水文不確定性為水文過程受到降雨、蒸發散、地表逕流等因素影響，而呈現不明確之狀態，並影響水庫供水狀況。本研究以石門水庫為研究案例，在考量水文不確定性，建立一套穩定供水模式。另外在制定人類供水目標的同時，本研究也考量保留下游河川一定流量以維護下游生態環境，達到生態水資源永續經營之目標。
本研究運用定率及階段性序率等兩種優選模式來瞭解水庫操作過程，以流量繁衍模式量化水文的不確定性，農業及公共用水參考現行石門水庫各標的之水權登記量，在環境流量的部份主要以基礎流量法來評估下游環境流量，在分析時根據超越機率將記錄年流量分為豐水年、平水年、枯水年及乾旱年等不同水文狀態，以兩種優選模式與現行M-5規線模擬結果進行比較，藉由缺水指標及風險評估指標，探討不同水文狀態下水庫供水受到水文不確定性之影響，從結果發現兩種優選模式比起M-5規線可改善嚴重缺水事件之缺水量，因此供水情形皆比M-5規線要來得佳，階段性序率模式因考量水文不確定性，其供水方式會比起定率模式要來得保守，但對於隔年水庫用水之影響為最小。而從平水年與豐水年分析結果，顯示隨著入流量豐沛，其入流量在時間上的不確定性也會提高，而影響該年供水結果。而M-5規線不考量環境需求時雖可改善農業及公用用水需求，但對於下游環境將造成嚴重衝擊。在分析水庫運作時，欲考量水文不確定之情況，決策者可運用階段性序率模式決定出合適的供水方式，並可做為日後水資源管理之參考。

Hydrological uncertainty is derived from a hydrological process which is influenced by rainfall, evapotranspiration or surface runoff. This may affect the water-supply in a reservoir. This study aims to provide a model of steady water-supply through hydrological uncertainty and supply environmental flow to maintain the downstream environment.
This study uses the deterministic optimization model and the two-Stage stochastic optimization model for optimizing changes in a storage. For the uncertainty assessment of inflow, this study uses the Thomas-Fiering model to generate a flow time series. Human demands for water are based on water rights of different users. Environmental flow assessment is based on a basic flow method. These results from the two optimization models are compared with the results from the M-5 Operation Rules. This study evaluates the condition of water supply through the Modified Shortage Index and the Risk Assessment Index. Results show that the two optimization models are better than the M-5 Operation Rules because of two optimization model can shorten the length of water shortages. Also the two-Stage stochastic optimization model is not superior to the deterministic optimization model due to the fact that the two-Stage stochastic optimization model considers inflow uncertainty, but can reduce the impact of the water supply for the next year. The results also show that when inflow is plentiful, inflow uncertainty may affect water supply. It is shown through the results that the two-Stage stochastic optimization model is the best choice.

Ahmed, J. A. and Sarma, A. K. Artificial neural network model for synthetic streamflow generation. Water Resources Management, 21(6), 1015-1029, 2007.
Ajami, N. K., Hornberger, G. M. and Sunding, D. L. Sustainable water resource management under hydrological uncertainty. Water Resources Research, 44(11), W11406, 2008.
Alcázar Montero, J. El método del caudal básico para la determinación de caudales de mantenimiento aplicación a la cuenca del ebro, 2007.
Andreu, J., Capilla, J. and Sanchís, E. Aquatool, a generalized decision-support system for water-resources planning and operational management. Journal of Hydrology, 177(3–4), 269-291, 1996.
Appleton, B. Appleton inquiry report. Health and Safety Executive. HMSO, London, 1992.
Awchi, T. A. and Srivastava, D. K. Analysis of drought and storage for mula project using ann and stochastic generation models. Hydrology Research, 40(1), 79, 2009.
Azaiez, M. N., Hariga, M. and Al-Harkan, I. A chance-constrained multi-period model for a special multi-reservoir system. Computers & Operations Research, 32(5), 1337-1351, 2005.
Beard, L. R. Hydrologic data management. Davis, Calif.: U.S. Hydrologic Engineering Center, 1972.
Beven, K. and Binley, A. The future of distributed models: Model calibration and uncertainty prediction. Hydrological Processes, 6(3), 279-298, 1992.
