Skip to main content Accessibility help
×
Hostname: page-component-848d4c4894-ttngx Total loading time: 0 Render date: 2024-06-05T13:48:37.538Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  14 August 2009

K. D. W. Nandalal
Affiliation:
University of Peradeniya, Sri Lanka
Janos J. Bogardi
Affiliation:
United Nations University, Bonn, Germany
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Dynamic Programming Based Operation of Reservoirs
Applicability and Limits
, pp. 125 - 128
Publisher: Cambridge University Press
Print publication year: 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ampitiya, H. K. (1995). Stochastic dynamic programming based approaches for the operation of a multi-reservoir system. Master's Thesis, Wageningen Agricultural University, the Netherlands.
Ampitiya, H. K., Bogardi, J. J. and Nandalal, K. D. W. (1996). Derivation of optimal operation policies for the reservoirs of the complex Mahaweli water resources scheme in Sri Lanka via a stochastic dynamic programming based approach. In Proceedings of the International Conference on Aspects of Conflicts in Reservoir Development and Management, City University, London, UK, pp. 539–548.Google Scholar
Archibald, T. W., McKinnon, K. I. M. and Thomas, L. C. (1997). An aggregate stochastic dynamic programming model of multireservoir systems. Water Resources Research, 33(2), 333–340.CrossRefGoogle Scholar
Araujo, A. R. and Terry, L. A. (1974). Operation of a hydrothermal system (in Portuguese), BrazilJournal of Electrical Engineering.Google Scholar
Bellman, R. E. (1957). Dynamic Programming. Princeton, NJ: Princeton University Press.Google ScholarPubMed
Bellman, R. E. and Dreyfus, S. E. (1962). Applied Dynamic Programming. Princeton, NJ: Princeton University Press.CrossRefGoogle ScholarPubMed
Bogardi, J. J., Budhakooncharoen, S., Shrestha, D. L. and Nandalal, K. D. W. (1988). Effect of state space and inflow discretization on stochastic dynamic programming based reservoir operation rules and system performance. In Proceedings, 6th Congress, Asian and Pacific Regional Division, IAHR, Vol. 1, Kyoto, Japan, pp. 429–436.Google Scholar
Bogardi, J. J., Brorens, B. A. H. V., Kularathna, M. D. U. P., Milutin, D. and Nandalal, K. D. W. (1995). Long-term Assessment of a Multi-unit Reservoir System Operation: The ShellDP Program Package Manual. Report 59, Internal Publication Series, Department of Water Resources, Wageningen Agricultural University, the Netherlands.Google Scholar
Bogardi, J. J. and Milutin, D. (1995). Sequential decomposition in the assessment of long-term operation of large-scale systems. In S. P. Simonović, Z. Kundzewicz, D. Rosbjerg and K. Takeuchi (eds.), Modeling and Management of Sustainable Basin-Scale Water Resource Systems, Proceedings of a symposium held at the XXI General Assembly of the International Union of Geodesy and Geophysics (Boulder, 1995). IAHS Publ. No. 231, pp. 233–240.
Bogardi, J. J., Milutin, D., Louati, M. E. and Keser, H. (1994). The performance of a long-term operation policy of multi-unit reservoir systems under drought conditions. In Proceedings of the VIII IWRA World Congress: Satisfying Future National and Global Demands, Cairo, Egypt.Google Scholar
Bogardi, J. J. and Szöllösi-Nagy, A. (2004). Towards the water policies for the 21st century: a review after the World Summit on Sustainable Development in Johannesburg. In Cabrera, E. and Cobacho, R., (eds.), Challenges of the New Water Policies for the XXI Century. Proceedings of the Seminar on Challenges of the New Water Policies for the 21st Century, 2002. Lisse/Abingdon/Exton (PA)/Tokyo: A. A. Balkema Publishers, pp. 17–37.Google Scholar
Brass, C. (2006). Optimising operations of reservoir systems with stochastic dynamic programming (SDP) under consideration of changing objectives and constraints. Ph.D. Dissertation (in German), Ruhr Universitaet Bochum, Germany.
Budhakooncharoen, S. (1986). Comparison of reservoir operation strategies. Master's Thesis No. WA 86–3, Asian Institute of Technology, Bangkok, Thailand.
Budhakooncharoen, S. (1990). Interactive multi-objective decision making in reservoir operation. Doctoral Dissertation, Asian Institute of Technology, Bangkok, Thailand.
Butcher, W. S. (1971). Stochastic dynamic programming for optimum reservoir operation. Water Resources Bulletin, 7(1), 115–123.CrossRefGoogle Scholar
Chandramouli, V. and Raman, H. (2001). Multireservoir modeling with dynamic programming and neural networks. Journal of Water Resources Planning and Management, 127(2), 89–98.CrossRefGoogle Scholar
Chow, V. T. and Cortes-Rivera, G. (1974). Applications of DDDP in Water Resources Planning. Research Report 78, Urbana: University of Illinois, Water Resources Center.
