水文地質概念模型差異對污染傳輸模擬之影響

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姓名	蔡孟儒(Meng-Ju Tsai) 查詢紙本館藏	畢業系所	應用地質研究所
論文名稱	水文地質概念模型差異對污染傳輸模擬之影響 (The influences of hydrogeological models on simulations of groundwater contaminant transport)
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摘要(中)	本研究自一個既有人造三維地質模型(Synthetic model)產生大量地質鑽孔資料，使用GMS(Groundwater Modeling System)軟體建立地質概念模型，並作為真實地質模型，根據(1)有無使用區域地質知識修正地質概念模型、(2)是否給予鑽孔正確的沉積層序(Horizon ID)，以及(3)不同的鑽孔密度提供之地層層界，建立不同的地質概念模型，並依各地層的異向性設定水力傳導係數，據以建立不同的地下水流模型，以MODFLOW模式搭配MT3DMS模式進行1,1-二氯乙烯與三氯乙烯地下水污染物傳輸模擬，以進一步探討前述三項因素對地質概念模型建置以及對污染傳輸模擬之影響。研究成果顯示，即使有387個鑽孔，仍無法使用GMS軟體內外插出良好的層界不整合面，而使用GMS軟體自動產生鑽孔層序的方法，比使用人為給定正確沉積層序的方法，需要更大量的鑽孔才能內外插出合理的地質概念模型，因此若能正確判斷鑽孔層序，將可使用更少的鑽孔建立合理的地質概念模型。此外，本研究透過所建立的地質概念模型，比對研究區既有監測井開篩段地層，並與觀測水位與降雨量綜合研判，剔除非開篩在同一含水層之監測井，以剩下的29口監測井觀測水位作為地下水流模型之率定標的。不同地下水流模型，率定後RMSE(Root Mean Square Error)差距在1.4公尺以內，然而各模型地下水流場並不相同，且固定深度的污染源，在不同模型中所在的地層亦不相同，因此各模型污染物傳輸模擬結果具有明顯差異，顯示水文地質概念模型對於污染傳輸模擬具有重要影響。
摘要(英)	In this study, a three-dimensional synthetic geological model was used to generate a lot of borehole drillings data. The GMS (groundwater modeling system) software was used to establish a geological models. The discussion of differences between models was made whether the different density of borehole drillings, the knowledge of regional geology and given the correct sedimentary sequence (Horizon ID) of the layers of borehole drillings was used or not. The numerical models of groundwater flow models were construct, with setting the hydraulic conductivities according to the anisotropy of each layer and by using MODFLOW code, and MT3DMS code was used to simulate the transport of 1,1-Dichloroethylene and Trichloroethylene. The results show that a well unconformity cannot be extrapolated and interpolated even if there were 387 borehole drillings data (approximately 5 hectares 1 borehole). Using GMS software to automatically generate sedimentary sequence to construct a reasonable geological conceptual model required more borehole drillings data than using the correct sedimentary sequence. Therefore, if the sedimentary sequence of the borehole drillings data can be correctly judged, it will be possible to use fewer borehole drillings data to construct a reasonable geological conceptual model. In addition, through the constructed geological conceptual model, this study compares the layers of the screen section of the monitoring wells in the study area, and comprehensively judges the observation data and rainfall data to excluded the monitoring wells that are not screen in the same aquifer system. Groundwater flow models were calibrated by using the observation data from in 29 groundwater monitoring wells and the RMSE (Root Mean Square Error) in each model is within 1.4 meters, the groundwater flow direction is different. The layer of contaminant source was also different in different geological models. Therefore, the simulation results of contaminant transport have obvious differences. The study results illustrated that the hydraulic geological model has an important influence on the simulation of groundwater contaminant transport.
