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論文中文名稱:整合資料同化與分佈式降雨逕流模式於水情測預報平台之研究 [以論文名稱查詢館藏系統]
論文英文名稱:An Integration of Data Assimilation and Distributed Rainfall-Runoff Model in FEWS_Taiwan [以論文名稱查詢館藏系統]
指導教授英文名:Che-Hao Chang
英文關鍵詞:FEWS_Taiwan, Data assimilation, distributed rainfall-runoff model
論文中文摘要:洪水預報模式是利用預報降雨加上集水區水文及地文因此推算未來河川水位或流量,以利防災決策者有足夠之反應時間做出防災決策。因此,洪水預報成果為防災決策者選擇防災決策之重要依據。目前水利署已利用水情測預報系統FEWS_Taiwan完成河川定期定時自動預報模式架構,而為提供更準確之模式預報成果,本研究欲將此架構上建立更高解析度模式及資料同化(Data assimilation)機制。
論文英文摘要:Flood Forecasting Model predicting the river water level and discharge by using forecasting rainfall and catchment area's Hydrological and Physiographic to in the future. To allow disaster strategists have more reaction time to do mitigation strategies. Thus, the result of the flood forecasting have become the basis of the mitigation strategies. Currently ,Taiwan Water Resources Agency has been completed auto regular forecasting model architecture by FEWS_Taiwan. And to provide a more accurate result of the prediction of the model . In this research, we built this architecture on a higher resolution and data assimilation mechanism.
In order to high-resolution model and data assimilation, this research chose distributed rainfall-runoff model wflow and data assimilation toolbox software OpenDA, then using the FEWS_Taiwan and OpenDA the functions of integration external mode and to implementing the integrate interfacing. The result of this research provide integrate open source ,include data exchange ,versions of open source, system requirements, workflow setup and time efficiency assessment. In the end, this research using five typhoon events to verified the interfacing of the achievement.
論文目次:摘 要 i
誌 謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究動機與目的 1
1.2 文獻回顧 2
1.2.1 模式整合 2
1.2.2 資料同化 3
1.2.3 資料同化工具 4
1.2.4 降雨逕流模式 5
1.3 研究架構與方法 8
第二章 即時資料同化之整合 11
2.1 OpenDA資料同化軟體工具箱 11
2.1.1 OpenDA銜接外部模式 12
2.1.2 OpenDA執行流程 14
2.1.3 Kalman Filter 17
2.1.4 Ensemble Kalman Filter 19
2.2 FEWS_Taiwan水情測預報平台 21
2.2.1 平台銜接外部模式 23
2.2.2 平台工作流程模組 26
2.3 整合概念 27
第三章 分佈式降雨逕流模式 28
3.1 模式理論 28
3.1.1 降雨截流模式 30
3.1.2 土壤模式 31
3.1.3 運動波模式 34
3.2 模式環境建立 37
3.2.1 版本與系統環境設定 37
3.2.2 模式靜態資料建置 38
3.2.3 模式參數建置 41
3.2.4 模式模擬資料 43
3.3 模式參數訂定 44
第四章 系統整合與實作案例 55
4.1 系統整合設定 55
4.1.1 FEWS_Taiwan平台設定檔建置 56
4.1.2 OpenDA設定檔建置 68
4.2 Ensemble Kalman Filter應用 75
4.2.1 卡玫基颱風事件 77
4.2.2 薔蜜颱風事件 78
4.2.3 莫拉克颱風事件 79
4.2.4 凡那比颱風事件 80
4.2.5 南瑪都颱風事件 81
4.3 時間效率評估 82
第五章 結論與建議 84
5.1 結論 84
5.2 建議 85
參考文獻 87
附錄 90
A:wflow模式參數與敏感度分析 90
論文參考文獻:[1] Albrecht H. Weerts, Jaap Schellekens and Frederiek Sperna Weiland, ”Real-Time Geospatial Data Handing and Forecasting: Examples from Delft-FEWS Forecasting Platform/System”, IEEE Jouranal of selected topics in applied earth observations and remote sensing, vol. 3, 2010, pp.386-394.
[2] Barker, D., W. Huang, Y.-R. Guo, A. J. Bourgeois,and Q. N. Xiao, ” A three-dimensional variational data assimilation system for MM5:Implementation and initial results”, Mon. Wea. Rev,No.132,2004,pp.897-914.
[3] Bergström, S.,” Development and application of a conceptual runoff model for Scandinavian catchments”, SMHI,No.7,1976.
[4] Beven, K.J., Kirkby, M.J.,”PHYSICALLY BASED, VARIABLE CONTRIBUTING AREA MODEL OF BASIN HYDROLOGY”, Hydrol Sci Bull Sci Hydrol,vol 24,No.1,1979,pp.43-69.
[5] Bishop, C.H., Brian J. Etherton, and Sharanya J. Majumdar,” Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects”,Monthly Weather Review,vol 129,No.3,2001,pp.420-436.
[6] Chiu Chao-Lin,”Applications of Kalman Filter to Hydrology, Hydraulics, and Water Resources”,proceedings of AGU Chapman Conference,Pittsburgh,1978,pp.783.
[7] Chow, V.T., Maidment, D.R., and Mays, L.W. (1988). Applied Hydrology, McGraw-Hill, New York, USA.