Chow, V. T., Maidment, D. R. and Tauxe, G. W. (1975). Computer time and memory requirements for DP and DDDP in water resource systems analysis. Water Resources Research, 11(5), 621–628.CrossRefGoogle Scholar
Cosgrove, W. and Rijsberman, F. (2000). World Water Vision: Making Water Everybody's Business. London: Earthscan Publications Ltd.Google Scholar
Crawley, P. D. and Dandy, C. G. (1989). Optimum reservoir operation policies including salinity considerations. In Hydrology and Water Resources Symposium, Christchurch, New Zealand, pp. 289–293.Google Scholar
Dandy, C. G. and Crawley, P. D. (1990). Optimization of cost and salinity in reservoir operations. In Simonovic, S. P.et al. (eds.), Proceedings of the International Symposium on Water Resources Systems Application, University of Manitoba, Canada, pp. 452–461.Google Scholar
Dandy, C. G. and Crawley, P. D. (1992). Optimum operation of a multiple reservoir system including salinity effects. Water Resources Research, 28(4), 979–990.CrossRefGoogle Scholar
Dantzing, G. B. (1963). Linear Programming and Extension. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Dias, N. L. C., Pereira, M. V. F. and Kelman, J. (1985). Optimization of flood control and power generation requirements in a multi-purpose reservoir. In Proceedings of the IFAC Symposium on Planning and Operation of Electric Energy Systems, Rio de Janeiro, Brazil, pp. 121–124.Google Scholar
Duckstein, L., Bogardi, J. J. and Huang, W. C. (1989). Decision rule for switching the operation mode of a multipurpose reservoir. In Loucks, D. P. (ed.), Proceedings of the Symposium on Systems Analysis for Water Resources Management: Closing the Gap Between Theory and Practice. IAHS Publication No. 180, Baltimore, pp. 151–161.Google Scholar
Faber, B. A. and Stedinger, J. R (2001). SSDP reservoir models using ensemble streamflow prediction (ESP) forecasts. In Phelps, D. and Sehlke, G. (eds.), Proceedings of the World Water and Environmental Resources Congress 2001, Bridging the Gap: Meeting the World's Water and Environmental Resources Challenges, Orlando, FL, USA.Google Scholar
Fan, K-Y. D., Shoemaker, C. A. and Ruppert, D. (2000). Regression dynamic programming for multiple-reservoir control. In Proceedings of Building Partnerships – 2000 Joint Conference on Water Resource Engineering and Water Resources Planning & Management (doi 10.1061/40517(2000)424).CrossRef
Fan, K-Y. D., Shoemaker, C. A. and Ruppert, D. (2001). Stochastic multiple-reservoir optimization using regression dynamic programming. In Proceedings of the World Water and Environmental Resources Congress, Bridging the Gap: Meeting the World's Water and Environmental Resources Challenges (doi 10.1061/40569(2001)158).
Fontane, D. G., Labadie, J. W. and Loftis, B. (1981). Optimal control of reservoir discharge quality through selective withdrawal. Water Resources Research, 17(6), 1594–1604.CrossRefGoogle Scholar
Foufoula-Georgiou, E. and Kitanidis, P. K. (1988). Gradient dynamic programming for stochastic optimal control of multidimensional water resources systems. Water Resources Research, 24(8), 1345–1359.CrossRefGoogle Scholar
Gablinger, M. and Loucks, D. P. (1970). Markov models for flow regulation. Journal of Hydraulics Division, ASCE, 96(HY1), 165–181.Google Scholar
Gal, S. (1979). Optimal management of a multireservoir water supply system. Water Resources Research, 15(4), 737–749.CrossRefGoogle Scholar
Gilbert, K. C. and Shane, R. M. (1982). TVA hydro scheduling model: theoretical aspects. Journal of Water Resources Planning and Management, 108(1), 1–20.Google Scholar
Goulter, I. C. and Tai, F-K. (1985). Practical implications in the use of stochastic dynamic programming for reservoir operation. Water Resources Bulletin, 121(1), 65–74.CrossRefGoogle Scholar
Haimes, Y. Y. (1977). Hierarchical Analyses of Water Resources Systems. New York: McGraw-Hill.Google Scholar
Haimes, Y. Y. (1982). Modeling of large scale systems in a hierarchical-multiobjective framework. Studies in Management Science and Systems, 7: 1–17, Amsterdam: North-Holland Publishing Company.Google Scholar
Hall, W. A. and Buras, N. (1961). The dynamic programming aproach to water resources development. Journal of Geophysical Research, 66(2), 517–520.CrossRefGoogle Scholar
Hall, W. A. and Dracup, J. A. (1970). Water Resources Systems Engineering, New York: McGraw-Hill.Google Scholar
Hall, W. A. and Shepard, R. W. (1967). Optimum Operation for Planning of a Complex Water Resources System, Technical Report 122 (UCLA-ENG 67–54), Water Resources Center, School of Engineering and Applied Science, University of California, USA.Google Scholar
Harboe, R. (1987). Application of optimization models to synthetic hydrologic samples. In Proceedings of the International Symposium on Water for the Future, Rome, Italy.Google Scholar
Harboe, R., Gautam, T. R. and Onta, P. R. (1995). Conjunctive operation of hydroelectric and thermal power plants. Water Resources Journal, ST/ESCAP/SER.C/186: 54–63 (reprint from Journal of Water Resources Planning and Management, 120(6), 1994).Google Scholar
Harboe, R. C., Mobasheri, F. and Yeh, W. W-G. (1970). Optimal policy for reservoir operation. Journal of Hydraulic Division, ASCE, 96 (HY11), 2297–2308.Google Scholar
He, Q., Nandalal, K. D. W., Bogardi, J. J. and Milutin, D. (1995). Application of Stochastic Dynamic Programming Models in Optimization of Reservoir Operations: A Study of Algorithmic Aspects. Report 56, Internal Publication Series, Department of Water Resources, Wageningen Agricultural University, the Netherlands.Google Scholar
Heidari, M., Chow, V. T., Kokotovic, P. V. and Meridith, D. D. (1971). Discrete differential dynamic programming approach to water resources systems optimizations. Water Resources Research, 7(2), 273–282.CrossRefGoogle Scholar
Hillier, F. S. and Lieberman, G. J. (1990). Introduction to Operations Research. New York: McGraw-Hill.Google Scholar
Howard, R. A. (1960). Dynamic Programming and Markov Processes. Cambridge, MA, USA: MIT Press.Google Scholar
Huang, W-C. (1989). Multiobjective decision making in the on-line operation of a multipurpose reservoir, Doctoral Dissertation, Asian Institute of Technology, Bangkok, Thailand.
