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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 鄭克聲(Ke-Sheng Cheng) | |
dc.contributor.author | Kuan-Ming Su | en |
dc.contributor.author | 蘇冠銘 | zh_TW |
dc.date.accessioned | 2021-06-16T06:39:11Z | - |
dc.date.available | 2018-08-05 | |
dc.date.copyright | 2014-08-05 | |
dc.date.issued | 2014 | |
dc.date.submitted | 2014-07-30 | |
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(2012). 極端氣候下複合性災害防治之研究-極端降雨情況下水庫防 洪減淤操作策略研究—子計畫二:異常極端降雨量對水文頻率分析之影響與 風險評估(III): 行政院國家科學委員會. 17. 蕭政宗、黃亮芸(2006),台灣地區一日暴雨之區域頻率分析. 2006. 農業工程 學報,53(2),77-94 18. 謝志誠. (2010). 莫拉克颱風八八水災死亡、失蹤及重傷統計. from http://www.taiwan921.lib.ntu.edu.tw/88pdf/A8801M.html 19. 魏國彥與許晃雄(1997),全球環境變遷導論,教育部。 20. Catania, Italy: Fondazione Politecnica del Mediterraneo. 21. Chow, V. T. (1951). A general formula for hydrologic frequency analysis. 59 Transactions, American Geophysical Union, 32, 231-237. 22. Chow, V. T., Maidment, D. R., & Mays, L. W. (1988). Applied hydrology. 23. Council, U. S. W. R. (1967). A uniform technique for determining flood flow frequencies. Retrieved 1st May, 2014, 2014, from http://water.usgs.gov/osw/bulletin17b/Bulletin_15_1967.pdf 24. Dalrymple, T. (1960). Flood frequency analyses, U.S. Geological Survey Water Supply Paper 1543-A, U.S. 25. Franco, C., Soares, A., & Delgado, J. (2006). Geostatistical modelling of heavy metal contamination in the topsoil of Guadiamar river margins (S Spain) using a stochastic simulation technique. Geoderma, 136(3), 852-864. 26. Greenwood, J. A., Landwehr, J. M., Matalas, N. C., & Wallis, J. R. (1979). Probability weighted moments: definition and relation to parameters of several distributions expressable in inverse form. Water Resources Research, 15(5), 1049-1054. 27. Greis, N. P., & Wood, E. F. (1981). Regional flood frequency estimation and network design. Water Resources Research, 17(4), 1167-1177. 28. Gumbel, E. J. (1941). The return period of flood flows. The annals of mathematical statistics, 12(2), 163-190. 29. 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Estimation of the generalized extreme-value distribution by the method of probability-weighted moments. Technometrics, 27(3), 251-261. 35. K. Najib, H. Jourde, S. Pistre, A methodology for extreme groundwater surge predetermination in carbonate aquifers: Groundwater flood frequency analysis, Journal of Hydrology, Volume 352, Issues 1–2, 30 April 2008, Pages 1-15, ISSN 0022-1694, http://dx.doi.org/10.1016/j.jhydrol.2007.11.035. 60 36. Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distributione. Giornale dell'Instituto Italiano degli Attuari, 4, 83-91. 37. Landwehr, J. M., Matalas, N. C., & Wallis, J. R. (1979a). Estimation of parameters and quantiles of Wakeby Distributions: 1. Known lower bounds. Water Resources Research, 15(6), 1361-1379. 38. Landwehr, J. M., Matalas, N. C., & Wallis, J. R. (1979b). Probability weighted moments compared with some traditional techniques in estimating Gumbel parameters and quantiles. Water Resources Research, 15(5), 1055-1064. 39. Liou, J.-J., Wu, Y.-C., & Cheng, K.-S. (2008). Establishing acceptance regions for L-moments based goodness-of-fit tests by stochastic simulation. Journal of hydrology, 355(1), 49-62. 40. McCuen, R. H. (1998). Hydrologic design and analysis. Prentice Hall, New Jersey, 814. 41. Nathan, R. J., & McMahon, T. A. (1990). Identification of homogeneous regions for the purposes of regionalisation. Journal of Hydrology, 121(1), 217-238. 42. Norbiato, D., Borga, M., Sangati, M., & Zanon, F. (2007). Regional frequency analysis of extreme precipitation in the eastern Italian Alps and the August 29, 2003 flash flood. Journal of hydrology, 345(3), 149-166. 43. Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 50(302), 157-175. 44. Ross, S. (1998). Natural Hazards: Nelson Thornes Ltd. 45. Ross, S. M. (2002). Simulation. San Diego: Academic Press. 46. Wallis, J. R. (1981). Risk and uncertainties in the evaluation of flood events for the design of hydraulic structure. (E. Guggino, G. Rossi & E. Todini Eds.). 47. Wallis, J. R. (1982). Hydrologic problems associated with oilshale development. Environmental Systems and Management, edited by S. Rinaldi, 85-102. 48. Webster, R., & Oliver, M. A. (2007). Geostatistics for environmental scientists. John Wiley & Sons. 49. Wu, Y.-C., Liou, J.-J., Su, Y.-F., & Cheng, K.-S. (2012). Establishing acceptance regions for L-moments based goodness-of-fit tests for the Pearson type III distribution. Stochastic Environmental Research and Risk Assessment, 26(6), 873-885. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57248 | - |