Celeste, A, B., Suzuki, K. and Kadota, A. Integrating long- and short-term reservoir operation models via stochastic and deterministic optimization: Case study in japan. Journal of Water Resources Planning and Management, 134(5), 440-448, 2008.
Chander, S., Kumar, A. and Spolia, S. Flood frequency analysis by power transformation. Journal of the Hydraulics Division, 104(11), 1495-1504, 1978.
Chang, L.-C., Chang, F.-J., Wang, K.-W. and Dai, S.-Y. Constrained genetic algorithms for optimizing multi-use reservoir operation. Journal of Hydrology, 390(1-2), 66-74, 2010.
Chen, H., Yang, L., Yang, Z. F. and Yu, S. W. Sustainable reservoir operations to balance upstream human needs and downstream lake ecosystem targets. Procedia Environmental Sciences, 13(0), 1444-1457, 2012.
Choudhari, S. and Anand Raj, P. Multiobjective multireservoir operation in fuzzy environment. Water Resources Management, 24(10), 2057-2073, 2010.
Dittmann, R., Froehlich, F., Pohl, R. and Ostrowski, M. Optimum multi-objective reservoir operation with emphasis on flood control and ecology. Nat. Hazards Earth Syst. Sci, 9, 1973-1980, 2009.
Ermolʹev, I. U. M. and Wets, R. J. B. Numerical techniques for stochastic optimization: Springer-Verlag, 1988
Fang, H. Optimization on water resource system operation policy during drought. Journal of Water Resource and Protection, 03(02), 140-146, 2011.
Franchini, M., Ventaglio, E. and Bonoli, A. A procedure for evaluating the compatibility of surface water resources with environmental and human requirements. Water Resources Management, 25(14), 3613-3634, 2011.
Fraser, J. C. Suggestions for developing flow recommendations for in-stream uses of new zealand streams / report to the national water and soil conservation organisation / by j.C. Fraser. Wellington, N.Z: Water and Soil Division, Ministry of Works and Development for the National Water and Soil Conservation Organization, 1978.
Harms, A. A. and Campbell, T. H. An extension to the thomas-fiering model for the sequential generation of streamflow. Water Resources Research, 3(3), 653-661, 1967.
Hashimoto, T., Stedinger, J. R. and Loucks, D. P. Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water Resources Research, 18(1), 14-20, 1982.
Hsu, N. and Cheng, K. Network flow optimization model for basin-scale water supply planning. Journal of Water Resources Planning and Management, 128(2), 102-112, 2002.
Huang, G. H. and Loucks, D. P. An inexact two-stage stochastic programming model for water resources management under uncertainty. Civil Engineering and Environmental Systems, 17(2), 95-118, 2000.
Gordon, N. D., McMahon, T. A., Finlayson, B. L., Gippel, C. J., and Nathan, R. J. Stream Hydrology: An Introduction for Ecologists: Wiley, 2004.
Kjeldsen, T. R. and Rosbjerg, D. Choice of reliability, resilience and vulnerability estimators for risk assessments of water resources systems / choix d’estimateurs de fiabilité, de résilience et de vulnérabilité pour les analyses de risque de systèmes de ressources en eau. Hydrological Sciences Journal, 49(5), null-767, 2004.
Kottegoda, N. T. Statistical methods of river flow synthesis for water resources assessment: Institution of Civil Engineers, 1971.
Kottegoda, N. T. Stochastic water resources technology. New York: Wiley, 1980
Krzysztofowicz, R. Bayesian system for probabilistic river stage forecasting. Journal of Hydrology, 268(1–4), 16-40, 2002.
Kuczera, G. A bayesian surrogate for regional skew in flood frequency analysis. Water Resources Research, 19(3), 821-832, 1983.
Kundzewicz, Z. W. and Kindler, J. Multiple criteria for evaluation of reliability aspects of water resource systems. IAHS Publications-Series of Proceedings and Reports-Intern Assoc Hydrological Sciences, 231, 217-224, 1995.
Langley, R. Unified approach to probabilistic and possibilistic analysis of uncertain systems. Journal of Engineering Mechanics, 126(11), 1163-1172, 2000.
Liu, C., Zhao, C., Xia, J., Sun, C., Wang, R. and Liu, T. An instream ecological flow method for data-scarce regulated rivers. Journal of Hydrology, 398(1–2), 17-25, 2011.
