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DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 童慶斌 | zh_TW |
dc.contributor.advisor | Ching-Pin Tung | en |
dc.contributor.author | 薛聖儒 | zh_TW |
dc.contributor.author | Sheng-Ju Shueh | en |
dc.date.accessioned | 2024-02-26T16:27:48Z | - |
dc.date.available | 2024-02-27 | - |
dc.date.copyright | 2024-02-26 | - |
dc.date.issued | 2022 | - |
dc.date.submitted | 2002-01-01 | - |
dc.identifier.citation | 1.林茂文,(1993),「時間數列分析與預測」,華泰書局。 2.陳奕弦,(1997),「以時間序列模擬複層地盤沉陷量化關係之建立」,國立中興大學土木工程學系碩士論文。 3.柳雅瀞,(1997),「邊坡位移預測之非線性系統動態分析」,國立成功大學資源工程研究所博士論文。 4.楊智堯,(1998),「類神經網路於邊坡破壞潛能分析之應用研究」,國立成功大學土木工程研究所碩士論文。 5.陳志忠,(2009),「地滑地排水設施成效減訂方法研究」,國立中興大學土木工程學系碩士論文。 6.楊奕農,(2009),時間序列分析:「經濟與財務上之應用 第二版」,雙葉書廊有限公司。 7.彭柏豪、劉達生,(2009),「國君主要用由預算編列價訂定之研究」,2009第十七屆國防管理學術暨實務研討會論文。 8.曹榮軒(2019). 氣候變遷調適演算法之法展與應用.臺灣大學生物環境工程學研究所 學位論文 9.行政院農業委員會水土保持局台中分局,(2021),「110 度大梨山地區地滑地與臺中市和平區潛在大規模崩塌監測計畫」。 10.科技部(2021)。IPCC氣候變遷第六次評估報告之科學重點摘錄與臺灣氣候變遷評析更新報告。檢自: https://tccip.ncdr.nat.gov.tw/km_abstract_one.aspx?kid=20210810134743 11.科技部(2022)。IPCC氣候變遷第六次評估報告「衝擊、調適與脆弱度」之科學重點摘錄與臺灣氣候變遷衝擊評析更新報告。檢自:https://tccip.ncdr.nat.gov.tw/km_abstract_one.aspx?kid=20220301094534 12.科技部(2021)。IPCC氣候變遷第六次評估報告之科學重點摘錄與臺灣氣候變遷評析更新報告。檢自: https://tccip.ncdr.nat.gov.tw/km_abstract_one.aspx?kid=20210810134743 13.科技部(2022)。IPCC氣候變遷第六次評估報告「衝擊、調適與脆弱度」之科學重點摘錄與臺灣氣候變遷衝擊評析更新報告。檢自:https://tccip.ncdr.nat.gov.tw/km_abstract_one.aspx?kid=20220301094534 14.行政院農業委員會水土保持局,(2022),水土保持局大規模崩塌警戒發布與解除作業指引(2022) 15.Adamowski,(1983),Stochastic Systems Model of Groundwater Level Fluctations, Journal of Hydrology,No.62,pp129-141. 16.Maidment, D. R. and S. P. Miaou (1985),Transfer Function Models of Daily Urban Water Use, Water Resources Res., Vol.21, No.4, pp.425-432. 17.J.P.T. Caris, Van Asch. (1991). Geophysical, geotechnical and hydrological investigations of a small landslide in the French Alps. Engineering Geology 31 249-276. 18.McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration of time scales. Eighth Conference on Applied Climatology, American Meteorological Society, Jan17-23, 1993, Anaheim CA, 179-186. 19.Box and Jenkins(1994),Time Series Analysis Forecasting and Control,Prentice-hall inc. 20.Van Asch, J. Buma, Van Beek (1999). A view on some hydrological triggering systems in landslides. Geomorphology 30 23-32. 21.Peter J.Brockwell and Richard A.Davis,(2002),Introduction to Time Series and Forecasting,Second Edition, Springer, Berlin, Germany. 22.Mohammed H.I. Dore. (2005) Climate change and changes in global precipitation patterns. Environment International 31 1167-1181 23.Mikko I. Jyrkama , Jon F. Sykes. (2007). The impact of climate change on spatially varyinggroundwater recharge in the grand river watershed(Ontario). Journal of Hydrology 338, 237-250. 24.Mahmudur Rahman , A.H.M. Saiful Islam, Shah Yaser Maqnoon Nadvi, Rashedur M Rahman. (2008). Comparative Study of ANFIS and ARIMA Modelfor Weather Forecasting in Dhaka. Department of Electrical Engineering and Computer Science, North South University. 25.Kevin E. Trenberth. (2011).Changes in precipitation with climate change. National Center for Atmospheric Research, Box 3000, Boulder, Colorado 80307 26.Ching-Weei Lin, Chih-Ming Tseng. (2013) Recognition of large scale deep-seated landslides in forest areas of Taiwan using high resolution topography. Journal of Asia Earth Science 62 389-400. 27.Ruey S. Tsay ,(2014), Multivariate Time Series Analysis with R and Financial Applications, John Wiley & Sons, New York, USA. 28.WBCSD. (2018). CEO Guide to Water. Retrieved from https://www.wbcsd.org/Programs/Food-and-Nature/Water/Resources/CEO-Guide-to-Water-building-resilient-business 29.Intergovernmental Panel on Climate Change. (2022). Sixth Assessment Report. https://www.ipcc.ch/assessment-report/ar6/ | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91921 | - |