Huang, W.-C., Harboe, R. and Bogardi, J. J. (1991). Testing stochastic dynamic programming models conditioned on observed or forecasted inflows. Journal of Water Resources Planning and Management, 117(1), 28–36.CrossRefGoogle Scholar
Jacoby, H. D. and Loucks, D. P. (1972). Combined use of optimization and simulation models in river basin planning. Water Resources Research, 8(6), 1401–1414.CrossRefGoogle Scholar
Jaworski, N. A., Weber, W. J. and Deininger, R. A. (1970). Optimal reservoir releases for water quality control. Journal of the Sanitary Engineering Division, ASCE, 96(SA3), 727–740.Google Scholar
Johnson, S. A., Stedinger, J. R., Shoemaker, C. A., Li, Y. and Tejada-Guibert, J. A. (1993). Numerical solution of continuous-state dynamic programs using linear and spline interpolation. Operations Research, 41(3), 484–500.CrossRefGoogle Scholar
Karamouz, M. and Houck, M. H. (1982). Annual and monthly reservoir operating rules generated by deterministic optimization. Water Resources Research, 18(5), 1337–1344.CrossRefGoogle Scholar
Karamouz, M. and Houck, M. H. (1987). Comparison of stochastic and deterministic dynamic programming for reservoir operating rule generation. Water Resources Bulletin, 23(1), 1–9.CrossRefGoogle Scholar
Karamouz, M. and Mousavi, S. J. (2003). Uncertainty based operation of large scale reservoir systems: Dez and Karoon experience. Journal of the American Water Resources Association, 39(4), 961–975.CrossRefGoogle Scholar
Karamouz, M. and Vasiliadis, H. V. (1992). Bayesian stochastic optimization of reservoir operation using uncertain forecasts. Water Resources Research, 28(5), 1221–1232.CrossRefGoogle Scholar
Keeney, R. L. and Raiffa, H. (1976). Decisions with Multiple Objectives: Preferences and Value Tradeoffs. New York: John Wiley and Sons.Google Scholar
Kelman, J., Cooper, L. A., Hsu, E. and Yuan, Sun-Quan (1988). The use of probabilistic constraints in reservoir operation policies with sampling stochastic dynamic programming. In Proceedings of the 3rd Water Resources Operations and Management Workshop, Colorado, USA, pp. 1–9.Google Scholar
Kelman, J., Stedinger, J. R., Cooper, L. A., Hsu, E. and Yuan, Sun-Quan (1990). Sampling stochastic dynamic programming applied to reservoir operation. Water Resources Research, 26(3), 447–454.CrossRefGoogle Scholar
Kitanidis, P. K. and Foufoula-Georgiou, E. (1987). Error analysis of conventional discrete and gradient dynamic programming. Water Resources Research, 23(5), 845–858.CrossRefGoogle Scholar
Kularathna, M. D. U. P. (1992). Application of dynamic programming for the analysis of complex water resources systems: a case study on the Mahaweli river basin development in Sri Lanka. Ph.D. Dissertation. Wageningen Agricultural University, the Netherlands.
Kularathna, M. D. U. P. and Bogardi, J. J. (1990). Simplified system configurations for stochastic dynamic programming based optimization of multireservoir systems. Water resources systems application. In Simonovic, S. P.et al. (eds.), Proceedings of the International Symposium on Water Resources Systems Application, University of Manitoba, Canada.Google Scholar
Kumar, D. N. and Baliarsingh, F. (2003). Folded dynamic programming for optimal operation of multireservoir system. Water Resources Management, 17, 337–353.CrossRefGoogle Scholar
Laabs, H. and Harboe, R. (1988). Generation of operating rules with stochastic dynamic programming and multiple objectives. Water Resources Management, 2, 221–227.CrossRefGoogle Scholar
Labadie, J. W. and Fontane, D. G. (1986). Objective space dynamic programming approach to multidimensional problems in water resources. In Esogbue, A. O. (ed.), Proceedings of the Bellman Continuum-Special NSF Workshop on Dynamic Programming and Water Resources, Georgia Institute of Technology, Atlanta, USA.Google Scholar
Lane, W. L. and Frevert, D. K. (1989). Applied Stochastic Techniques, User Manual. Bureau of Reclamation, Engineering Research Center, Denver, Colorado.Google Scholar
Larson, R. E. (1968). State Incremental Dynamic Programming. New York: Elsevier.Google Scholar
Liang, Q., Johnson, L. E. and Yu, Y-S. (1996). A comparison of two methods for multiobjective optimization for reservoir operation. Water Resources Bulletin, 32(2), 333–340.CrossRefGoogle Scholar
Loucks, D. P., Stedinger, J. R. and Haith, D. A. (1981). Water Resources Systems Planning and Analysis. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Loucks, D. P. and van Beek, E. (2005). In Water Resources Systems Planning and Management: An Introduction to Methods, Models and Applications (with contributions from Stedinger, J. R., Dijkman, J. P. M. and Villars, M. T.), Studies and Reports in Hydrology, Paris: UNESCO Publishing.Google Scholar
Maidment, D. R. and Chow, V. T. (1981). Stochastic state variable dynamic programming for reservoir systems analysis. Water Resources Research, 17(6), 1578–1584.CrossRefGoogle Scholar
Matalas, N. C. (1967). Mathematic assessment of synthetic hydrology. Water Resources Research, 3(4), 937–945.CrossRefGoogle Scholar
Mawer, P. A. and Thorn, D. (1974). Improved dynamic programming procedures and their practical application to water resource systems. Water Resources Research, 10(2), 183–190.CrossRefGoogle Scholar
Meier, W. L. and Beightler, C. S. (1967). An optimization method for branching multistage water resources systems, Water Resources Research, 3(9), 645–652.CrossRefGoogle Scholar
Millennium Development Goals (MDGs) (2000). UNITED NATIONS Development Programme (UNDP) Website www.undp.org/mdg/basics.shtml, viewed March 10, 2006.
Millennium Ecosystem Assessment (2005). Ecosystems and Human Well-Being: Current State and Trends. Findings of the Condition and Trends Working Group. Millennium Ecosystem Assessment Series. Washington, DC: Island Press.
Milutin, D. (1998). Multiunit water resource systems management by decomposition, optimization and emulated evolution. Ph.D. Dissertation, Department of Water Resources, Wageningen Agricultural University, the Netherlands.
Mousavi, S. J., Karamouz, M. and Menhadj, M. B. (2004). Fuzzy-state stochastic dynamic programming for reservoir operation. Journal of Water Resources Planning and Management, 130(6), 460–470.CrossRefGoogle Scholar
Murray, D. M. and Yakowitz, S. J. (1979). Constrained differential dynamic programming and its application to multireservoir control. Water Resources Research, 15(5), 1017–1027.CrossRefGoogle Scholar
Nandalal, K. D. W. (1986). Operation policies for two multipurpose reservoirs of the Mahaweli Development Scheme in Sri Lanka. M.Eng. Thesis No.WA-86-9, Asian Institute of Technology, Bangkok, Thailand.
Nandalal, K. D. W. (1995). Reservoir management under consideration of stratification and hydraulic phenomena. Ph.D. Dissertation, Department of Water Resources, Wageningen Agricultural University, the Netherlands.