Loucks, D. P. Quantifying trends in system sustainability. Hydrological Sciences Journal, 42(4), 513-530, 1997.
Maidment, D. R. Handbook of hydrology: McGraw-Hill, 1993.
Mays, L. W. and Tung, Y. K. Hydrosystems engineering and management: Water Resources Publications, LLC, 2002.
McMahon, T. A. and Mein, R. G. River and reservoir yield: Water Resources Publications, 1986.
McMahon, T. A. and Miller, A. J. Application of the thomas and fiering model to skewed hydrologic data. Water Resources Research, 7(5), 1338-1340, 1971.
Milhous, R. T., Wegner, D. L., Waddle, T., Energy, W., Group, L. U. T. C. I. F. S., Agency, U. S. E. P. and Service, U. S. S. C. User's guide to the physical habitat simulation system (phabsim): The Team, 1984.
Modarres, R. Streamflow drought time series forecasting. Stochastic Environmental Research and Risk Assessment, 21(3), 223-233, 2006.
Mohan, S. and Sahoo, P. K. Stochastic simulation of droughts. Part 1: Point droughts. Hydrological Processes, 22(6), 854-862, 2008.
Montanari, A. What do we mean by ‘uncertainty’? The need for a consistent wording about uncertainty assessment in hydrology. Hydrological Processes, 21(6), 841-845, 2007.
Montanari, A. and Brath, A. A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resources Research, 40(1), W01106, 2004.
Ochoa-Rivera, J., Andreu, J. and García-Bartual, R. Influence of inflows modeling on management simulation of water resources system. Journal of Water Resources Planning and Management, 133(2), 106-116, 2007.
Palau, A. and Alcázar, J. The basic flow method for incorporating flow variability in environmental flows. River Research and Applications, 28(1), 93-102, 2012.
Phatarfod, R. M. Some aspects of stochastic reservoir theory. Journal of Hydrology, 30(3), 199-217, 1976.
Philips, C. Stochastic analysis and generation of streamflow data: Monash University, 1972.
Poff, N. L., Richter, B. D., Arthington, A. H., Bunn, S. E., Naiman, R. J., Kendy, E., Acreman, M., Apse, C., Bledsoe, B. P., Freeman, M. C., Henriksen, J., Jacobson, R. B., Kennen, J. G., Merritt, D. M., O’Keeffe, J. H., Olden, J. D., Rogers, K., Tharme, R. E. and Warner, A. The ecological limits of hydrologic alteration (eloha): A new framework for developing regional environmental flow standards. Freshwater Biology, 55(1), 147-170, 2010.
Prairie, J., Rajagopalan, B., Fulp, T. and Zagona, E. Modified k-nn model for stochastic streamflow simulation. Journal of Hydrologic Engineering, 11(4), 371-378, 2006.
Richter, B. D., Warner, A. T., Meyer, J. L. and Lutz, K. A collaborative and adaptive process for developing environmental flow recommendations. River Research and Applications, 22(3), 297-318, 2006.
Rosenberg, D. and Lund, J. Modeling integrated decisions for a municipal water system with recourse and uncertainties: Amman, jordan. Water Resources Management, 23(1), 85-115, 2009.
Sattari, M. T., Apaydin, H. and Ozturk, F. Operation analysis of eleviyan irrigation reservoir dam by optimization and stochastic simulation. Stochastic Environmental Research and Risk Assessment, 23(8), 1187-1201, 2009.
Schakke, J. C. Disaggregation processes in stochastic hydrology. Water Resources Research, 9(3), 580-585, 1973.
Seifi, A. and Hipel, K. Interior-point method for reservoir operation with stochastic inflows. Journal of Water Resources Planning and Management, 127(1), 48-57, 2001.
Sharma, A., Tarboton, D. G. and Lall, U. Streamflow simulation: A nonparametric approach. Water Resources Research, 33(2), 291-308, 1997.
Shirangi, E., Kerachian, R. and Bajestan, M. A simplified model for reservoir operation considering the water quality issues: Application of the young conflict resolution theory. Environmental Monitoring and Assessment, 146(1-3), 77-89, 2008.
Soltani, F., Kerachian, R. and Shirangi, E. Developing operating rules for reservoirs considering the water quality issues: Application of anfis-based surrogate models. Expert Systems with Applications, 37(9), 6639-6645, 2010.