關鍵字(中)	★ 地質模型不確定性 ★ 地質學知識 ★ 鑽孔密度 ★ 地下水污染傳輸 ★ 數值模擬	關鍵字(英)	★ Geological model uncertainty ★ Geological knowledge ★ Borehole density ★ Groundwater contaminant transport ★ Numerical simulations
論文目次	摘要 I Abstract II 誌謝 III 目錄 V 圖目錄 VII 表目錄 IX 一、緒論 1 1.1 研究動機與目的 1 1.2 研究流程 3 二、文獻回顧 6 2.1 水文地質概念模型之定義 6 2.2 地下水模擬的不確定性來源 8 2.3 地質鑽井內外插建立地質概念模型可能造成的問題 12 三、研究場址概況與研究方法 14 3.1 研究區域概況 14 3.1.1 位置與範圍 14 3.1.2 地形、氣候與水文資訊 15 3.1.3 區域地質概況 17 3.1.4 研究區既有資料 18 3.1.5 研究區域地下水污染概況 26 3.2 建立地質概念模型 27 3.2.1 地質鑽孔產生與選取方式 27 3.2.2 GMS軟體建立地質概念模型的步驟 28 3.2.3 GMS軟體以鑽井內外插的數值方法 29 3.3 水力傳導係數設定 30 四、成果與討論 33 4.1 建立地質概念模型 33 4.1.1 以區域地質知識建立MB模型 34 4.1.2 建立M1、M2與M3模型 36 4.1.3 鑽孔密度與層序對地質概念模型的影響 40 4.2 建立地下水流模型 46 4.2.1 建立數值網格 46 4.2.2 篩選地下水監測井 47 4.2.3 邊界條件與初始水頭設定 49 4.2.4 水力傳導係數設定 50 4.3 地下水流模式率定 53 4.4 污染傳輸模擬與分析 57 4.4.1 污染傳輸模擬設定 57 4.4.2 Case 1:區域地質知識修正對污染傳輸模擬的影響 58 4.4.3 Case 2:不同鑽孔層序對污染傳輸模擬的影響 60 4.4.4 Case 3:不同鑽孔密度對污染傳輸模擬的影響 62 五、結論與建議 66 5.1 結論 66 5.2 建議 68 參考文獻 69 附錄一、地質鑽孔井錄 75 附錄二、土樣物性試驗資料 108
參考文獻	[1] Alyamani M. S. and Şen Z., “Determination of hydraulic conductivity from complete grain‐size distribution curves“, Groundwater, 31, 4, pp. 551-555, 1993. [2] Anderson M. P. and Woessner W. W., Applied Groundwater Modeling: Simulation of Flow and Advective Transport, Academic press, 1999. [3] Beven K. and Binley A., “The future of distributed models: model calibration and uncertainty prediction“, Hydrological processes, 6, 3, pp. 279-298, 1992. [4] Beyer W., “On the determination of hydraulic conductivity of gravels and sands from grain-size distributions“, Wasserwirtschaft-wassertechnik, 14, 6, pp. 165-169, 1964. [5] Bredehoeft J., “The conceptualization model problem—surprise“, Hydrogeology journal, 13, 1, pp. 37-46, 2005. [6] Butts M. B., Payne J. T., Kristensen M. and Madsen H., “An evaluation of the impact of model structure on hydrological modelling uncertainty for streamflow simulation“, Journal of Hydrology, 298, 1-4, pp. 242-266, 2004. [7] Carman P. C., “Determination of the specific surface of powders I. Transactions“, J. Soc. Chemical Industries., 57, pp. 225-234, 1938. [8] Carman P. C., “Flow of gases through porous media“, pp. 1956. [9] Carrera J., Alcolea A., Medina A., Hidalgo J. and Slooten L. J., “Inverse problem in hydrogeology“, Hydrogeology journal, 13, 1, pp. 206-222, 2005. [10] Carrier III W. D., “Goodbye, hazen; hello, kozeny-carman“, Journal of geotechnical and geoenvironmental engineering, 129, 11, pp. 1054-1056, 2003. [11] Chen C.-S., Tu C.-H., Chen S.-J. and Chen C.-C., “Simulation of groundwater contaminant transport at a decommissioned landfill site—A case study, Tainan City, Taiwan“, International journal of environmental research and public health, 13, 5, pp. 467, 2016. [12] Christensen S. and Cooley R. L., “Evaluation of prediction intervals for expressing uncertainties in groundwater flow model predictions“, Water Resources Research, 35, 9, pp. 2627-2639, 1999. [13] Clark M. P., Kavetski D. and Fenicia F., “Pursuing the method of multiple working hypotheses for hydrological modeling“, Water Resources Research, 47, 9, pp. 2011. [14] Cronican A. E. and Gribb M. M., “Hydraulic conductivity prediction for sandy soils“, Groundwater, 42, 3, pp. 459-464, 2004. [15] Doherty J. and Welter D., “A short exploration of structural noise“, Water Resources Research, 46, 5, pp. 2010. [16] Domeneghetti A., Castellarin A. and Brath A., “Assessing rating-curve uncertainty and its effects on hydraulic model calibration“, Hydrol. Earth Syst. Sci., 16, 4, pp. 1191-1202, 2012. [17] Dubus I. G., Brown C. D. and Beulke