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姓名	鍾佳良(Jia-Liang Jhong)  查詢紙本館藏	畢業系所	應用地質研究所
論文名稱	利用模擬退火演算法推估地下污染物來源 (Identification of the groundwater contaminant source using simulated annealing algorithm)
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摘要(中)	地下水被視為穩定且可靠的用水來源，卻也因其不可見及水循環更新速度慢這兩特性，一旦受到污染，管理單位難以在第一時間發現，也導致污染源會隨時間推移而擴大其分布範圍，直接或間接增加民眾用水品質風險。在面對受污染的水體，需要瞭解污染傳輸歷程。要解污染物之傳輸歷程，須瞭解該地區的水文地質條件及地下水污染傳輸等機制，方得以數值模式進行相關推估，基於各項參數取得條件之不易、監測井數量有限，推估的工作變得相當困難。為解決現地觀測資料的不足所帶來之影響，本研究開發出以python介接數值模式與啟發式演算法(heuristic algorithm)推估污染傳輸之方法，其中水文及污染傳輸數值模式分別使用MODFLOW-2005與MT3D-MS，用於生成測試案例與當作最佳化問題的數值模式。啟發式演算法則採用退火演算法(simulated annealing algorithm, SA)，用於求解最佳化問題之演算法。為減少推估誤差與提升系統之穩健性，本研究將數值模式中所使用的參數設定成一特定範圍並離散化，降低因固定參數所產生之誤差；對於退火演算法及動力系統所帶來的不確定性，利用系集(ensemble)與空間分析之概念，降低單一次模擬所帶來的誤差，提高推估系統穩健性。為驗證推估方法，研究中使用均質地質條件與單一且持續性的污染點源釋放，合成兩假想之污染傳輸案例作為推估方法的驗證，經測試案例驗證後，推估方法除能夠有效推估污染源之點位、傳輸方向，本研究於方法建立後，探討並量化不同數量的觀測點對於此方法的適用性與不確定性，結果顯示在監測井數量為6以上時，點源推估之誤差皆小於1公尺，傳輸方向誤差為5度以內。
摘要(英)	Groundwater is one of the stable and reliable water resources. Due to the natural complexity of the aquifer systems, early detection of the contaminant is challenging. The spread of the contaminant in a groundwater system might directly or indirectly influence residents near the contamination sources. Typical approaches to predicting the migration of the plumes are the numerical models, which allow the reproductions of the transport processes and quantify the concentration distribution. Due to the limited parameters for flow and transport models, the implementations of most numerical models become complicated. We introduced a heuristic algorithm to estimate flow and transport parameters for a contaminant site in the study. The model tests consider two numerical examples, where the flow directions and numbers of observations are different in the designed scenarios. Specifically, the MODFLOW-2005 and MT3D-MS models were used for generating the observations at the synthetic sites. The MODFLOW-2005 and MT3D-MS models associated with the simulated annealing (SA) algorithm were developed and systematically tested to quantify the accuracy of the estimated flow and transport parameters. In the study, the numerical model parameters were fixed to a specific range and discretized to reduce the estimation errors and improve the system′s robustness. Additionally, the ensemble approach and spatial analysis were used to reduce the errors caused by a single simulation. Results showed that the developed model could effectively identify the locations and directions of the contaminant source. The model enables evaluating suitable observation wells for the sites and quantifies associated uncertainty induced by the limited observations. The numerical examples showed that the number of monitoring wells needs to be higher than 6. The source point estimation error can be less than 1 m, and the error of the transport direction can be within 5 degrees.
關鍵字(中)	★ 模擬退火演算法 ★ 地下水污染溯源 ★ 系集	關鍵字(英)	★ simulated annealing algorithm ★ groundwater contaminant source identification ★ ensemble
論文目次	摘要 i Abstract ii 圖目錄 v 表目錄 viii 第一章 緒論 1 1-1 前言 1 1-2 研究動機與目的 2 1-3 研究流程 3 1-4 論文架構 4 第二章 文獻回顧 5 2-1 污染源識別相關研究 5 2-2 啟發式演算法 6 第三章 研究方法 10 3-1 地下水模擬模式 11 3-1-1 地下水流模式MODFLOW 11 3-1-2 溶質傳輸模式MT3D-MS 12 3-2 模擬退火演算法 13 3-2-1 方法概述 14 3-2-2 演算法流程 18 3-2-3 目標函數 20 3-2-4 退火演算法參數設定 23 3-3 空間聚集分析 25 第四章 測試案例 28 4-1 模式參數說明 30 4-2 可行解空間 35 4-3 退火策略參數 35 第五章 結果與討論 36 5-1 測試案例一：污染點源與傳輸方向推估之結果 36 5-2 測試案例二：污染點源與傳輸方向推估之結果 43 5-3 監測井數與推估點源方法之適用性及討論 50 5-3-1 推估點源座落位置之準確度與精準度 60 5-3-2 推估點源座落位置之成功率與誤差量 62 5-3-3 推估傳輸方向之誤差量 64 第六章 結論與建議 66 6-1 結論 66 6-2 建議 67 參考文獻 68
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指導教授	倪春發(Chuen-Fa Ni)	審核日期	2021-1-28
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