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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 廖國偉(Kuo-Wei Liao) | |
dc.contributor.author | Ting-Hsuan Hsu | en |
dc.contributor.author | 許庭瑄 | zh_TW |
dc.date.accessioned | 2021-06-16T08:05:07Z | - |
dc.date.available | 2022-07-03 | |
dc.date.copyright | 2020-07-27 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-07-20 | |
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Journal of Geotechnical and Geoenvironmental Engineering, 131(9), 1097-1107. doi:doi:10.1061/(ASCE)1090-0241(2005)131:9(1097) 5. Fannin, R., Rollerson, T. (1993). Debris flows: some physical characteristics and behaviour. Canadian Geotechnical Journal, 30(1), 71-81. 6. Franks, C. (1999). Characteristics of some rainfall-induced landslides on natural slopes, Lantau Island, Hong Kong. Quarterly Journal of Engineering Geology and Hydrogeology, 32(3), 247-259. 7. Glastonbury, J., Fell, R. (2000). Report on the analysis of “rapid” natural rock slope failures, University of New South Wales School of Civil and Environmental Engineering UNICIV Report No. R-390. 8. Giannecchini, R. (2006). Relationship between rainfall and shallow landslides in the southern Apuan Alps (Italy). 9. Hungr, O., Morgan, G., Kellerhals, R. (1984). Quantitative analysis of debris torrent hazards for design of remedial measures. Canadian Geotechnical Journal, 21(4), 663-677. 10. Haas, Tjalling de, Woerkom, Teun van. (2016). Bed scour by debris flows: experimental investigation of effects of debris‐flow composition. Earth Surface Processes and Landforms, 41(13), 1951-1966. 11. Jakob, M., Hungr, O., Thomson, B. (1997). Two debris flows with anomalously high magnitude. In: C-L. Chen (ed), Proceedings of the 1st International Conference on Debris-flow Hazards Mitigation: Mechanics, Prediction, and Assessment (pp. 382-394). American Society of Civil Engineers, New York. 12. Jakob, M., Anderson, D., Fuller, T., Hungr, O., Ayotte, D. (2000). An unusually large debris flow at hummingbird creek, mara lake, british columbia. Canadian Geotechnical Journal, 37(5), 1109-1125. 13. Jakob, Matthias, Hungr, Oldrich, Jakob, Dr Matthias. (2005). Debris-flow hazards and related phenomena (Vol. 739): Springer. 14. Jan, Chyan-Deng, Chen, Tsung-Hsien, Lo, Wei-Cheng. (2007). Effect of rainfall intensity and distribution on groundwater level fluctuations. Journal of Hydrology, 332(3), 348-360. doi: https://doi.org/10.1016/j.jhydrol.2006.07.010 15. King, J. (1996) Tsing Shan Debris Flow (Special Project Report SPR 6/96, 133 pp.). Geotechnical Engineering Office, Hong Kong Government. 16. Li, J. and Yuan, J. (1983) The main features of the mudflow in Jiang-Jia Ravine. Zeitschrift Geomorphologie, 27, 325-341. 17. Okuda, S., Suwa, H., Okunishi, K., Yokohama, K., and Ogawa, K. (1980). Synthetic observation on debris flow. Annals of the Disaster Prevention Research Institute, Kyoto University, 24, 411-448 18. Pan, Huali, Wang, Ren, Huang, Jiangcheng, Ou, Guoqiang. (2013). Study on the ultimate depth of scour pit downstream of debris flow sabo dam based on the energy method. Engineering geology, 160, 103-109. 19. Rickenmann, D., Weber, D., Stepanov, B. (2003). Erosion by debris flows in field and laboratory experiments. In: D. Rickenman and L-C. Chen (eds), Proceedings of the 3rd International Conference on Debris-flow Hazards Mitigation: Mechanics, Prediction and Assessment (pp. 883-893). Millpress, Rotterdam. 