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System No. U0002-1602202410115900
DOI 10.6846/tku202400089
Title (in Chinese) 應用乾旱指標與非優勢排序多目標遺傳演算法於水庫運營與停灌決策之研究
Title (in English) Optimizing Reservoir Operations and Irrigation Suspension Strategies using Drought Indices and Non-dominated Sorting in Genetic Algorithms
Other Title
Institution 淡江大學
Department (in Chinese) 水資源及環境工程學系碩士班
Department (in English) Department of Water Resources and Environmental Engineering
Other Division
Other Division Name
Other Department/Institution
Academic Year 112
Semester 1
PublicationYear 113
Author's name (in Chinese) 楊凱崴
Author's name(in English) Kai-Wei Yang
Student ID 611480095
Degree 碩士
Language Traditional Chinese
Other Language
Date of Oral Defense 2024-01-15
Pagination 126page
Committee Member advisor - Li-Chiu Chang(changlc@mail.tku.edu.tw)
co-chair - Fi-John Chang(changfj@ntu.edu.tw)
co-chair - Wen-Cheng Huang(b0137@mail.ntou.edu.tw)
Keyword (inChinese) 乾旱緩解
Keyword (in English) Drought Mitigation
Non-dominated Sorting Genetic Algorithm II (NSGA-II)
Reservoir Operation
Drought Indices
Other Keywords
Abstract (in Chinese)
Abstract (in English)
Global development has intensified climate change, resulting in severe global warming and an increasing frequency of extreme hydrological events, including droughts and floods. Countries worldwide are facing the urgent need to develop comprehensive strategies to cope with growing demands for water resources from society and industries. Despite an annual average rainfall of approximately 2500 mm, Taiwan is classified by the United Nations as the 18th country facing a water scarcity crisis due to its steep mountainous terrain and short, swift rivers that hinder efficient water retention. Additionally, uneven spatial and temporal rainfall distribution, coupled with an extended dry season, necessitates reliance on water stored during the wet season.
Water reservoirs play a critical role in Taiwan's water resource management, significantly influencing future water supply capabilities. Proactive decision-making to conserve and effectively allocate water resources during droughts and extreme drought events is vital to mitigate disaster losses. This study proposes the use of a Standardized Reservoir Storage Index (SRSI) at different time scales as an early irrigation suspension warning and decision-making indicator. Utilizing historical data based on various percentiles of inflow and actual historical inflow, the study applies the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to simulate optimal release strategies for reservoirs under actual water conditions and extreme drought scenarios.
By exploring the application of drought indices and the Non-dominated Sorting Genetic Algorithm in water resource management, the study aims to provide valuable insights into enhancing water resource allocation, drought mitigation, and reservoir operations. The results offer practical recommendations for reservoir discharge operations, irrigation suspension practices, and water restriction policies, contributing to the reduction of future drought impacts and associated losses. This approach can serve as a valuable tool for predicting and managing future drought events, promoting sustainable water resource utilization on a broader scale. The research results indicate that the numerical characteristics of SRSI at various time scales can effectively inform decisions regarding agricultural irrigation cessation in different regions. Furthermore, it is confirmed that the strategy of implementing advanced agricultural irrigation cessation, coupled with NSGA-II, can effectively consider the prioritization of public water use, optimal discharge configuration for agricultural outflows, and avoidance of water resource wastage during the first crop season. This approach facilitates the efficient utilization and storage of water resources.