dc.description.abstract | 近年來臺灣受氣受變遷影響導致降雨型態改變,降水強度增加及延時縮短造成極端降雨事件頻傳,臺灣山區災害類型從以往單一型災害,演變成複合型災害,2009年莫拉克颱風導致山區多處嚴重土砂災害即為明顯案例,造成中南部山區同時發生地滑、土石流和堰塞湖造成嚴重的人員傷亡和破壞。為應對複雜的災害型態,2010年起行政院農業委員會水土保持局依地質型態及空載光達資料,劃定227個大規模崩塌潛勢區域,並於各崩塌潛勢區域進行調查規畫及裝設相關地表、地中監測儀器,作為未來發布警戒基準值參考依據。 為有效掌握大規模崩塌及地滑災害,地下水位扮演重要的因子,但國內外對於地下水位作為防災預警相關研究卻不多,本研究採用自回歸移動平均整合模式(Autoregressive Integrated Moving Model, ARIMA),選擇臺中市和平區3處大規模崩塌(D038、D050及T003)內自動化監測站作為研究測站,各站均超過13年監測且位處於保全住戶周邊,利用各站2009年莫拉克颱風作為訓練,及選用其它2場極端降雨事件之時雨量及時地下水位變化資料作為模式驗證,以建立各站之ARIMA模型參數、轉換函數,為模擬地下水位變化輔助將水保局情資研判中心發布警戒基準之依據。 由各測站之極端降雨事件ARIMA模擬成果可知,S1和A1測站實際觀測與模擬地下水位變化趨勢相近,峰值及到達延時均可成功模擬,有助於大規模崩塌區D038及D050後續地下水位警戒值發布參考;但大規模崩塌區T003之J1測站之模擬成果與觀測值具有明顯落差,且峰值及延時明顯落後,則不適用於警界發布參考,研判係人為工程構造物影響地下水位變化導致;可知ARIMA模型係可以助於決策者發布警戒值之參考,仍建議應持續蒐集未來極端降雨事件資料,滾動檢討ARIMA模型參數,並選擇周邊較無人為影響之測站作為代表測站。 | zh_TW |
dc.description.abstract | In recent years, the rainfall pattern has been changed since precipitation intensity has increased and the duration has shortened in Taiwan. Traditionally, the Taiwanese government focused on the sediment-related disasters only, but typhoon Morakot caused severe casualties and damages in the central Taiwan because of landslides, debris flows and barrier lakes. In order to tackle complicated compound disasters, the Soil and Water Conservation Bureau (SWCB) has identified 227 large-scale landslide areas which are classified by the size and geological formation. Since then the SWCB has installed real-time monitoring equipment and released warning systems which are based on the past rainfall-induced disasters. Although billions of dollars have been invested in large-scale landslide areas, the SWCB is still unable to effectively release a warming alert of underground water level, and there is a lack of relevant research and application related to monitoring data. Therefore, the study adopts time-series analysis, the Auto-Regressive Integrated Moving Average (ARIMA) model, to simulate the change of underground water which is affected by the rainfall. Under the study, the selected S1, A1 and J1 stations are located in 3 large-scale landslide areas D038, D050 and T003 respectively, in the Lishan area, Taichung City. These stations have observed more than 13 years, and are located in major villages. The study establishes 3 different models for each station and applies the data from the typhoon Morakot which has the biggest accumulated rainfall to train these models. Then, each model has input the rainfall and underground water data from other 2 representative rainfall events with the highest record of underground water level and slope-land movement to verify the results of simulation. The main outputs are (1) the parameters of 3 models and (2) the models to simulate the change of underground water by input the rainfall data, and the study aim to help decision-makers to issue a landslide alert in the SWCB. The results of the simulation show that the data from extreme rainfall events such as Typhoon Dujuan, Megi, Soudelor and 15-days series rainfall in 2016 verifies the parameters of the models effectively. The models of S1 and A1 stations demonstrate positive correlations between the simulated and observed peak and change of underground water, which helps decision-makers to pre-release warming issue in large-scale landslide D038 and D050. However, the result from the model of J1 station in large-scale landslide T003 shows negative correlation in the peak of underground water. It is assumed that the ARIMA models are specific to simulate one station only, and the results could provide the SWCB to issue a warming alert. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-02-26T16:27:48Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2024-02-26T16:27:48Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 總目錄 口試委員審定書 I 誌謝………………………………………………………………………II 摘要……………………………………………………………………III Abstract .V 總目錄 VII 圖目錄 XI 表目錄 .XIII 第一章 前言 …1 1.1 研究動機………………………………………………………1 1.2 研究目的………………………………………………………2 1.3 論文架構………………………………………………………3 第二章 文獻回顧 …4 2.1 氣候變遷造成降雨型態改變…………………………………4 2.2 降雨與地下水對崩塌地影響…………………………………6 2.3 大地工程中常見的地下水模擬………………………………9 2.4 崩塌地警戒基準值之研究…………………………………...11 第三章 研究區域 ……….21 3.1梨山地區區域介紹……………………………………….…..21 3.1.1梨山精華區(臺中市-和平區-D050)……………………..26 3.1.2松茂地區(臺中市-和平區-D038)……………………………27 3.1.3新佳陽地區(臺中市-和平區-T003)………………………….29 3.2梨山地區區域介紹 30 3.2.1區域地形……………………………………………………..30 3.2.2區域地質……………………………………………………..31 3.2.3地形分析……………………..………………………………32 3.2.3地表地質……………………..………………………………33 第四章 研究方法……………………………………………………….. 34 4.1監測資料處理 34 4.1.1時間序列理論 …………………………………………………34 4.1.2平穩型時間序列………………………………………………..36 4.1.2.1自回歸過程(Autoregressive Process) ……………….…..36 4.1.2.2移動平均過程(Moving Average Process) …………….....37 4.1.2.3無定向型時間序列(Nonstationary Time Series)……...…38 4.2模式建立方法…………………………….…………………..….39 4.2.1模式鑑定……………………………………………………….39 4.2.2延伸自我相關函數(Extended Autocorrelation Function)……..40 4.2.3模式檢定方法………………………………………………….42 4.2.4模式之選用準則………………………………….……………43 4.2.5轉換函數模式…………………………………….……………44 4.2.5.1二元交叉相關函數分析………………….……………..44 4.2.5.2轉換函數之基本概念…………………….……………..46 4.2.5.3轉換函數模式鑑定法…………………….……………..48 4.2.5.4角落方法(Corner Method) ……………….……………..49 4.3建立ARIMA模型輔助警戒管理運作………………….….………..49 4.3.1ARIMA與轉換函數之建立…………………………..………..49 4.3.2大規模崩塌潛勢區管理基準值………………….……………51 4.3.3ARIMA模型輔助地下水位警戒發布…………………………52 第五章 結果與討論…………………………………………………...…55 5.1建立ARIMA模型輔助警戒管理運作………………………………55 5.1.1梨山精華區A1自動監測站(臺中市-和平區-D050)………….55 5.1.2松茂地區S1自動監測站(臺中市-和平區-D038)……………..59 5.1.3新佳陽聚落J1自動監測站(臺中市-和平區-T003)…………..62 5.2綜合警戒值輔助發布警戒管理值…………………………………...65 第六章 結論與建議 ……………………………………………….……..68 6.1結論……………………………………………………………….…..68 6.2建議…………………………………………………………………..69 第七章 參考文獻………………………………………………………..71 | - |
dc.language.iso | zh_TW | - |
dc.title | 極端降雨事件下利用時間序列模擬大規模崩塌潛勢區之地下水位變化輔助決策者發布警戒值 | zh_TW |
dc.title | Using Time-Series Analysis to Simulate Underground Water Level to Issue a Warming Alert in Large-Scale Landslide Areas under Extreme Weather | en |
dc.type | Thesis | - |
dc.date.schoolyear | 110-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 許少瑜;李明旭;謝宜桓 | zh_TW |
dc.contributor.oralexamcommittee | Shao-Yiu Hsu;Ming-Hsu Li;Yi-Huan Hsieh | en |
dc.subject.keyword | 大規模崩塌地,地下水水位,自回歸移動平均整合模式,崩塌地預警,輔助決策判斷, | zh_TW |
dc.subject.keyword | Potentially Large-scale Landslide Area,Autoregressive Integrated Moving Model,Underground Water Level,Warming Threshold,Assistant model, | en |
dc.relation.page | 74 | - |
dc.identifier.doi | 10.6342/NTU202203778 | - |
dc.rights.note | 同意授權(全球公開) | - |
dc.date.accepted | 2022-09-26 | - |
dc.contributor.author-college | 理學院 | - |
dc.contributor.author-dept | 氣候變遷與永續發展國際學位學程 | - |
顯示於系所單位: | 氣候變遷與永續發展國際學位學程(含碩士班、博士班) |
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