Nandalal, K. D. W. (1998). The use of optimization techniques in planning and management of complex water resources systems. In Proceedings of the National Conference Status and Future Direction of Water Research in Sri Lanka, pp. 119–129.Google Scholar
Nandalal, K. D. W. and Ampitiya, H. K. (1997). The assessment of long-term operation of multi-unit reservoir systems. Engineer, Journal of the Institution of Engineers, Sri Lanka, 26(2), 16–24.Google Scholar
Nandalal, K. D. W. and Sakthivadivel, R. (2002). Planning and management of a complex water resources system: case study of Samanalawewa and Udawalawe reservoirs in the Walawe river, Sri Lanka. Agricultural Water Management, 57(3), 207–221.CrossRefGoogle Scholar
Nopmongcol, P. and Askew, A. J. (1976). Multi-level incremental dynamic programming. Water Resources Research, 12(6), 1291–1297.CrossRefGoogle Scholar
Opricović, S. and Djordjević, B. (1976). Optimal long-term control of a multipurpose reservoir with indirect users. Water Resources Research, 12(6), 1286–1290.CrossRefGoogle Scholar
Orlob, G. T. and Simonovic, S. P. (1981). Reservoir operation for water quality control. In Proceedings of the International Symposium on Real-Time Operation of Hydrosystems, Waterloo, Ontario, Canada, pp. 599–616.Google Scholar
Palmer, R. N. and Holmes, K. J. (1988). Operational guidance during droughts: expert systems approach. Journal of Water Resources Planning and Management, 114(6), 647–666.CrossRefGoogle Scholar
Phien, H. N. and Ruksasilp, W. (1981). A review of single site models for monthly streamflow generation. Journal of Hydrology, 52, 1–12.CrossRefGoogle Scholar
Randall, D., Houck, M. H. and Wright, J. R. (1990). Drought management of existing water supply system. Journal of Water Resources Planning and Management, 116(1), 1–20.CrossRefGoogle Scholar
Ratnayake, U. R. (1995). Sequential stochastic optimization of a reservoir system. Doctoral Dissertation No. WA 95-2, Asian Institute of Technology, Bangkok, Thailand.
Reznicek, K. K. and Simonovic, S. P. (1990). An improved algorithm for hydropower optimization, Water Resources Research, 26(2), 189–198.CrossRefGoogle Scholar
Reznicek, K. K. and Simonovic, S. P. (1992). Issues in hydropower modeling using the GEMSLP algorithm, Journal of Water Resources Planning and Management, 118(1), 54–70.CrossRefGoogle Scholar
Roefs, T. G. and Bodin, L. D. (1970). Multireservoir operation studies. Water Resources Research, 6(2), 410–420.CrossRefGoogle Scholar
Rogers, D. F., Plante, R. D., Wong, R. T. and Evans, J. R. (1991). Aggregation and disaggregation techniques and methodology in optimization. Operations Research, 39(4), 553–582.CrossRefGoogle Scholar
Saad, M. and Turgeon, A. (1988). Application of principal component analysis to long-term reservoir management. Water Resources Research, 24(7), 907–912.CrossRefGoogle Scholar
Saad, M., Turgeon, A. and Stedinger, J. R. (1992). Censored-data correlation and principal component dynamic programming. Water Resources Research, 28(8), 2135–2140.CrossRefGoogle Scholar
Saad, M., Turgeon, A., Bigras, P. and Duquette, R. (1994). Learning disaggregation technique for the operation of long-term hydroelectric power systems. Water Resources Research, 30(11), 3195–3202.CrossRefGoogle Scholar
Shane, R. M. and Gilbert, K. C. (1982). TVA hydro scheduling model: practical aspects. Journal of Water Resources Planning and Management, 108(1), 21–36.Google Scholar
Shiati, K. (1991). Salinity management in river basins: modelling and management of the salt-affected Jarreh Reservoir. Doctoral Dissertation, Wageningen Agricultural University, the Netherlands.
Shrestha, D. L. (1987). Optimal hydropower system configuration considering operational aspects, M.Eng. Thesis, Asian Institute of Technology, Bangkok, Thailand.
Shrestha, D. L., Bogardi, J. J. and Paudyal, G. N. (1990). Evaluating alternative state space discretization in stochastic dynamic programming for reservoir operation studies. In Simonovic, S. P.et al. (eds.), Proceedings of the International Conference on Water Resources Systems Application, University of Manitoba, Canada, pp. 378–387.Google Scholar
Simonovic, S. P. (2000). A shared vision for management of water resources. Water International, 25(1).CrossRefGoogle Scholar
Simonovic, S. P. and Orlob, G. T. (1981). Optimization of New Melons Reservoir operation for water quality management. In Proceedings of International Conference on Environmental Systems Analysis and Management, International Federation for Information Processing, Rome, Italy.Google Scholar
Simonovic, S. P. and Orlob, G. T. (1984). Risk–reliability programming for optimal water quality control. Water Resources Research, 20(6), 639–646.CrossRefGoogle Scholar
Sinotech Engineering Consultants Inc. (1985). Technical Report of the Operational Rules of Feitsui Reservoir. Sponsored by the Taiwan Power Company.
