessing and Applying Social Vulnerability Index of Slope-land Disasters (SVIoL)

921地震之後，坡地災害發生之次數明顯的增加，使得坡地住民的受災風險因而提升。這十年來政府雖積極進行許多整治工作，但由於氣候變異影響逐漸顯著，使得短延時且強降雨的致災事件增多，例如：2009年的莫拉克颱風夾帶超過兩百年頻率的超大豪雨，釀成全台共1690處的坡地災害、130處道路中斷、196座橋梁損毀以及699人死亡等嚴重災情。過去依據物理脆弱度因子（有效集水面積、岩體之破碎程度、通過之斷層長度、崩塌面積等）來進行的預警工作，雖可針對山坡地的自然環境進行監控，但若要改善坡地災害造成的損失與傷亡，亦不可忽略對山坡地社會脆弱因素的探討與分析，才能理解社會系統面對自然災害時的抵抗能力，藉以有效降低災害衝擊。本文將坡地災害之社會脆弱度因素分類為四個取向，包括：(1)可能的最大損失（保全人數、結構物損失、家俱家電、交通工具的損失），(2)環境建設（土地使用、道路交通），(3)自保能力（依賴人口、警消人力、避難所與受災次數等），(4)復原與適應能力。同時為了使研究成果得以落實於現今防災工作，本文使用帕累托等級分析法（Pareto ranking），建立分項及綜合之評估指標。最後，透過GIS圖層的繪製，空間化不同地區之社會脆弱度，使之易於結合坡地災害之區域分布特性。指標評估結果發現，屏東縣、台東縣內高脆弱鄉鎮最多，依比例來說，嘉義市與桃園縣內的高脆弱鄉鎮市區比例最高，這四個縣市是坡地災害衝擊下，高社會脆弱度區，此外，若套疊坡地歷史災點更可發現，南投縣信義、水里、埔里鄉，新竹縣尖石鄉、苗栗縣泰安鄉等，是坡地災害的高風險地區。藉由指標的評估結果有助於災害防救單位進行適切的災前減災規畫、災時應變評估與災後復原策略擬訂等防災工作。

This study constructs a framework of social vulnerability index of slope-land disasters, and assesses the idea of social vulnerability by analyzing a group of factors classified by the framework of SVIoL. The number of landslide disasters increased significantly after the Chi-chi earthquake, putting residents of mountain areas at higher risk of debris flow or landslide. The government has revised numerous engineering design over the past decade to reduce the risk of slope-land disasters. However, weather events still cause enormous damage. For example, Typhoon Morakot caused the heavy rainfall breaking the historical records, and resulted in 1,690 landslide/debris flow events, 130 broken roads, 196 damaged bridges and 699 deaths. This disaster revealed that disaster management needs go beyond merely evaluating physical vulnerability or building engineering facilities, and that social vulnerability index assessment is a potential means of improving disaster management and catastrophe resistance. The framework of SVI has four important aspects attributed by previous studies: 1) maximum loss of household property, 2) environmental engineering, 3) resistance to slopeland disasters, and 4) self-recovery ability. Pareto ranking (PR) analysis was applied to integrate the four aspects, and to rank the intensity of SV scores of each town, where higher ranks indicated greater vulnerability. Pingtung and Taitung counties have the highest number of towns assigned to the highest rank, while Chiayi City and Taoyuan County have the highest percentage of towns with the highest PR. Furthermore, after overlapping the historical landslide hotspots with the SVI layer, the most risky places are Shueili, Shini and Puli in Nantou County, Jianshi in Hsinchu County, and Taian in Miaoli County. SVIoL can help not just local governments but also central government understanding the disaster vulnerability of different places, and adjust their disaster prevention, response and recovery strategies accordingly.