[8] David Aubert*, Ce´cile Loumagne, Ludovic Oudin,” Sequential assimilation of soil moisture and streamflow data in a conceptual rainfall–runoff model”, Journal of Hydrology,vol.280,No.1-4,2003,pp.145-161.
[9] Derber, J.C.,D. F. Parrish, and S. J. Lord,” The new global operational analysis system at the National Meteorological Center”, Wea. Forecasting, vol 6, 1991, pp538-547
[10] Evensen, G.,” Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics”, Journal of Geophysical Research,vol 99,No.C5,1994,pp.10143-10162.
[11] Finnegan, N.J., Roe, G., Montgomery, D.R., Hallet, B., “Controls on the channel width of rivers: Implications for modeling fluvial incision of bedrock”, Geology, vol 33, 2005, pp229-232
[12] Hino, M,”On-line prediction of hydrologic system”,vol 4,1973,pp121-129.
[13] Japp Schellekens,wflow documentation release 0.9,2012.
[14] Kalman, R.E.,” A New Approach to Linear Filtering and Prediction Problems”, Journal of Basic Engineering,No.82,1960,pp.35-45.
[15] Lee, K. T., and Ten, B. C. “Geomorphology and kinematic-wave based hydrograph deviation”, Journal of Hydraulic Engineering, vol 123, 1997, pp73-80
[16] Liang Feng and Paul Palmer,PyOSSE:A python package for Observation System Similation Experiments,2013.
[17] Melanie Trudel,Robert Leconte,Claudio Paniconi,” Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations”, Journal of Hydrology,vol.514,no.6,2014,pp.192-201.
[18] Sander Janssen, Ioannis N. Athanasidis, Irina Bezleokina, Rob Knapen, Hongtao Li, Ignacio Pérez Dominhuez, Andrea Emilio Rizzoli, Martin K. van Ittersum. ” Linking models for assessing agricultural land use change”, Computers and Electronics in Agriculture, Vol.76, 2011, pp.148-160.
[19] Sherman, L.K., ”Streamflow from rainfall by the unit-graph method”, Engineering News Record, Vol.108, 1932, pp.501-505.
[20] Vertessy, R.A. and H. Elsenbeer, ”Distrubuted modelling of storm flow generation in an Amazonian rainforest catchment: effects of model parameterization”, Water Resources Research,vol 35,No.7,1999,pp.2173-2187.
[21] Wen-Cheng Huang,”KALMAN FILTER EFFECTIVE TO HYDROLOGIC ROUTING?”,Journal of Marine Science and Technology,vol.7,no.1,1999,pp.65-71.
[22] Whitaker, J.S., Hamill T.M.,” Ensemble Data Assimilation without Perturbed Observations”,Monthly Weather Review,vol 130,No.7,2002,pp.1913-1924.
[23] Wood EF, Szollosi-Nagy A,”Real-Time Forecasting/Control of Water Resource Systems”, IIASA Proceedings Series,vol 8,1980.
[24] Shen, J.C., Chang, C.-H., Wu, S.-J., Hsu, C.-T., Lien, H.-C.,”Real-time correction of water stage forecast using combination of forecasted errors by time series models and Kalman filter method”, Stochastic Environmental Research and Risk Assessment, 2015.
[25] Sten Bergström, Development and Application of a Conceptual Runoff Model for Scandinavian Catchments,Lund, University of Lund,1976,pp.134.
[26] Xianhong Xie,Dongxiao Zhang,” Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter” Advances in Water Resources,vol.33,no.6,2010,pp.678-690.
[27] Yang S-C, E. Kalnay and T. Miyoshi, ”Accelerating the EnKF Spinup for Typhoon Assimilation and Prediction”,Wea. Forecasting,No.27,2012,pp.878-897.
[28] Z. Fred Zhang,” Soil Water Retention and Relative Permeability for Conditions from Oven-Dry to Full Saturation”,Vadose Zone Journal,vol 10,No.4,2011,pp.1299-1308.
[29] 台灣省政府農林廳山地農牧局,屏東縣山坡地土壤調查報告,1984。
[30] 余思亮,河川洪水系集預報模式,碩士論文,國立臺灣大學生物資源暨農學院生物環境系統研究所,臺北,2012。
[31] 陳柏愷,介接淹水模式於即時作業平台,碩士論文,國立臺北科技大學土木與防災研究所,臺北,2012。
[32] 曹明君,利用系集卡門濾波器建立具資料同化功能之河川洪水預報模式,碩士論文,國立臺灣大學生物環境系統工程學系暨研究所,臺北,2011。
[33] 黃奕彰,極端降雨事件分散式集水區逕流模式之發展與驗證,碩士論文,國立中央大學水文科學研究所,桃園,2007。
[34] 單信瑜,台灣地下水資源使用與水質現況,水資源教育教師研習活動,2005。
[35] 經濟部水利署,水文氣象觀測整合平台擴充建置(2/2),2009。
[36] 盧惠生、林壯沛、林介龍、黃良鑫、王秋嫻,「台灣中部坡地不同土地利用及降雨強度土壤入滲」,坡地防災學報,第十卷,第一期,2011,第10-26頁。
[37] 邱煌升,以OpenMI架構整合都市降雨逕流模式與雨水下水道模式,碩士論文,國立中原大學,桃園,2008。