Stedinger, J. R., Sule, B. F. and Loucks, D. P. (1984). Stochastic dynamic programming models for reservoir operation optimization. Water Resources Research, 20(11), 1499–1505.CrossRefGoogle Scholar
Su, S. Y. and Deininger, R. A. (1974). Modeling the regulation of Lake Superior under uncertainty of future water supplies. Water Resources Research, 10(1), 11–25.CrossRefGoogle Scholar
Tai, F. K. and Goulter, I. C. (1987). A stochastic dynamic programming based approach to the operation of a multireservoir system. Water Resources Bulletin, 23(3), 371–377.CrossRefGoogle Scholar
Takeuchi, K. (2002). Future of reservoirs and their management criteria. In Bogardi, J. J. and Kundzewicz, Z. W. (eds.), Risk, Reliability, Uncertainty, and Robustness of Water Resources Systems, Cambridge, UK: Cambridge University Press, pp. 190–198.CrossRefGoogle Scholar
Teixeira, A. S. and Marino, M. A. (2002). Coupled reservoir operation–irrigation scheduling by dynamic programming. Journal of Irrigation and Drainage Engineering, 128(2), 63–73.CrossRefGoogle Scholar
Tejada-Guibert, J. A., Johnson, S. A. and Stedinger, J. R. (1993). Comparison of two approaches for implementing multireservoir operation policies derived using stochastic dynamic programming. Water Resources Research, 29(12), 3969–3980.CrossRefGoogle Scholar
Tejada-Guibert, J. A., Johnson, S. A. and Stedinger, J. R. (1995). The value of hydrologic information in stochastic dynamic programming models of a multireservoir system. Water Resources Research, 31(10), 2571–2579.CrossRefGoogle Scholar
Thomas, H. A. and Fiering, M. B. (1962). Mathematical synthesis of streamflow sequences for the analysis of river basins by simulation. In Mass, A.et al. (eds.), Design of Water Resources Systems, Cambridge, MA: Harvard University Press, pp. 459–493.CrossRefGoogle Scholar
Tilmant, A., Vanclooster, M., Duckstein, L. and Persoons, E. (2002). Comparison of fuzzy and nonfuzzy optimal reservoir operation policies, Journal of Water Resources Planning and Management, 128(6), 390–398.CrossRefGoogle Scholar
Trott, W. J. and Yeh, W.W-G. (1973). Optimization of multiple reservoir systems. Journal of the Hydraulics Division, ASCE, 99(HY10), 1865–1884.Google Scholar
Turgeon, A. (1980). Optimal operation of multireservoir power systems with stochastic inflows. Water Resources Research, 16(2), 275–283.CrossRefGoogle Scholar
Turgeon, A. (1981). A decomposition method for the long-term scheduling of reservoirs in series. Water Resources Research, 17(6), 1565–1570.CrossRefGoogle Scholar
Turgeon, A. (1982). Incremental dynamic programming may yield nonoptimal solutions. Water Resources Research, 18(6), 1599–1604.CrossRefGoogle Scholar
Umamahesh, N. V. and Chandramouli, S. (2004). Fuzzy dynamic programming model for optimal operation of a multipurpose reservoir. In Herath, S., Pathirana, A. and Weerakoon, S. B. (eds.), Proceedings of the International Conference on Sustainable Water Resources Management in the Changing Environment of the Monsoon Region, Vol. II, November, Sri Lanka, pp. 552–557.Google Scholar
UN (1992). Agenda 21. United Nations Conference on Environment & Development, Rio de Janerio, Brazil, 3 to 14 June 1992. www.un.org/esa/sustdev/documents/agenda21/english/Agenda21.pdf.
Vasiliadis, H. V. and Karamouz, M. (1994). Demand-driven operation of reservoirs using uncertainty-based optimal operation policies. Journal of Water Resources Planning and Management, 120(1), 101–114.CrossRefGoogle Scholar
Vedula, S. and Kumar, D. N. (1996). An integrated model for optimal reservoir operation for irrigation of multiple crops. Water Resources Research, 32(4), 1101–1108.CrossRefGoogle Scholar
Verhaeghe, R. J. and Tholan, N. (1983). Illustrative Examples of Optimization Techniques for Quantitative and Qualitative Water Management. Report on Investigation, Report R999-8. Delft Hydraulics Laboratory, the Netherlands.
WCED (World Commission on Environment and Development) (1987). Our Common Future. New York: Oxford University Press.
World Commission on Dams (2000). Dams and Development: A New Framework for Decision-Making. The Report of the World Commission on Dams. London: Earthscan Publications Ltd.
World Water Assessment Programme (2003). Water for People Water for Life: The United Nations World Water Development Report. UNESCO Publishing and Bernan Association.
WSSD (2002). Johannesburg Plan of Implementation. World Summit on Sustainable Development, August 26–September 4, 2002, Johannesburg, South Africa. www.un.org/esa/sustdev/documents/WSSD_POI_PD/English/WSSD_PlanImpl.pdf.
Wurbs, R. A. (1993). Reservoir-system simulation and optimization models. Journal of Water Resources Planning and Management, 119(4), 455–472.CrossRefGoogle Scholar
Yakowitz, S. (1982). Dynamic programming applications in water resources. Water Resources Research, 18(4), 673–696.CrossRefGoogle Scholar
Yeh, W. W-G. (1985). Reservoir management and operation models: a state-of-the-art review. Water Resources Research, 21(12), 1797–1818.CrossRefGoogle Scholar
Yekom Consulting Engineers (1980). Shapur and Dalaki Project Feasibility Report, Jarreh Storage Dam. Vol.1: Engineering.
Young, G. K. (1967). Finding reservoir operation rules. Journal of the Hydraulics Division, ASCE, 93(HY6), 297–321.Google Scholar
Ampitiya, H. K. (1995). Stochastic dynamic programming based approaches for the operation of a multi-reservoir system. Master's Thesis, Wageningen Agricultural University, the Netherlands.
Ampitiya, H. K., Bogardi, J. J. and Nandalal, K. D. W. (1996). Derivation of optimal operation policies for the reservoirs of the complex Mahaweli water resources scheme in Sri Lanka via a stochastic dynamic programming based approach. In Proceedings of the International Conference on Aspects of Conflicts in Reservoir Development and Management, City University, London, UK, pp. 539–548.Google Scholar
Archibald, T. W., McKinnon, K. I. M. and Thomas, L. C. (1997). An aggregate stochastic dynamic programming model of multireservoir systems. Water Resources Research, 33(2), 333–340.CrossRefGoogle Scholar
Araujo, A. R. and Terry, L. A. (1974). Operation of a hydrothermal system (in Portuguese), BrazilJournal of Electrical Engineering.Google Scholar
Bellman, R. E. (1957). Dynamic Programming. Princeton, NJ: Princeton University Press.Google ScholarPubMed
Bellman, R. E. and Dreyfus, S. E. (1962). Applied Dynamic Programming. Princeton, NJ: Princeton University Press.CrossRefGoogle ScholarPubMed
Bogardi, J. J., Budhakooncharoen, S., Shrestha, D. L. and Nandalal, K. D. W. (1988). Effect of state space and inflow discretization on stochastic dynamic programming based reservoir operation rules and system performance. In Proceedings, 6th Congress, Asian and Pacific Regional Division, IAHR, Vol. 1, Kyoto, Japan, pp. 429–436.Google Scholar
Bogardi, J. J., Brorens, B. A. H. V., Kularathna, M. D. U. P., Milutin, D. and Nandalal, K. D. W. (1995). Long-term Assessment of a Multi-unit Reservoir System Operation: The ShellDP Program Package Manual. Report 59, Internal Publication Series, Department of Water Resources, Wageningen Agricultural University, the Netherlands.Google Scholar
Bogardi, J. J. and Milutin, D. (1995). Sequential decomposition in the assessment of long-term operation of large-scale systems. In S. P. Simonović, Z. Kundzewicz, D. Rosbjerg and K. Takeuchi (eds.), Modeling and Management of Sustainable Basin-Scale Water Resource Systems, Proceedings of a symposium held at the XXI General Assembly of the International Union of Geodesy and Geophysics (Boulder, 1995). IAHS Publ. No. 231, pp. 233–240.