Srikanthan, R. and McMahon, T. A. A review of lag-one markov models for generation of annual flows. Journal of Hydrology, 37(1–2), 1-12, 1978.
Srikanthan, R. and McMahon, T. A. Stochastic generation of monthly streamflows. Journal of the Hydraulics Division, 108(3), 419-441, 1982.
Stedinger, J. R. and Taylor, M. R. Synthetic streamflow generation: 1. Model verification and validation. Water Resources Research, 18(4), 909-918, 1982a.
Stedinger, J. R. and Taylor, M. R. Synthetic streamflow generation: 2. Effect of parameter uncertainty. Water Resources Research, 18(4), 919-924, 1982b.
Stewardson, M. and Cottingham, P. A demonstration of the flow events method: Environmental flow requirements of the broken river. Australian Journal of Water Resources, 5(1), 33, 2001.
Suen, J.-P. and Eheart, J. W. Reservoir management to balance ecosystem and human needs: Incorporating the paradigm of the ecological flow regime. Water Resources Research, 42(3), W03417, 2006.
Suen, J. P. Ecologically based methods for multi-objective water resources management in taiwan: University of Illinois at Urbana-Champaign, 2005.
Sun, T., Yang, Z., Shen, Z. and Zhao, R. Ecological water requirements for the source region of china's yangtze river under a range of ecological management objectives. Water International, 37(3), 236-252, 2012.
Tarekul, I. M. and Yoshihisa, K. (2009). Stochastic modeling and prediction of the ganges flow Advances in water resources and hydraulic engineering (pp. 6-11): Springer Berlin Heidelberg.
Tennant, D. L. Instream flow regimens for fish, wildlife, recreation and related environmental resources. Fisheries, 1(4), 6-10, 1976.
Thomas, H. and Fiering, M. Mathematical synthesis of streamflow sequences for the analysis of river basins by simulation. Design of water resource systems, 459-493, 1962.
Tu, M., Hsu, N., Tsai, F. and Yeh, W. Optimization of hedging rules for reservoir operations. Journal of Water Resources Planning and Management, 134(1), 3-13, 2008.
Wets, R. J. B. Solving stochastic programss with simple recourse. Stochastics, 10(3-4), 219-242, 1983.
Wilson, E. B. and Hilferty, M. M. The distribution of chi-square. Proceedings of the National Academy of Sciences, 17(12), 684-688, 1931.
Xu, Z., Schumann, A. and Li, J. Markov cross-correlation pulse model for daily streamflow generation at multiple sites. Advances in Water Resources, 26(3), 325-335, 2003.
Yang, Z. F., Sun, T., Cui, B. S., Chen, B. and Chen, G. Q. Environmental flow requirements for integrated water resources allocation in the yellow river basin, china. Communications in Nonlinear Science and Numerical Simulation, 14(5), 2469-2481, 2009.
Yeh, W. W. G. Reservoir Management and Operations Models: A State-of-the-Art Review. Water Resources Research, 21(12), 1797-1818, 1985.
Yin, X., Yang, Z., Yang, W., Zhao, Y. and Chen, H. 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, 2010.
Yin, X. A. and Yang, Z. F. Development of a coupled reservoir operation and water diversion model: Balancing human and environmental flow requirements. Ecological Modelling, 222(2), 224-231, 2011.
Yurekli, K., Kurunc, A., and Simsek, H. Prediction of daily maximum streamflow based on stochastic approaches. Journal of Spatial Hydrology, 4(2), 2012.
王瑞鋐，考量下游水質及河川流態於水庫最佳化操作之研究，國立成功大學碩士論文，(2009)。
行政院，「旱災災害防救業務計畫」，(2009)。
邱繼賢，兼顧環境流量之跨流域水資源運用－取法都江堰之引水概念，國立成功大學碩士論文，(2010)。
吳瑞賢，陳榮松，溫博文，保育用水推動策略規劃，(2005)。
財團法人農業工程研究中心，石門水庫供水區域各標的用水中長期規劃暨區域產業發展探討及推動之研究，(2008)。
蕭政宗、吳富春，「集集攔河堰最佳引水與河川生態流量之研究」，第十四屆水利工程研討會論文集，第C1-C8頁，(2004)
盧盈宏，以合作賽局理論應用於環境流量及社會需求之水資源分配，國立成功大學碩士論文，(2011)。