台灣地區因降雨在時間與空間上分佈不均勻，穩定的供水極需仰賴水庫來調節河川豐枯不均的流量，但在嚴重的乾旱時期，水庫供水無法滿足既定用水需求的機率將會大幅增加，容易造成缺水情況發生。台灣地區多數水庫均以規線評估各時期水庫蓄水狀態以決定供水量，在水庫蓄水量低於規線下限時代表水庫供水能力不足以供應未來的供水需求，通常會以折扣供水的方式來減輕未來供水的壓力。在乾旱發生之前水庫蓄水量低於下限時，先以小比例限水來避免未來嚴重乾旱時期可能發生的嚴重缺水，是水庫管理單位經常採用的乾旱管理措施之一。但限水的時機與限水比例是水庫營運決策問題，而水庫下限的形狀會影響此二因子，因此本文建立優選模式以尋求水庫之最佳營運策略，所考慮的兩種模式包括模式一僅考慮供水係數的變動，模式二則考慮供水係數與規線的變動，並以多準則決策的方式將7種缺水指標(缺水事件最長延時、缺水事件最大缺水量、缺水事件平均缺水延時及缺水量、風險度、總缺水率、缺水事件頻率)整合成單一缺水目標函數，以遺傳演算法尋求最佳營運策略。經本文應用於位在台灣南部區域之南化水庫，顯示兩種優選模式結果皆優於現況，其中又以模式二之最佳下限與供水係數對改善缺水最有幫助，在7個缺水指標中有6項優於現況，有5項缺水指標優於模式一，僅缺水事件平均連續缺水量由現況之5.836 MCM略增至模式一8.024 MCM及模式二7.151 MCM。

Uneven spatial and temporal rainfall distribution in Taiwan induces that stable water-supply heavily depends on regulation of fluctuating streamflow by reservoirs. In Taiwan, rule curves are used in reservoir operation to determine water releases. Water storage below lower rule curve denotes the low water availability condition. A common measure adopted to mitigate such water deficits is water rationing, which reduces water supplies in advance and conserves more water for future use. Therefore, this study aims to construct optimal reservoir operation rules during drought period. Two types of optimization models are considered in the study. Mode I considers only the water-release coefficient as the decision variable, which the Model II considers the water-release coefficients associated with the lower rule curve as the decision variables. A multiple criteria decision making based approach integrates 7 water shortage indexes (maximum shortage event duration, maximum shortage event deficit, average shortage event duration, average shortage event deficit, risk, total shortage ratio, shortage event frequency)into a single objective to search the optimal solution using genetic algorithm. The proposed approach is applied to the Nanhua Reservoir located in southern Taiwan. The results show that both two optimization models are better than current operation, which model II outperforms model I.

Afshar, A., Mariño, M. A., Saadatpour, M., & Afshar, A. (2011). Fuzzy TOPSIS multi-criteria decision analysis applied to Karun reservoirs system. Water Resources Management, 25(2), 545-563.
Azmi, M., Araghinejad, S., & Sarmadi, F. (2011). A national-scale assessment of agricultural development feasibility using multi-criteria decision making (MCDM) Approaches. Advances in Natural & Applied Sciences, 5(4), 379-391
Babaei, H., Araghinejad, S., & Hoorfar, A. (2013). Developing a new method for spatial assessment of drought vulnerability (case study: Zayandeh‐Rood river basin in Iran). Water and Environment Journal, 27(1), 50-57.
Chang, L.-C., & Chang, F.-J. (2009). Multi-objective evolutionary algorithm for operating parallel reservoir system. Journal of Hydrology, 377(1), 12-20.
Chang, L.-C., Ho, C.-C., & Chen, Y.-W. (2009). Applying multiobjective genetic algorithm to analyze the conflict among different water use sectors during drought period. Journal of Water Resources Planning and Management, 136(5), 539-546.
Chang, L. C., & Chang, F. J. (2001). Intelligent control for modelling of real‐time reservoir operation. Hydrological Processes, 15(9), 1621-1634.
Chen, L. (2003). Real coded genetic algorithm optimization of long term reservoir operation1. Journal of the American Water Resources Association, 39(5), 1157-1165.
Chen, L., McPhee, J., & Yeh, W. W.-G. (2007). A diversified multiobjective GA for optimizing reservoir rule curves. Advances in Water Resources, 30(5), 1082-1093.
Draper, A. J., & Lund, J. R. (2004). Optimal hedging and carryover storage value. Journal of Water Resources Planning and Management, 130(1), 83-87.
Hashimoto, T., Stedinger, J. R., & Loucks, D. P. (1982). Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water Resources Research, 18(1), 14-20.
Heim, R. R. (2002). A review of twentieth-century drought indices used in the United States. Bulletin of the American Meteorological Society, 83(8). 1149-1165.
Hwang, C., & Yoon, K. Multiple attribute decision making: methods and applications, A State of the Art Survey. (1981). Sprinnger-Verlag, New York, NY.
Kangrang, A., & Chaleeraktrakoon, C. (2007). Genetic algorithms connected simulation with smoothing function for searching rule curves. American Journal of Applied Sciences, 4(2),73-79
Keyantash, J., & Dracup, J. A. (2002). The quantification of drought: An evaluation of drought indices. Bulletin of the American Meteorological Society, 83(8). 1167-1180
Labadie, J. W. (2004). Optimal operation of multireservoir systems: State-of-the-art review. Journal of Water Resources Planning and Management, 130(2), 93-111.
Liu, P., Guo, S., Xu, X., & Chen, J. (2011). Derivation of aggregation-based joint operating rule curves for cascade hydropower reservoirs. Water Resources Management, 25(13), 3177-3200.