Bogardi, J. J., Milutin, D., Louati, M. E. and Keser, H. (1994). The performance of a long-term operation policy of multi-unit reservoir systems under drought conditions. In Proceedings of the VIII IWRA World Congress: Satisfying Future National and Global Demands, Cairo, Egypt.Google Scholar
Bogardi, J. J. and Szöllösi-Nagy, A. (2004). Towards the water policies for the 21st century: a review after the World Summit on Sustainable Development in Johannesburg. In Cabrera, E. and Cobacho, R., (eds.), Challenges of the New Water Policies for the XXI Century. Proceedings of the Seminar on Challenges of the New Water Policies for the 21st Century, 2002. Lisse/Abingdon/Exton (PA)/Tokyo: A. A. Balkema Publishers, pp. 17–37.Google Scholar
Brass, C. (2006). Optimising operations of reservoir systems with stochastic dynamic programming (SDP) under consideration of changing objectives and constraints. Ph.D. Dissertation (in German), Ruhr Universitaet Bochum, Germany.
Budhakooncharoen, S. (1986). Comparison of reservoir operation strategies. Master's Thesis No. WA 86–3, Asian Institute of Technology, Bangkok, Thailand.
Budhakooncharoen, S. (1990). Interactive multi-objective decision making in reservoir operation. Doctoral Dissertation, Asian Institute of Technology, Bangkok, Thailand.
Butcher, W. S. (1971). Stochastic dynamic programming for optimum reservoir operation. Water Resources Bulletin, 7(1), 115–123.CrossRefGoogle Scholar
Chandramouli, V. and Raman, H. (2001). Multireservoir modeling with dynamic programming and neural networks. Journal of Water Resources Planning and Management, 127(2), 89–98.CrossRefGoogle Scholar
Chow, V. T. and Cortes-Rivera, G. (1974). Applications of DDDP in Water Resources Planning. Research Report 78, Urbana: University of Illinois, Water Resources Center.
Chow, V. T., Maidment, D. R. and Tauxe, G. W. (1975). Computer time and memory requirements for DP and DDDP in water resource systems analysis. Water Resources Research, 11(5), 621–628.CrossRefGoogle Scholar
Cosgrove, W. and Rijsberman, F. (2000). World Water Vision: Making Water Everybody's Business. London: Earthscan Publications Ltd.Google Scholar
Crawley, P. D. and Dandy, C. G. (1989). Optimum reservoir operation policies including salinity considerations. In Hydrology and Water Resources Symposium, Christchurch, New Zealand, pp. 289–293.Google Scholar
Dandy, C. G. and Crawley, P. D. (1990). Optimization of cost and salinity in reservoir operations. In Simonovic, S. P.et al. (eds.), Proceedings of the International Symposium on Water Resources Systems Application, University of Manitoba, Canada, pp. 452–461.Google Scholar
Dandy, C. G. and Crawley, P. D. (1992). Optimum operation of a multiple reservoir system including salinity effects. Water Resources Research, 28(4), 979–990.CrossRefGoogle Scholar
Dantzing, G. B. (1963). Linear Programming and Extension. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Dias, N. L. C., Pereira, M. V. F. and Kelman, J. (1985). Optimization of flood control and power generation requirements in a multi-purpose reservoir. In Proceedings of the IFAC Symposium on Planning and Operation of Electric Energy Systems, Rio de Janeiro, Brazil, pp. 121–124.Google Scholar
Duckstein, L., Bogardi, J. J. and Huang, W. C. (1989). Decision rule for switching the operation mode of a multipurpose reservoir. In Loucks, D. P. (ed.), Proceedings of the Symposium on Systems Analysis for Water Resources Management: Closing the Gap Between Theory and Practice. IAHS Publication No. 180, Baltimore, pp. 151–161.Google Scholar
Faber, B. A. and Stedinger, J. R (2001). SSDP reservoir models using ensemble streamflow prediction (ESP) forecasts. In Phelps, D. and Sehlke, G. (eds.), Proceedings of the World Water and Environmental Resources Congress 2001, Bridging the Gap: Meeting the World's Water and Environmental Resources Challenges, Orlando, FL, USA.Google Scholar
Fan, K-Y. D., Shoemaker, C. A. and Ruppert, D. (2000). Regression dynamic programming for multiple-reservoir control. In Proceedings of Building Partnerships – 2000 Joint Conference on Water Resource Engineering and Water Resources Planning & Management (doi 10.1061/40517(2000)424).CrossRef
Fan, K-Y. D., Shoemaker, C. A. and Ruppert, D. (2001). Stochastic multiple-reservoir optimization using regression dynamic programming. In Proceedings of the World Water and Environmental Resources Congress, Bridging the Gap: Meeting the World's Water and Environmental Resources Challenges (doi 10.1061/40569(2001)158).