dc.description.abstract | 本研究以區域頻率分析法分析臺灣南部 5 縣市、共25 個雨量測站,自1965
年至2011 年間所有颱風事件的8 種選用延時最大降雨量序列,並由半變異元模 式分析空間相關性,以建立伽碼隨機變域模式。由10,000 場模擬事件最大降雨 量中,計算指定條件發生的頻率。 從歷年降雨資料可知,許多長延時的年最大降雨量來自颱風事件,且大多為 同一場。此外,有研究指出2009 年莫拉克颱風期間,許多測站觀測到超過2000 年重現期的降雨。上述情形反映出兩大問題:(1)測站間具有相關性;(2)觀測到 離群值雨量。由於許多測站之記錄年限尚短,離群值的出現會使得參數推估受到 很大的影響,移除離群值又可能無法有效反應真實情況。因此,本研究採用颱風 事件選定延時最大雨量作為研究資料,相較傳統上年最大值序列可有更大樣本數, 其參數推估的不確定性較低,可有效改善離群值的影響。 本研究以K-means 群集分析法作均勻區劃分,考量使區內各站具有較佳的統 計均勻性,採用水文頻率分析常用的標準化方法,將各測站的雨量轉為頻率因子 作為區域變數,可使區域變數之第1、2 階動差皆為常數。 隨機變域模擬需要測站間之共變異矩陣,由於由樣本所建立的共變異矩陣無 法符合半正定條件,因此本研究假設測站間之空間相關性一致,隨機變域滿足二 階定常性假設及內在假設,由半變異元模式建立共變異矩陣。最後透過多變量伽 瑪隨機變數繁衍的技術,繁衍颱風事件各延時的最大雨量頻率因子,再以簡單的 水文頻率分析通式計算即可求得模擬雨量。結果顯示本研究與採用年最大值序列 之頻率分析結果相近,映證前述觀察現象。 本研究成果改善傳統頻率分析方法,可用於計算多測站雨量超越某一定值的 重現期,其模擬的颱風選定延時最大雨量具有空間相關性,可供後續辦理水利工 程規劃設計、災害風險評估之參考。 | zh_TW |
dc.description.abstract | stations in southern Taiwan. A unique feature of
this study is that it considers both the local variability of duration-specific maximum event-based typhoon rainfalls and the spatial correlations of such rainfalls among different stations. Spatial correlation structure was built by variogram modeling of rainfalls of different stations. By simulating large number (10,000 in this study) of realizations of multisite duration-specific maximum typhoon rainfalls, the return period of an event defined by a common exceedance level for several particular stations can be determined. The results of this study demonstrate that the proposed method not only has the capability of yielding local intensity-duration-frequency curves at all individual stations, but also provides reasonable estimates of return periods for events which are defined by rainfalls of the same storm but occurred at a set of different stations. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T06:39:11Z (GMT). No. of bitstreams: 1 ntu-103-R00622040-1.pdf: 8653128 bytes, checksum: 82746ca8f9453d7dc56a4f2de47236e3 (MD5) Previous issue date: 2014 | en |
dc.description.tableofcontents | 第一章緒論............................................................................................................. 1
1.1 研究動機及目的........................................................................................ 1 1.2 本文架構.................................................................................................... 2 第二章文獻回顧..................................................................................................... 3 2.1 頻率分析.................................................................................................... 3 2.2 區域頻率分析............................................................................................ 3 2.2.1 均勻區劃分..................................................................................... 4 2.2.2 適合度檢定..................................................................................... 5 2.2.3 參數推估......................................................................................... 5 2.3 多變量隨機變數模擬................................................................................. 6 第三章理論介紹..................................................................................................... 7 3.1 機率分佈之建模........................................................................................ 7 3.1.1 機率權重動差.................................................................................. 7 3.1.2 線性動差......................................................................................... 8 3.1.3 假設檢定......................................................................................... 9 3.1.4 皮爾遜第三型分佈參數推估......................................................... 