S., “Sources of uncertainty in pesticide fate modelling“, Science of the total environment, 317, 1-3, pp. 53-72, 2003. [18] Enemark T., Peeters L. J., Mallants D. and Batelaan O., “Hydrogeological conceptual model building and testing: A review“, Journal of Hydrology, 569, pp. 310-329, 2019. [19] Feyen L., Ribeiro Jr P., De Smedt F. and Diggle P., “Stochastic delineation of capture zones: classical versus Bayesian approach“, Journal of hydrology, 281, 4, pp. 313-324, 2003. [20] Gallagher M. and Doherty J., “Parameter estimation and uncertainty analysis for a watershed model“, Environmental Modelling & Software, 22, 7, pp. 1000-1020, 2007. [21] Glasgow H. S., Fortney M. D., Lee J., Graettinger A. J. and Reeves H. W., “MODFLOW 2000 head uncertainty, a first-order second moment method“, Ground water, 41, 3, pp. 342, 2003. [22] Gupta H. V., Clark M. P., Vrugt J. A., Abramowitz G. and Ye M., “Towards a comprehensive assessment of model structural adequacy“, Water Resources Research, 48, 8, pp. 2012. [23] Højberg A. and Refsgaard J., “Model uncertainty–parameter uncertainty versus conceptual models“, Water Science and Technology, 52, 6, pp. 177-186, 2005. [24] Hazen A., “Some physical properties of sand and gravel with special reference to their use in filtration“, 24th Ann, Rep., Mass. State Board of Health, Boston, 1983, pp. 1892. [25] James A. L. and Oldenburg C. M., “Linear and Monte Carlo uncertainty analysis for subsurface contaminant transport simulation“, Water Resources Research, 33, 11, pp. 2495-2508, 1997. [26] Kiang J. E., Gazoorian C., McMillan H., Coxon G., Le Coz J., Westerberg I. K., Belleville A., Sevrez D., Sikorska A. E., Petersen-Øverleir A., Reitan T., Freer J., Renard B., Mansanarez V. and Mason R., “A Comparison of Methods for Streamflow Uncertainty Estimation“, Water Resources Research, 54, 10, pp. 7149-7176, 2018. [27] Kozeny J., “Über kapillare Leitung des Wassers im Boden‐Aufstieg“, Versickerung und Anwendung auf die Bewässerung, pp. 1927. [28] Lemon A. M. and Jones N. L., “Building solid models from boreholes and user-defined cross-sections“, Computers & Geosciences, 29, 5, pp. 547-555, 2003. [29] Mallet C. and Pacquant J., “Les barrages en terre“, pp. 1951. [30] Mann C. J., Uncertainty in geology, 1993. [31] McMillan H., Krueger T. and Freer J., “Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality“, Hydrological Processes, 26, 26, pp. 4078-4111, 2012. [32] McMillan H. K., Westerberg I. K. and Krueger T., “Hydrological data uncertainty and its implications“, Wiley Interdisciplinary Reviews: Water, 5, 6, pp. e1319, 2018. [33] Meyer P. D., Gee G. W. and Nicholson T. J., Information on hydrologic conceptual models, parameters, uncertainty analysis, and data sources for dose assessments at decommissioning sites, Pacific Northwest National Lab.(PNNL), Richland, WA (United States), 1999. [34] Moges E., Demissie Y., Larsen L. and Yassin F., “Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis“, Water, 13, 1, pp. 2020. [35] Newman S. and Wierenga P. J., “Comprehensive Strategy of Hydrogeologic Modeling and Uncertainty Analysis for Nuclear Facilities and Sites“, pp. 2003. [36] Ni C.-F., Yeh T.-C. J. and Chen J.