Fontane, D. G., Labadie, J. W. and Loftis, B. (1981). Optimal control of reservoir discharge quality through selective withdrawal. Water Resources Research, 17(6), 1594–1604.CrossRefGoogle Scholar
Foufoula-Georgiou, E. and Kitanidis, P. K. (1988). Gradient dynamic programming for stochastic optimal control of multidimensional water resources systems. Water Resources Research, 24(8), 1345–1359.CrossRefGoogle Scholar
Gablinger, M. and Loucks, D. P. (1970). Markov models for flow regulation. Journal of Hydraulics Division, ASCE, 96(HY1), 165–181.Google Scholar
Gal, S. (1979). Optimal management of a multireservoir water supply system. Water Resources Research, 15(4), 737–749.CrossRefGoogle Scholar
Gilbert, K. C. and Shane, R. M. (1982). TVA hydro scheduling model: theoretical aspects. Journal of Water Resources Planning and Management, 108(1), 1–20.Google Scholar
Goulter, I. C. and Tai, F-K. (1985). Practical implications in the use of stochastic dynamic programming for reservoir operation. Water Resources Bulletin, 121(1), 65–74.CrossRefGoogle Scholar
Haimes, Y. Y. (1977). Hierarchical Analyses of Water Resources Systems. New York: McGraw-Hill.Google Scholar
Haimes, Y. Y. (1982). Modeling of large scale systems in a hierarchical-multiobjective framework. Studies in Management Science and Systems, 7: 1–17, Amsterdam: North-Holland Publishing Company.Google Scholar
Hall, W. A. and Buras, N. (1961). The dynamic programming aproach to water resources development. Journal of Geophysical Research, 66(2), 517–520.CrossRefGoogle Scholar
Hall, W. A. and Dracup, J. A. (1970). Water Resources Systems Engineering, New York: McGraw-Hill.Google Scholar
Hall, W. A. and Shepard, R. W. (1967). Optimum Operation for Planning of a Complex Water Resources System, Technical Report 122 (UCLA-ENG 67–54), Water Resources Center, School of Engineering and Applied Science, University of California, USA.Google Scholar
Harboe, R. (1987). Application of optimization models to synthetic hydrologic samples. In Proceedings of the International Symposium on Water for the Future, Rome, Italy.Google Scholar
Harboe, R., Gautam, T. R. and Onta, P. R. (1995). Conjunctive operation of hydroelectric and thermal power plants. Water Resources Journal, ST/ESCAP/SER.C/186: 54–63 (reprint from Journal of Water Resources Planning and Management, 120(6), 1994).Google Scholar
Harboe, R. C., Mobasheri, F. and Yeh, W. W-G. (1970). Optimal policy for reservoir operation. Journal of Hydraulic Division, ASCE, 96 (HY11), 2297–2308.Google Scholar
He, Q., Nandalal, K. D. W., Bogardi, J. J. and Milutin, D. (1995). Application of Stochastic Dynamic Programming Models in Optimization of Reservoir Operations: A Study of Algorithmic Aspects. Report 56, Internal Publication Series, Department of Water Resources, Wageningen Agricultural University, the Netherlands.Google Scholar
Heidari, M., Chow, V. T., Kokotovic, P. V. and Meridith, D. D. (1971). Discrete differential dynamic programming approach to water resources systems optimizations. Water Resources Research, 7(2), 273–282.CrossRefGoogle Scholar
Hillier, F. S. and Lieberman, G. J. (1990). Introduction to Operations Research. New York: McGraw-Hill.Google Scholar
Howard, R. A. (1960). Dynamic Programming and Markov Processes. Cambridge, MA, USA: MIT Press.Google Scholar
Huang, W-C. (1989). Multiobjective decision making in the on-line operation of a multipurpose reservoir, Doctoral Dissertation, Asian Institute of Technology, Bangkok, Thailand.
Huang, W.-C., Harboe, R. and Bogardi, J. J. (1991). Testing stochastic dynamic programming models conditioned on observed or forecasted inflows. Journal of Water Resources Planning and Management, 117(1), 28–36.CrossRefGoogle Scholar
Jacoby, H. D. and Loucks, D. P. (1972). Combined use of optimization and simulation models in river basin planning. Water Resources Research, 8(6), 1401–1414.CrossRefGoogle Scholar
Jaworski, N. A., Weber, W. J. and Deininger, R. A. (1970). Optimal reservoir releases for water quality control. Journal of the Sanitary Engineering Division, ASCE, 96(SA3), 727–740.Google Scholar
Johnson, S. A., Stedinger, J. R., Shoemaker, C. A., Li, Y. and Tejada-Guibert, J. A. (1993). Numerical solution of continuous-state dynamic programs using linear and spline interpolation. Operations Research, 41(3), 484–500.CrossRefGoogle Scholar
Karamouz, M. and Houck, M. H. (1982). Annual and monthly reservoir operating rules generated by deterministic optimization. Water Resources Research, 18(5), 1337–1344.CrossRefGoogle Scholar
Karamouz, M. and Houck, M. H. (1987). Comparison of stochastic and deterministic dynamic programming for reservoir operating rule generation. Water Resources Bulletin, 23(1), 1–9.CrossRefGoogle Scholar
Karamouz, M. and Mousavi, S. J. (2003). Uncertainty based operation of large scale reservoir systems: Dez and Karoon experience. Journal of the American Water Resources Association, 39(4), 961–975.CrossRefGoogle Scholar
Karamouz, M. and Vasiliadis, H. V. (1992). Bayesian stochastic optimization of reservoir operation using uncertain forecasts. Water Resources Research, 28(5), 1221–1232.CrossRefGoogle Scholar
Keeney, R. L. and Raiffa, H. (1976). Decisions with Multiple Objectives: Preferences and Value Tradeoffs. New York: John Wiley and Sons.Google Scholar
Kelman, J., Cooper, L. A., Hsu, E. and Yuan, Sun-Quan (1988). The use of probabilistic constraints in reservoir operation policies with sampling stochastic dynamic programming. In Proceedings of the 3rd Water Resources Operations and Management Workshop, Colorado, USA, pp. 1–9.Google Scholar
Kelman, J., Stedinger, J. R., Cooper, L. A., Hsu, E. and Yuan, Sun-Quan (1990). Sampling stochastic dynamic programming applied to reservoir operation. Water Resources Research, 26(3), 447–454.CrossRefGoogle Scholar
Kitanidis, P. K. and Foufoula-Georgiou, E. (1987). Error analysis of conventional discrete and gradient dynamic programming. Water Resources Research, 23(5), 845–858.CrossRefGoogle Scholar
Kularathna, M. D. U. P. (1992). Application of dynamic programming for the analysis of complex water resources systems: a case study on the Mahaweli river basin development in Sri Lanka. Ph.D. Dissertation. Wageningen Agricultural University, the Netherlands.
