臺灣博碩士論文加值系統

近年來針對保護河川生態的河川環境流量研究，已從以往考慮保留單一最小流量的方式，發展成為以維護「生態河川流態」為基礎的河川流量管理方式；但發展生態河川流態的難題在於如何能真正考量河川流態與河川生態系統間的關係與影響，而非僅是採用歷史流量改變度評估的替代方案。本研究提出一考量生態河川流態與魚類群聚關係的架構，以數量生態學上的梯度分析方法建立魚類豐度與台灣生態水文指標(TEIS)間的生態反應模型，引進代表合成環境梯度的虛擬變數以定義各魚種在生態水文環境梯度軸上的生態區位；這方法的優點在於(1)以河川魚類群聚為考量對象而非少數選定魚種，(2)為一基於高斯反應模型的生態模型，(3)能有效的分離眾多環境因子對生物影響的複雜合成效應。在本研究中並延伸此概念於建立基於河川流態的河川流量管理方式，以石門水庫為例建立考量人類需求與生態需求的多目標最佳化操作模式，並利用非支配排序遺傳演算II (NSGA-II)搜尋最佳蓄水歷線。研究結果顯示結合梯度分析方法與NSGA-II能幫助建立更具生態意義的河川流量管理方式，找出同時滿足人類用水需求與維持生態系統健全之水庫操作規則，以供多目標水資源管理進行決策。

Investigation on environmental flow for conservation of river ecosystem has been focused on ecological flow regime approach which is more comprehensive than the traditional minimum flow management schemes that merely consider single flow value. The pivotal difficulty in developing ecological flow regime is how to take into account the interaction and relation between flow regime and river ecosystem. In this study we propose an idea of considering the relation between ecological flow regime and fish communities and then applying the gradient analysis technique in quantitative ecology theory to constructing the ecological response model. The model is built based on the fish abundance and the Taiwan Ecohydrology Indicator System (TEIS). The dummy variables for representing synthetic environment gradient could be used to identify the niche in each fish species on ecohydrological gradient axis. The main advantages of this technique are: (1)approximate the natural flow regimes that maintained the entire panoply of species, (2)based on unimodal Gaussian response model, and (3)separate the effects of explanatory environment variables.
This technique is then extended herein to build the optimal operation model in Shihmen Reservoir by considering the maintenance of natural flow regimes and human needs, and the non-dominated sorting genetic algorithm II (NSGA-II) is used to optimize the multi-objective model. The results demonstrated that more meaningful manner of flow management in ecological aspect can be effectively constructed by integrating the gradient analysis technique and NSGA-II for the ecological flow regimes. Meanwhile, the method searches the optimal operation rule that can simultaneously the water demand for maintenance of ecosystem and human need provides the decision for multi-objective water resources management.

摘 要 i
Abstract ii
目 錄 iv
表目錄 ix
圖目錄 xi
第一章 緒 論 1
1.1 研究動機與目的 1
1.2 研究方法與流程 2
1.3 論文架構 4
第二章 文獻回顧 6
2.1 生態河川流態 6
2.2 梯度分析方法 8
2.3 模糊規劃理論 10
2.4 優選模式於水庫運轉操作 11
2.5 多目標進化式演算法 13
第三章 理論概述 15
3.1 台灣生態水文指標系統 15
3.1.1 自然河川流態與生態河川流態 15
3.1.2 水文變化指標 17
3.1.3 台灣生態水文指標系統之考量因子 18
3.1.4 台灣生態水文指標系統之介紹 21
3.2 梯度分析方法 23
3.2.1 環境梯度與生態區位 23
3.2.2 梯度分析方法之目的 27
3.2.3 梯度分析方法的分類與流程 30
3.2.4 梯度分析方法之雙序圖意義 33
3.2.5 除趨勢對應分析(DCA) 36
3.2.6 浄蒙地卡羅排列測試 37
3.2.7 典型對應分析(CCA) 38
3.3 模糊規劃 40
3.3.1 模糊集合理論 40
3.3.2 模糊規劃模式 41
3.4 遺傳演算法 45
3.4.1 遺傳演算法簡述 45
3.4.2 演算流程與基本單元 47
3.4.3 遺傳演算法三大運算元 49
3.5 非支配排序遺傳演算法II (NSGA-II) 52
3.5.1 多目標最佳化模式 52
3.5.2 NSGA-II概述及演算流程 57
3.5.3 非支配排序及擁擠距離 59
3.5.4 NSGA-II運算元 61
第四章 研究案例 63
4.1 研究區域概況 63
4.1.1 大漢溪流域簡介 63
4.1.2 大漢溪流域魚類簡介 64
4.1.3 石門水庫簡介 67
4.2 梯度分析方法結果 69
4.2.1 資料選取原則及限制 69
4.2.2 降趨對應分析DCA結果 73
4.2.3 DCA梯度值與水文因子逐步迴歸結果 82
4.2.4 浄蒙地卡羅排列測試結果 88
4.2.5 典型對應分析CCA結果 92
4.3 石門水庫操作 101
4.3.1 石門水庫引水系統概述 101
4.3.2 石門水庫操作規線 101
4.4 多目標最佳化模式之建立 103
4.4.1 人類需求目標及限制式 103
4.4.2 人類需求目標函數及限制式的模糊化 106
4.4.3 生態系統需求目標 108
4.4.4 多目標水庫最佳化模式 109
4.4.5 聯程原理與缺水指標 112
第五章 結果與討論 115
5.1 石門水庫單目標最佳操作 115
5.2 石門水庫多目標最佳化結果 120
5.3 結果與討論 125
第六章 結論與建議 132
6.1 結論 132
6.2 建議 134
參考文獻 135
附錄一 台灣生態水文指標系統說明 148
附錄二 大漢溪常見淡水魚類照片與棲所生態描述 151
附錄三 民國77年石門水庫操作規線最佳化結果 155

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