12 3.2 半變異元模式理論................................................................................... 15 3.3 多變量伽瑪分佈隨機變數繁衍............................................................... 19 3.4 重現期...................................................................................................... 22 第四章研究方法................................................................................................... 23 4.1 研究地區與資料...................................................................................... 23 4.1.1 水文............................................................................................... 23 4.1.2 觀測站地理及記錄資訊................................................................ 23 4.2 研究流程.................................................................................................. 28 4.3 雨量資料處理.......................................................................................... 29 4.3.1 事件分割....................................................................................... 29 4.3.2 降雨事件篩選................................................................................ 29 4.4 區域模式建立.......................................................................................... 39 4.4.1 均勻區劃分................................................................................... 39 4.4.2 區域變數處理................................................................................ 40 4.4.3 機率分佈檢定................................................................................ 40 4.4.4 參數推估....................................................................................... 43 4.4.5 共變異矩陣................................................................................... 43 4.5 多測站各延時最大颱風降雨量模擬........................................................ 46 4.5.1 共變異矩陣轉換............................................................................ 46 4.5.2 多變量常態分佈隨機變數繁衍..................................................... 46 4.5.3 多變量伽瑪分佈隨機變數繁衍..................................................... 46 第五章結果與討論............................................................................................... 48 5.1 區域頻率分析.......................................................................................... 48 5.1.1 設計雨量....................................................................................... 48 5.1.2 Horner公式係數............................................................................ 48 5.1.3 分析資料不同的結果差異............................................................ 49 5.1.4 莫拉克颱風暴雨之重現期............................................................ 49 5.2 多變量伽瑪分佈隨機變數模擬............................................................... 55 5.2.1 模擬與觀測資料之比較................................................................ 55 5.2.2 研究案例—高屏溪流域災害風險評估......................................... 55 5.2.3 大範圍異常極端降雨事件之分佈情形......................................... 56 第六章結論........................................................................................................... 58 參考文獻...........................................................................................................59 附錄A Horner 公式參數表……………………………………………..……………62 附錄 B 模擬實現值與觀測值之 ECDF 疊繪圖…………………………………….65 附錄C 大範圍異常極端降雨事件散佈圖………………………………………….82 | |
dc.language.iso | zh-TW | |
dc.title | 考慮空間相關之暴雨頻率分析 | zh_TW |
dc.title | Regional Frequency Analysis with Consideration of Multisite Covariance of Typhoon rainfalls | en |
dc.type | Thesis | |
dc.date.schoolyear | 102-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蘇明道(Ming-Dao Su),黃文政(Wen-Cheng Huang),張國強(Kuo-chyang Chang) | |
dc.subject.keyword | 序率模擬,線性動差法,區域頻率分析,伽瑪隨機變域模擬, | zh_TW |
dc.subject.keyword | Stochastic simulation;L-Moment,Regional frequency analysis,Gamma random field simulation, | en |
dc.relation.page | 96 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2014-07-30 | |
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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