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研究生:林亮君
研究生(外文):Liang-Chun Lin
論文名稱:不確定環境下的河川總量管制策略
論文名稱(外文):Wasteload Allocation Strategeries with Uncertainty in a River Basin
指導教授:陳鶴文陳鶴文引用關係
指導教授(外文):Ho-Wen Chen
學位類別:碩士
校院名稱:朝陽科技大學
系所名稱:環境工程與管理系碩士班
學門:工程學門
學類:環境工程學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:中文
論文頁數:89
中文關鍵詞:序率規劃模式蒙地卡羅模擬遺傳演算法河川水質管理
外文關鍵詞:Water Quality ManagementGenetic AlgorithmMonte Carlo SimulationStochastic Programming
相關次數:
  • 被引用被引用:17
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近年來河川水質改善工作的重點在於總量管制的規劃與執行。為了在不確定環境下估算並分配河川的涵容能力(Total Maximum Daily Loading, TMDL),本研究利用移動平均數、移動標準偏差和相關分析來估算高屏溪流域水文環境的時間性與空間性;利用蒙地卡羅模擬法來模擬流量的隨機性。同時考慮污染防制成本最小化以及水體水質達成度最大化的規劃目標下,建立多目標序率規劃模式(Multiobjectives Stochastic Programming),進行不同設計流量(Q75, Q90 and Qrd)及總量管制四種策略:(1)最大污染負荷法(2)全區等去除率(3)分區等去除率和(4)分類分區等去除率的污染負荷分配方案的擬定。為了求解規劃模式,遺傳演算法(Genetic Algorithm)與蒙地卡羅模擬法(Monte Carlo Simulation)工具被成功整合。
分析結果發現,新發大橋、杉林大橋及六龜橋等水文站觀測流量有隨時間逐漸減少的趨勢;里嶺大橋及三地門大橋歷年水文站的變異量則有逐年增加的趨勢。多目標優化分析結果顯示目前高屏溪流域可允許最大日污染負荷量較目前高屏溪點源污染排入的污染量低出許多,因此河川發揮其自淨作用的效果不大。進行分集水區、全流域等去除率及全流域不同去除率進行污染物削減後,發現全流域不同去除率可花費最小處理成本,而分集水區等去除率方案又比全流域等去除率較符合經濟效益。
Recently major policy planning for improving water quality is to control total maximum daily load. In order to estimate permissible maximum daily waste in a river under uncertainty, we use moving average, moving stand deviation and correlation analysis to evaluate flow difference between different time intervals and between locations in Kao-Ping River. Then, Monte Carlo Simulation is used to simulate stochastic properties of flows. In order to establish Multiobjectives Stochastic Programming and then to proceed three Design daily flow (Q75, Q90 and Qrd ) and four waste load allocation policies of Total Mass Control: (1) the maximum discharge policy, (2) the uniform treatment for the whole water basin, (3) the uniform treatment for each watershed and (4) the different treatment for each element to demonstrate, we then use those simulated flows to achieve minimum cost and opitimal water-quality improvement comply with regulations simultaneously.
In order to solve the optimal solutions of the model, we combine against Genetic Algorithm and Mote Carlo Simulation.
The results of the study show that flow at Shin-Fa Bridge, San-Lin Bridge and Liu-Kwei stations tend to diminish and variance of Li-Lin Bridge and San-Ti-Men stations tend to increase. Based on assimilative capacity of Gao-Ping River, this research finds out that our resulted TMDL is less than the current load. Results show that (4) will cost least, (3) is economically viable than (2).
摘 要 I
Abstract II
誌 謝 III
目 錄 IV
表目錄 VI
圖目錄 VII
第一章 緒論 1
1-1 研究動機與緣起 1
1-2 研究方法與架構 2
1-3 研究目標 4
第二章 文獻回顧 5
2-1 總量管制 5
2-2 河川水質模擬 6
2-3 不確定性分析 9
2-4 遺傳演算法 13
第三章 研究方法 15
3-1 案例環境介紹 15
3-2 資料蒐集 16
3-3 河川流量變遷分析 22
3-4 推估水體涵容能力 30
3-5 污染削減方案規劃 36
第四章 結果與討論 43
4-1 河川流量變遷分析 43
4-2 水質模式率定 50
4-3 多目標序率規劃模式之建立 52
第五章 結論與建議 69
5-1 結論 69
5-2 建議 70
參考文獻 72
附表目錄 78
簡 歷 89
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