Study on Land Subsidence Risk in Near Shore Land Zone at Yunlin County

• Main Authors: Liu, Shao-An, 劉紹安
• Other Authors: Ku, Cheng-Yu
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/at5785

碩士 === 國立臺灣海洋大學 === 河海工程學系 === 106 === Since 1960's, the land subsidence in the near shore land zone of western Taiwan is gradually occurred in over-pumping areas. The coastal areas have become high-risk areas including flooding, storm surges, lowland, and salinization due to the problems of the land subsidence, the sea level rise, and the impact of climate change. In the case of limited resources of the land in Taiwan, how to slow down the speed of the subsidence and to promote the sustainable use of land are the crucial issue to ensure sustainable development of the natural environmental resources. To resolve the problems mentioned above, a disaster risk analysis model for land subsidence was established to conduct disaster risk analysis for the near shore land zone of Yunlin County. The study is to conduct the land subsidence, susceptibility, and vulnerability analyses. The hazard and vulnerability of the land subsidence disasters are analyzed and the results are brought into the risk matrix to produce a risk map. The important topic in risk analysis is to determine the weighting of factors. In this study, we adopted the principal component analysis (PCA) in which the PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables. Through the PCA, we obtained the dominate factors from vulnerable and susceptible groups for the risk analysis. Results obtained demonstrate that compared with the analytic hierarchy process, the principal component analysis has the advantage of rapid and low error and can improve the discrimination of analysis results. In addition, a series of the land subsidence risk maps are established under different scenarios. It is expected that results from this study can be used to propose the measures and the elaboration of adaptation strategies.