20. Revellino, P., Hungr, O., Guadagno, F. M., Evans, S. G. (2004). Velocity and runout simulation of destructive debris flows and debris avalanches in pyroclastic deposits, Campania region, Italy. Environmental Geology, 45, 295-311. 21. Reid, M. E., Christian, S. B., Brien, D. L., Henderson, S. (2015). Scoops3D—software to analyze three-dimensional slope stability throughout a digital landscape. US Geological Survey Techniques and Methods, book, 14. 22. Singh, Vijay P. (1998), “Pearson Type III Distribution”, Entropy-Based Parameter Estimation in Hydrology. 23. Springer, G. S., Dowdy, H. S., Eaton, L. S. (2001). Sediment budgets for two mountainous basins affected by a catastrophic storm: Blue Ridge Mountains, Virginia. Geomorphology, 37, 135-148. 24. Santacana, N., Baeza, B., Corominas, J., De Paz, A., Marturiá, J. (2003). A GIS-based multivariate statistical analysis for shallow landslide susceptibility mapping in La Pobla de Lillet area (Eastern Pyrenees, Spain). Natural hazards, 30(3), 281-295. 25. USGS. (2004). Landslide Types and Processes, U.S., Geological Survey. 26. Varnes D.J(1978), “Slope movement types and processes”, “In: Special Report 176: Landslides: Analysis and Control (Eds: Schuster, R. L. Krizek, R. J.), Transportation and Road Research Board, National Academy of Science, Washington D. C., 11-33. 27. 千木良雅弘(2011),「大規模崩塌潛感區」,科技圖書股份有限公司 28. 日本國土交通省砂防部(2001),「土砂災害防止法」,日本國交通省部出版 29. 日本土木研究所(2008),「深層崩塌潛勢溪流檢出方法說明書」,日本 30. 何岱杰,張維恕,林慶偉,劉守恆(2014),應用數值地形及光學影像於潛在大規模崩塌地形特徵判釋,航測及遙測學刊,第2期,p.109-127。 31. 邱子芸. (2017). 應用Scoops3D於潛在大規模崩塌影響之研究. (碩士), 國立臺灣海洋大學, 基隆市. Retrieved from https://hdl.handle.net/11296/642ctx 32. 水土保持局台北分局(2017),「台9甲10.2K大崩塌安全評估及後續整體調查規劃成果報告書」,行政院農業委員會水土保持局台北分局委託計劃報告。 33. 國家災害防救科技中心 災害事件簿查詢展示系統。https://den.ncdr.nat.gov.tw/ 34. 陳明仁,陳宜欣,張家銓,鄭克聲,林國峰等(2012),「氣候變遷水文情境評估研究(1/2)」,經濟部水利署「氣候變遷對水環境之衝擊與調適研究計畫」科技研究發展專業計畫。 35. 陳宗顯. (2007). 降雨引致地下水位變化之研究-以那菝、六甲與東和地下水位站為例. 國立成功大學, Available from Airiti AiritiLibrary database. 36. 黃柏軒. (2019). 以隨機森林法評估淺層崩塌潛勢. (碩士), 國立臺灣大學, 台北市. 37. 黃楗祐. (2019). 台灣旗山溪集水區崩塌熱區與崩塌潛勢分析. (碩士), 國立成功大學, 台南市. 38. 水土保持局台北分局(2017),忠治二號橋下游右岸崩塌處理工程-竣工圖 39. 水土保持局台北分局(2018),新北DF230潛勢溪流治理二期工程-竣工圖 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58050 | - |
dc.description.abstract | 坡地災害是台灣常見的天然災害之一,致災因子、災害發生的機制與災後整治工程(或措施)的效益評估,因此成為本研究關著的重點。鑒於坡地災害本質上是以三維的運動方式,本研究首先利用三維模式Scoops3D進行分析、之後輔以二維模式Geostudio探討整治工程(或措施)的效應,其中,諸多因子的不確定性均納入分析的過程中,如雨量、雨型、地下水位、土壤參數與沖刷深度等。 在崩塌發生之前,通常會產生地表特徵如坡頂裂縫或邊坡位移,本研究參考這些地表與地中特徵資訊,應用Scoops3D和粒子群演算法(PSO, particle swarm optimize )推算最佳化滑動面位置,由於選用不同的BPNN訓練架構和最佳化之目標函數,最後挑選出整體誤差較小的11個滑動面,其中3個滑動面的幾何位置近乎一致,且崩塌機率較高,因其最接近真實滑動面位置,故推測為最佳滑動面。 三維模式Scoops3D無法考慮整治措施對邊坡的影響,故本研究應用二維模式Geostudio 建立5個剖面的二維模型,分析各剖面邊坡在延時48小時、重現期50年降雨下的崩塌機率,再以面積加權的方式計算最佳化滑動塊體的崩塌機率,計算結果為0.1956,而應用三維模式Scoops3D分析最佳化滑動塊體的崩塌機率為0.113,兩者的分析結果相近,且如預期地,二維模式的分析結果偏保守側,故初步推斷以二維模式推估整治後三維滑動塊體崩塌機率為可行的方法。 另外再應用Geostudio分析兩個剖面(SB-6剖面和18-5W剖面)邊坡在沖刷深度和重現期降雨下對崩塌機率的影響,分析結果為兩個剖面的崩塌機率皆會受沖刷深度和重現期降雨的影響,其中沖刷深度的影響又更為顯著。 | zh_TW |
dc.description.abstract | Slope disasters are one of the common natural disasters in Taiwan. The hazard factors, disaster occurrence mechanism, and effects of post-disaster remediation projects have therefore become the focus of this research. In view of the fact that slope disasters are essentially three-dimensional movements, this study first used the three-dimensional model, Scoops3D, for analysis, and then supplemented with the two-dimensional model Geostudio to discuss the effects of remediation projects. Among them, the uncertainties of many factors were included in the analysis, such as