Other Abstract
Table of Content (with Page Number)
謝誌	II
目錄	VI
圖目錄	VIII
表目錄	IX
第一章 前言	1
1.1	研究緣起	1
1.2	研究目的	2
1.3	論文架構	2
第二章 文獻回顧	3
2.1	乾旱指標發展與相關研究	3
2.2	遺傳演算法發展與修正演算法之研究	4
2.3	遺傳演算法應用於水資源與水庫方面之研究	5
第三章 理論概述	9
3.1	乾旱指標	9
3.2	遺傳演算法	14
3.3	非優勢排序多目標遺傳演算法	27
第四章 研究案例	32
4.1	研究區域	32
4.2	乾旱指標分析與選擇	50
4.3	水庫水資源調配決策模式	52
4.4	遺傳演算法參數設定	56
第五章 結果與討論	61
5.1	柏拉圖鋒線	63
5.2	實際水情情境結果比較	68
5.3	極端水情情境放流分析	91
第六章 結論與建議	104
6.1	結論	104
6.2	建議	105
參考文獻	106
附錄A 實際水情情境各操作統計表	111
附錄B 極端水情情境各操作統計表	119

圖3-1 累積機率轉換圖	11
圖3-2 SPI常態機率分布圖	12
圖3-3 遺傳演算法流程架構圖	15
圖3-4 輪盤式選取法示意圖	19
圖3-5單點交配示意圖	22
圖3-6多點交配示意圖	23
圖3-7單點突變示意圖	25
圖3-8 柏拉圖鋒線示意圖	27
圖3-9 非優勢排序多目標遺傳演算法(NSGA-II)架構圖	28
圖3-10 快速非優勢排序與擁擠距離比較示意圖	29
圖3-11 擁擠距離比較示意圖	31
圖4-1 石門水庫流域圖	33
圖4-2 石門水庫之供水系統圖	34
圖4-3石門水庫運用規線	35
圖4-4歷年2月初有效蓄水量與一期作總放流量比較圖	47
圖4-5水文年88年後2月初水庫有效蓄水量與一期作總放流量比較圖	49
圖4-7 2月初有效蓄水量與SSI之關係圖	51
圖4-8 2月初有效蓄水量與SRSI之關係圖	51
圖5-1 研究流程架構圖	62
圖5-2 水文年103年28旬至104年3旬實際流量之柏拉圖解	64
圖5-3 水文年109年28旬至110年3旬實際流量之柏拉圖解	66
表3-1 SSI乾旱程度對照表	10
表3-2 二進位編碼範例	16
表3-3 實數編碼範例	16
表4-1石門水庫運用規線表	35
表4-2 104年石門水庫登記水權水量	38
表4-3水文年88年後之停灌區域統計表	40
表4-4石門水庫歷年濕季之水文年統計與分類表	41
表4-5石門水庫歷年乾季之水文年統計與分類表	44
表4-6 石門水庫歷次水權登記水量表	48
表4-7乾旱指標不同時間尺度與2月初有效蓄水量之相關性	51
表4-8 NSGA-II參數設定表	56
表4-9 SRSI之停灌決策各時間尺度數值範圍設定	58
表5-1 水文年88年後之乾旱停灌事件資料	63
表5-2 102年第28旬至隔年第3旬實際與模式數值	70
表5-3 102年第28旬至隔年第3旬各操作目標函數	71
表5-4 石門水庫各區域停灌決策之缺水指數數值定義	71
表5-5 石門水庫各區域公共用水之通用缺水指數數值定義	71
表5-6 90年第28旬至隔年第3旬實際與模式數值(模式未停灌)	73
表5-7 90年第28旬至隔年第3旬各操作目標函數(模式未停灌)	74
表5-8 90年第28旬至隔年第3旬實際與模式數值(石門停灌)	76
表5-9 90年第28旬至隔年第3旬各操作目標函數(石門停灌)	77
表5-10 91年第28旬至隔年第3旬實際與模式數值(模式未停灌)	79
表5-11 91年第28旬至隔年第3旬各操作目標函數(模式未停灌)	80
表5-12 91年第28旬至隔年第3旬實際與模式數值(桃園停灌)	82
表5-13 91年第28旬至隔年第3旬各操作目標函數(桃園停灌)	83
表5-14 109年第28旬至隔年第3旬實際與模式數值(模式未停灌)	85
表5-15 109年第28旬至隔年第3旬各操作目標函數(模式未停灌)	86
表5-16 109年第28旬至隔年第3旬實際與模式數值(全區域停灌)	88
表5-17 109年第28旬至隔年第3旬各操作目標函數(全區域停灌)	89
表5-18 90年第28旬至隔年第3旬實際與超越機率百分比入流量	91
表5-19 90年第28旬至隔年第3旬Q90各操作目標函數	92
表5-20 90年第28旬至隔年第3旬Q80各操作目標函數	93
表5-21 90年第28旬至隔年第3旬Q70各操作目標函數	94
表5-22 91年第28旬至隔年第3旬實際與超越機率百分比入流量	95
表5-23 91年第28旬至隔年第3旬Q90各操作目標函數	96
表5-24 91年第28旬至隔年第3旬Q80各操作目標函數	97
表5-25 91年第28旬至隔年第3旬Q70各操作目標函數	98
表5-26 91年第28旬至隔年第3旬Q60各操作目標函數	99
表5-27 109年第28旬至隔年第3旬實際與超越機率百分比入流量	100
表5-28 109年第28旬至隔年第3旬Q90各操作目標函數	101
表5-29 109年第28旬至隔年第3旬Q80各操作目標函數	102
表5-30 109年第28旬至隔年第3旬Q70各操作目標函數	103
附表A-1 92年第28旬至隔年第3旬實際與模式數值(模式未停灌)	111
附表A-2 92年第28旬至隔年第3旬各操作目標函數(模式未停灌)	112
附表A-3 92年第28旬至隔年第3旬實際與模式數值(模式停灌)	113
附表A-4 92年第28旬至隔年第3旬各操作目標函數(模式停灌)	114
附表A-5 103年第28旬至隔年第3旬實際與模式數值(模式未停灌)	114
附表A-6 103年第28旬至隔年第3旬各操作目標函數(模式未停灌)	116
附表A-7 103年第28旬至隔年第3旬實際與模式數值(模式停灌)	116
附表A-8 103年第28旬至隔年第3旬各操作目標函數(模式停灌)	118
附表B-1 92年第28旬至隔年第3旬實際與超越機率百分比入流量	119
附表B-2 92年第28旬至隔年第3旬Q90各操作目標函數	120
附表B-3 92年第28旬至隔年第3旬Q80各操作目標函數	120
附表B-4 92年第28旬至隔年第3旬Q70各操作目標函數	121
附表B-5 92年第28旬至隔年第3旬Q60各操作目標函數	121
附表B-6 92年第28旬至隔年第3旬Q50各操作目標函數	122
附表B-7 92年第28旬至隔年第3旬Q40各操作目標函數	122
附表B-8 103年第28旬至隔年第3旬實際與超越機率百分比入流量	123
附表B-9 103年第28旬至隔年第3旬Q90各操作目標函數	124
附表B-10 103年第28旬至隔年第3旬Q80各操作目標函數	124
附表B-11 103年第28旬至隔年第3旬Q70各操作目標函數	125
附表B-12 103年第28旬至隔年第3旬Q60各操作目標函數	125
附表B-13 103年第28旬至隔年第3旬Q50各操作目標函數	126
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