工學院: 土木工程學研究所指導教授: 林美聆賴均銘Lai, Jun-MingJun-MingLai2017-03-132018-07-092017-03-132018-07-092015http://ntur.lib.ntu.edu.tw//handle/246246/2781522010年3月4日上午8時18分，台灣西南部發生芮氏規模6.4的甲仙地震，造成人民受傷、房屋傾斜及許多建築物損毀，也造成南部地區發生多起液化事件。由於在國內外許多地震事件中，經常發現地下水位在地震發生前後有異常變化之現象，因此，經濟部水利署在台灣地區設置高密度的地下水觀測井，而在發生甲仙地震的這段期間，嘉南平原一帶的水位觀測井分別記錄了當時地下水位所產生的變化。 本研究以嘉南平原為研究區域，選定竹圍、貴林、平溪、歡雅、下營及總爺等六站，利用地質調查所提供的地層柱資料，建立了各分析井的簡化剖面，並輸入中央氣象局設置的全國強震測站所提供的加速度歷時資料，最後進行富水地層受震之數值模擬，輔嘉南平原地下水位監測井網之水位變化資料作驗證，並探討不同地下水受震模式之適用情形。 為能了解富水層受地震力作用下其孔隙水壓變化的關係，本研究首先使用SHAKE程式當中的反卷積(Deconvolution)計算功能推得地下水觀測井基盤位置的地震加速度歷時資料，再利用FLAC程式建立地下水觀測井的地層剖面，輸入地震加速度歷時記錄，藉由數值軟體得到分析結果，以了解地震與地下水位變化之相關機制。 本研究利用有限差分軟體 FLAC 程式建構孔隙水壓力動態反應模式的模型，同時以Finn及Biot兩種模式進行分析，進一步根據嘉南平原的地下水觀測井網，於甲仙地震發生前後所記錄到的實際地下水位變化量等資料，與數值分析結果進行比較及討論。分析後發現以Finn模式進行的模擬成果較Biot模式來的優異；另外，地下水位變化分為階變反應變化及振盪反應變化，由Finn模式中可看出明顯的階變反應變化，而Biot模式則呈現振盪反應變化，此外Finn模式的激發量較大，Biot模式的孔隙水壓變化量則是集中在一範圍內。 比較數值分析結果與實際地下水位觀測變化，主方向輸入震波模擬結果較東西向及南北向輸入震波模擬結果較佳，此與斷層錯動、震波傳遞方向有關，主方向輸入震波為觀測井與震央之連線方向震波，與甲仙地震震波的主要方向一致，因此，以主方向輸入震波去模擬效果最為優異。 整體而言，以Finn模式進行數值模擬的結果中，富水層一及富水層二的模擬成效良好，雖與實際地下水位變化有所差距，但變化趨勢是吻合的，也與地表加速度尖峰值趨勢有正相關，但與震央距離關係則較不顯著；以Biot模式進行數值模擬的結果中，富水層一模擬結果較佳，與地表加速度尖峰值趨勢稍微相關，富水層二模擬結果則較差，這表示以Biot模式進行數值模擬適用於淺層土壤，深層土壤之模擬較不理想。 最後，利用模擬結果所得到的參數，計算出的各觀測井的壓密係數，發現壓密係數與數值模擬的地下水變化量有關，壓密係數越小，孔隙激發的地下水變化量則越大；另外，壓密係數於地震初期及地震後期的變化幅度與地表加速度尖峰值也有相關，地表加速度尖峰值越大，壓密係數的變化幅度就越大。In 2010, Jia-Sian earthquake hit Taiwan, causing casualties, house collapses, and landslides, also caused many liquefaction cases in the alluvial plain of southern Taiwan. Groundwater level changes during earthquakes were recorded widely. The groundwater monitoring network established by the Water Resources Agency to the Jianan Plain recorded the groundwater level changes during the Jia-Sian earthquake. In this research, records of six wells were chosen for simulation from Jianan Plain study area. They are Ju-Wei, Guei-Lin, Ping-Shi, Huan-Ya, Shia-Ying and Tzung-Ye. A simplified stratigraphic column profile was used for the water-rich strata in the earthquake simulation. Results were compared with the data of groundwater monitoring network for validation of water level changes using different modes of pore water excitation for the seismic analysis. In order to understand the seismic behavior of water-rich strata, this research uses SHAKE program for deconvolution of ground motion record as the base motion of groundwater monitoring wells. Then FLAC was used with the simplified stratigraphic profile with input acceleration history for simulating the groundwater level changes caused by earthquakes. Conceptual model of pore water pressure seismic response is constructed using the finite difference program, FLAC where both Finn and Biot modes of pore water pressure generation were used for analysis. Analysis showed that simulation of Finn mode is better than Biot mode. In addition, There are two types of groundwater level changes, step-wise and oscillating changes in response. The simulated water pressure curve from the Finn mode shows reactions of step-wise changes, and Biot mode exhibits oscillating changes. Finn mode triggered a large amount of the pore water pressure, while in Biot mode the pore pressure change is limit to some range. Comparing numerical results with the observed data, the results of input primary-direction ground acceleration is better than input E-W and N-S ground acceleration. This is related to the fault dislocation and seismic wave transmission direction. Therefore, the simulation results with Primary ground acceleration is the best. Generally speaking, simulation results of Finn mode of Aquifer 1 and 2 are fairly good. There are differences between the simulation results in Finn mode and the recorded groundwater level changes. The variations of simulated results with the peak ground acceleration are positively correlated, but irrelevant with the epicenter distance. Biot mode in ground water changes results in a small range, and only Aquifer 1can obtain good simulation results, when the depth increasing, the simulation of pore pressure change has not changed much. Finally, by using the parameters of the simulation results to calculate the coefficient of consolidation in the observation well, the variations of simulated results with the coefficient of consolidation are found good correlation. In addition, the change of coefficient of consolidation also correlated well with the peak ground acceleration.10829394 bytesapplication/pdf論文公開時間: 2017/8/21論文使用權限: 同意有償授權(權利金給回饋學校)地震地下水位動態孔隙水壓Finn模式Biot模式壓密係數earthquakegroundwater level changesdynamic pore pressureFinn modeBiot modethe coefficient of consolidationthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/278152/1/ntu-104-R02521125-1.pdf