rainfall, rain type, groundwater level, soil parameters, scouring depth and so on. Before landslide, observations such as tension cracks or displacement of the slope are usually found, so this study first utilizes Scoops3D and particle swarm optimization (PSO) algorithm to optimize the position of the slip surface with the collected information. Due to different BPNN training structures and objective functions of optimization, 11 candidates of slip surface are selected, in which 3 of 11 slip surfaces are almost at the same position, indicating this position possesses a higher landslide occurrence probability, so it is selected and used for further analyses. The three-dimensional model Scoops3D cannot consider the retrofitting method, the two-dimensional model Geostudio is therefore, used to analyze landslide probability with the retrofitting. Several cases are analyzed, for example, to compare the difference between Scoops3D and Geostudio, a case of 50-year returning period and 48-hour rainfall event is considered. Results shown that the landslide probabilities are 0.1956 and 0.113 for Geostudio and Scoops3D, respectively. As expected, the 2D model delivers a similar but more conservative outcome, indicating the proposed 2D analysis framework can provide a reasonable estimation of landslide occurrence probability. In addition, Rainfall has been long recognized as one of the most significant triggering factors for slope failures, Geostudio was used to analyze (slope of SB-6 profile and slope of 18-5W profile) the landslide probability under different scour depths and return-period rainfall events to further illustrate their influence on landslide occurrence probability. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T08:05:07Z (GMT). No. of bitstreams: 1 U0001-1507202014390600.pdf: 8137757 bytes, checksum: 4c0ab987fba3ef9874bc2a12b489f24c (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 致謝 i 中文摘要 ii ABSTRACT iii 目錄 v 圖目錄 vii 表目錄 x 第一章 緒論 1 1.1 研究動機與目的 1 1.2 研究流程 4 1.3 論文架構 7 第二章 文獻回顧 8 2.1 崩塌分類 8 2.1.1 滑動深度分類 8 2.1.2 崩塌型態分類 9 2.2 Scoops3D 15 2.2.1 Ordinary切片法 19 2.2.2 Bishop切片法 (Bishop's Simplified Method) 21 2.2.3 Scoops3D的分析模式 22 2.3 Geostudio 23 2.4 Geostudio和Scoops3D的比較 24 2.5 粒子群演算法( Particle Swarm Optimization, PSO) 25 2.6 倒傳遞類神經網路(Back Propagation Neural Network) 27 第三章 研究區域與資料 29 3.1 研究區域 29 3.2 觀測資料 32 3.2.1 地層資料 32 3.2.2 地下水位 34 3.2.3 邊坡位移資料 37 第四章 研究方法 39 4.1 最佳化滑動面的幾何位置 39 4.2 設計暴雨 43 4.3 以二維模型分析三維滑動塊體的崩塌機率 44 4.4 地下水位預估模式 47 4.5 邊坡崩塌機率 51 第五章 研究結果 57 5.1 最佳化滑動面的結果 57 5.2 以二維模型分析三維滑動塊體崩塌機率的可行性探討 65 5.3 效益評估 67 5.4 重現期降雨和土石流沖刷深度對邊坡崩塌機率的影響 69 第六章 結論與建議 73 6.1 結論與討論 73 6.2 未來建議 75 參考文獻 76 附錄A 82 附錄B 86 附錄C 88 附錄D 90 附錄E 95 | |
dc.language.iso | zh-TW | |
dc.title | 應用Scoops3D進行滑動面位置之最佳化與崩塌機率之分析 | zh_TW |
dc.title | Application of Scoops3D on optimizing slip surface position and analysis of the landslide probability | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 范正成(Jen-Chen Fan) | |
dc.contributor.oralexamcommittee | 鄭克聲(Ke-Sheng Cheng),王晉倫(Chin-Lun Wang) | |
dc.subject.keyword | Scoops3D,邊坡穩定,崩塌機率,不確定性,Geostudio,頻率分析,滑動面位置, | zh_TW |
dc.subject.keyword | Scoops3D,Slope Stability Analysis,Landslide Probability,Uncertainty,Geostudio,Frequency Analysis,Position of Slip Surface, | en |
dc.relation.page | 95 | |
dc.identifier.doi | 10.6342/NTU202001544 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2020-07-20 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
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