Maity, R., Sharma, A., Nagesh Kumar, D., & Chanda, K. (2012). Characterizing drought using the reliability-resilience-vulnerability concept. Journal of Hydrologic Engineering, 18(7), 859-869.
Martin-Carrasco, F., Garrote, L., Iglesias, A., & Mediero, L. (2013). Diagnosing causes of water scarcity in complex water resources systems and identifying risk management actions. Water Resources Management 27(6): 1693-1705.
Mishra, A. K., & Singh, V. P. (2010). A review of drought concepts. Journal of Hydrology, 391(1), 202-216.
Moy, W. S., Cohon, J. L., and ReVelle, C. S. (1986). A programming model for analysis of the reliability, resilience, and vulnerability of a water supply reservoir. Water Resources Research, 22(4), 489-498.
Rittima, A. (2009). Hedging policy for reservoir system operation: a case study of Mun Bon and Lam Chae reservoirs. Kasetsart Journal. (Natural Science), 43(4), 833-842.
Rossi, G. and A. Cancelliere (2013). Managing drought risk in water supply systems in Europe: A review. International Journal of Water Resources Development, 29(2), 272-289.
Seifollahi-Aghmiuni, S., Haddad, O. B., Omid, M., & Mariño, M. (2013). Effects of pipe roughness uncertainty on water distribution network performance during its operational period. Water Resources Management, 27(5), 1581-1599.
Seifollahi-Aghmiuni, S., Haddad, O. B., Omid, M. H., & Mariño, M. A. (2011). Long-term efficiency of water networks with demand uncertainty. Proceedings of the ICE-Water Management, 164(3), 147-159.
Shiau, J.-T. (2009). Optimization of reservoir hedging rules using multiobjective genetic algorithm. Journal of Water Resources Planning and Management, 135(5), 355-363.
Shiau, J. (2003). Water release policy effects on the shortage characteristics for the Shihmen reservoir system during droughts. Water Resources Management, 17(6), 463-480.
Srdjevic, B., Medeiros, Y., & Faria, A. (2004). An objective multi-criteria evaluation of water management scenarios. Water Resources Management, 18(1), 35-54.
Srinivasan, K., & Philipose, M. (1996). Evaluation and selection of hedging policies using stochastic reservoir simulation. Water Resources Management, 10(3), 163-188.
Suiadee, W., & Tingsanchali, T. (2007). A combined simulation–genetic algorithm optimization model for optimal rule curves of a reservoir: a case study of the Nam Oon Irrigation Project, Thailand. Hydrological Processes, 21(23), 3211-3225.
Tu, M.-Y., Hsu, N.-S., Tsai, F. T.-C., & Yeh, W. W.-G. (2008). Optimization of hedging rules for reservoir operations. Journal of Water Resources Planning and Management, 134(1), 3-13.
Tu, M.-Y., Hsu, N.-S., & Yeh, W. W.-G. (2003). Optimization of reservoir management and operation with hedging rules. Journal of Water Resources Planning and Management, 129(2), 86-97.
Tung, C. P., Hsu, S. y., Liu, C. M., & Li Jr, S. (2003). Application of the genetic algorithm for optimizing operation rules of the liyutan reservoir in taiwan1. Journal of the American Water Resources Association, 39(3), 649-657.
Yin, X., Yang, Z., Yang, W., Zhao, Y., & Chen, H. (2010). Optimized reservoir operation to balance human and riverine ecosystem needs: model development, and a case study for the Tanghe reservoir, Tang river basin, China. Hydrological Processes, 24(4), 461-471.
You, J. Y., & Cai, X. (2008a). Hedging rule for reservoir operations: 1. A theoretical analysis. Water Resources Research, Vol.44,W01415,doi10.1029/ 2006
WR005481.
You, J. Y., & Cai, X. (2008b). Hedging rule for reservoir operations: 2. A numerical model. Water Resources Research, Vol.44,W01416,doi10.1029/ 2006
WR005482.
陳正炎, 姚嘉耀, 謝馥揚, 廖苑雅. (2006). 運用遺傳演算法推求水庫操作規線之研究-以明德水庫為例. 中華水土保持學報, 37(2), 173-184.
陳莉. (1995). 以物件導向之遺傳演算法優選水庫運用規線之硏究. 八十四年度農業工程研討會,541-555.
蕭政宗. (2000). 乾旱時期水庫供水策略對缺水影響分析. 農業工程學報,46(2), 54-74
蕭政宗, 黃景裕. (2010). 以遺傳演算法推導考量二衝突缺水指標之南化水庫多標的最佳限水策略. 農業工程學報, 56(4), 27-41.
鄭皆達, 陳裕仁. (2006). 模擬法及遺傳演算法應用於明德水庫操作規線之研究. 水土保持學報, 38(2), 129-140.
王惟芬. (2012).水資源地圖, 聯經出版公司
童慶斌, 許少瑜, 譚仲哲, 劉佳明. (2001). 水庫操作規線與啟發式優選方法. 中華水資源管理學會季刊, 3(3), 25-32.
童慶斌,陳佳正. (2002). 水庫操作方法探討及其應用. 九十一年度農業工程研討會, 543-551.
經濟部水利處規畫試驗所(2002).美濃水庫規劃檢討一、基本設計資料補充調查與檢討(一)高屏溪水源運用檢討工作.
經濟部水利署水利規畫試驗所(2009).烏山嶺第二隧道配合曾文越引計畫供水策略研究.
經濟部水利署南水局(2006).曾文水庫越域引水工程計畫-輸水工程可行性規劃成果檢討及設計-水源運用方式檢討報告.
經濟部水利署(2010).南化水庫運用規線要點.