-S., “Cost-effective hydraulic tomography surveys for predicting flow and transport in heterogeneous aquifers“, Environmental science & technology, 43, 10, pp. 3720-3727, 2009. [37] NJDEP, N. J. D. o. E. Protection, USING THE COMBINED SESOIL/AT123D MODELS TO DEVELOP SITE-SPECIFIC IMPACT TO GROUND WATER SOIL REMEDIATION STANDARDS FOR MOBILE CONTAMINANTS, Version 2.1, Trenton, New Jersey, 2014. [38] Rawls W. and Brakensiek D., Estimation of soil water retention and hydraulic properties, Springer, 1989. [39] Refsgaard J. C., van der Sluijs J. P., Brown J. and van der Keur P., “A framework for dealing with uncertainty due to model structure error“, Advances in Water Resources, 29, 11, pp. 1586-1597, 2006. [40] Refsgaard J. C., Christensen S., Sonnenborg T. O., Seifert D., Højberg A. L. and Troldborg L., “Review of strategies for handling geological uncertainty in groundwater flow and transport modeling“, Advances in Water Resources, 36, pp. 36-50, 2012. [41] Rojas R., Feyen L. and Dassargues A., “Conceptual model uncertainty in groundwater modeling: Combining generalized likelihood uncertainty estimation and Bayesian model averaging“, Water Resources Research, 44, 12, pp. 2008. [42] Seifert D., Sonnenborg T. O., Scharling P. and Hinsby K., “Use of alternative conceptual models to assess the impact of a buried valley on groundwater vulnerability“, Hydrogeology Journal, 16, 4, pp. 659-674, 2007. [43] Sikorska A. E., Scheidegger A., Banasik K. and Rieckermann J., “Considering rating curve uncertainty in water level predictions“, Hydrol. Earth Syst. Sci., 17, 11, pp. 4415-4427, 2013. [44] Slichter C. S., “Theoretical investigation of the motion of ground waters“, The 19th Ann. Rep. US Geophys Survey., pp. 304-319, 1899. [45] Troin M., Arsenault R., Martel J.-L. and Brissette F. o., “Uncertainty of Hydrological Model Components in Climate Change Studies over Two Nordic Quebec Catchments“, Journal of Hydrometeorology, 19, 1, pp. 27-46, 2018. [46] Troldborg L., Refsgaard J. C., Jensen K. H. and Engesgaard P., “The importance of alternative conceptual models for simulation of concentrations in a multi-aquifer system“, Hydrogeology Journal, 15, 5, pp. 843-860, 2007. [47] Walker W. E., Harremoës P., Rotmans J., van der Sluijs J. P., van Asselt M. B. A., Janssen P. and Krayer von Krauss M. P., “Defining Uncertainty: A Conceptual Basis for Uncertainty Management in Model-Based Decision Support“, Integrated Assessment, 4, 1, pp. 5-17, 2003. [48] Warmink J. J., Janssen J. A. E. B., Booij M. J. and Krol M. S., “Identification and classification of uncertainties in the application of environmental models“, Environmental Modelling & Software, 25, 12, pp. 1518-1527, 2010. [49] Willis D. W. and John L. S., Manual of Applied Field Hydrogeology, McGraw-Hill Education, New York, 2001. [50] Zhang R., “Applied Contaminant Transport Modeling: Theory and Practice“, Journal of Environmental Quality, 25, 4, pp. 927-927, 1995. [51] 中興工程顧問股份有限公司, 全國高污染潛勢工業區地下水質預警監測井網規劃建置計畫(第二期), 行政院環境保護署, 2014. [52] 方麒淯，潮汐對地下水中污染物傳輸之影響，國立交通大學，碩士論文，2014。 [53] 王彪, 劉義, 邵景力, 王思源 and 張黎明, “基於GMS的秦王川盆地三維地質模型構建“, 工程地質學報, 27, s1, pp. 361-366, 2019. [54] 李權顯，半島工業區地下水流模擬與污染監測系統效益評估，國立成功大學，碩士論文，2015。 [55] 林禹豪，含氯有機溶劑GCW整治案例分析，國立交通大學，碩士論文，2015。 [56] 倪春發, 李奕賢, 李唯祺, 林淇平, 吳宛庭, Dung T. Q., 馮嵩棣 and 陳昶宏, “國內外土壤地下水常用數學模式分類彙整與基準案例評析“, 土壤及地下水污染整治, 3, 4, pp. 261-275, 2016. [57] 國立中央大學, 污染場址地下環境分析模式發展計畫, 行政院環境保護署, 2020. [58] 陳鹏, 鄧飛 and 劉思廷, “三維空間屬性插值方法的研究“, 電腦知識與技術, 11, 7, pp. 235-239, 2015. [59] 馮波, 陳明濤, 岳冬冬, 李勝濤, 賈小豐 and 宋丹, “基於兩種插值算法的三維地質建模對比“, 吉林大學學報(地球科學版), 49, 4, pp. 1200-1208, 2019. [60] 業興環境科技股份有限公司, 嘉義縣民雄頭橋工業區污染補充調查與行政措施研擬計畫, 嘉義縣環境保護局, 2017. [61] 業興環境科技股份有限公司, 污染場址地下環境分析模式整合發展與審查制度建置計畫, 行政院環境保護署, 2018. [62] 劉韋恩，導水度異質性對於含氯有機溶劑污染場址健康風險評估之影響，國立交通大學，碩士論文，2010。 [63] 謝澤銘，運用地質知識建立三維合成地質模型和評估地質模型不確定性，國立中央大學，碩士論文(未出版)，2021。
指導教授	董家鈞王士榮(Jia-Jyun Dong Shih-Jung Wang)	審核日期	2021-3-26
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