Kularathna, M. D. U. P. and Bogardi, J. J. (1990). Simplified system configurations for stochastic dynamic programming based optimization of multireservoir systems. Water resources systems application. In Simonovic, S. P.et al. (eds.), Proceedings of the International Symposium on Water Resources Systems Application, University of Manitoba, Canada.Google Scholar
Kumar, D. N. and Baliarsingh, F. (2003). Folded dynamic programming for optimal operation of multireservoir system. Water Resources Management, 17, 337–353.CrossRefGoogle Scholar
Laabs, H. and Harboe, R. (1988). Generation of operating rules with stochastic dynamic programming and multiple objectives. Water Resources Management, 2, 221–227.CrossRefGoogle Scholar
Labadie, J. W. and Fontane, D. G. (1986). Objective space dynamic programming approach to multidimensional problems in water resources. In Esogbue, A. O. (ed.), Proceedings of the Bellman Continuum-Special NSF Workshop on Dynamic Programming and Water Resources, Georgia Institute of Technology, Atlanta, USA.Google Scholar
Lane, W. L. and Frevert, D. K. (1989). Applied Stochastic Techniques, User Manual. Bureau of Reclamation, Engineering Research Center, Denver, Colorado.Google Scholar
Larson, R. E. (1968). State Incremental Dynamic Programming. New York: Elsevier.Google Scholar
Liang, Q., Johnson, L. E. and Yu, Y-S. (1996). A comparison of two methods for multiobjective optimization for reservoir operation. Water Resources Bulletin, 32(2), 333–340.CrossRefGoogle Scholar
Loucks, D. P., Stedinger, J. R. and Haith, D. A. (1981). Water Resources Systems Planning and Analysis. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Loucks, D. P. and van Beek, E. (2005). In Water Resources Systems Planning and Management: An Introduction to Methods, Models and Applications (with contributions from Stedinger, J. R., Dijkman, J. P. M. and Villars, M. T.), Studies and Reports in Hydrology, Paris: UNESCO Publishing.Google Scholar
Maidment, D. R. and Chow, V. T. (1981). Stochastic state variable dynamic programming for reservoir systems analysis. Water Resources Research, 17(6), 1578–1584.CrossRefGoogle Scholar
Matalas, N. C. (1967). Mathematic assessment of synthetic hydrology. Water Resources Research, 3(4), 937–945.CrossRefGoogle Scholar
Mawer, P. A. and Thorn, D. (1974). Improved dynamic programming procedures and their practical application to water resource systems. Water Resources Research, 10(2), 183–190.CrossRefGoogle Scholar
Meier, W. L. and Beightler, C. S. (1967). An optimization method for branching multistage water resources systems, Water Resources Research, 3(9), 645–652.CrossRefGoogle Scholar
Millennium Development Goals (MDGs) (2000). UNITED NATIONS Development Programme (UNDP) Website www.undp.org/mdg/basics.shtml, viewed March 10, 2006.
Millennium Ecosystem Assessment (2005). Ecosystems and Human Well-Being: Current State and Trends. Findings of the Condition and Trends Working Group. Millennium Ecosystem Assessment Series. Washington, DC: Island Press.
Milutin, D. (1998). Multiunit water resource systems management by decomposition, optimization and emulated evolution. Ph.D. Dissertation, Department of Water Resources, Wageningen Agricultural University, the Netherlands.
Mousavi, S. J., Karamouz, M. and Menhadj, M. B. (2004). Fuzzy-state stochastic dynamic programming for reservoir operation. Journal of Water Resources Planning and Management, 130(6), 460–470.CrossRefGoogle Scholar
Murray, D. M. and Yakowitz, S. J. (1979). Constrained differential dynamic programming and its application to multireservoir control. Water Resources Research, 15(5), 1017–1027.CrossRefGoogle Scholar
Nandalal, K. D. W. (1986). Operation policies for two multipurpose reservoirs of the Mahaweli Development Scheme in Sri Lanka. M.Eng. Thesis No.WA-86-9, Asian Institute of Technology, Bangkok, Thailand.
Nandalal, K. D. W. (1995). Reservoir management under consideration of stratification and hydraulic phenomena. Ph.D. Dissertation, Department of Water Resources, Wageningen Agricultural University, the Netherlands.
Nandalal, K. D. W. (1998). The use of optimization techniques in planning and management of complex water resources systems. In Proceedings of the National Conference Status and Future Direction of Water Research in Sri Lanka, pp. 119–129.Google Scholar
Nandalal, K. D. W. and Ampitiya, H. K. (1997). The assessment of long-term operation of multi-unit reservoir systems. Engineer, Journal of the Institution of Engineers, Sri Lanka, 26(2), 16–24.Google Scholar
Nandalal, K. D. W. and Sakthivadivel, R. (2002). Planning and management of a complex water resources system: case study of Samanalawewa and Udawalawe reservoirs in the Walawe river, Sri Lanka. Agricultural Water Management, 57(3), 207–221.CrossRefGoogle Scholar
Nopmongcol, P. and Askew, A. J. (1976). Multi-level incremental dynamic programming. Water Resources Research, 12(6), 1291–1297.CrossRefGoogle Scholar
Opricović, S. and Djordjević, B. (1976). Optimal long-term control of a multipurpose reservoir with indirect users. Water Resources Research, 12(6), 1286–1290.CrossRefGoogle Scholar
Orlob, G. T. and Simonovic, S. P. (1981). Reservoir operation for water quality control. In Proceedings of the International Symposium on Real-Time Operation of Hydrosystems, Waterloo, Ontario, Canada, pp. 599–616.Google Scholar
Palmer, R. N. and Holmes, K. J. (1988). Operational guidance during droughts: expert systems approach. Journal of Water Resources Planning and Management, 114(6), 647–666.CrossRefGoogle Scholar
Phien, H. N. and Ruksasilp, W. (1981). A review of single site models for monthly streamflow generation. Journal of Hydrology, 52, 1–12.CrossRefGoogle Scholar
Randall, D., Houck, M. H. and Wright, J. R. (1990). Drought management of existing water supply system. Journal of Water Resources Planning and Management, 116(1), 1–20.CrossRefGoogle Scholar
Ratnayake, U. R. (1995). Sequential stochastic optimization of a reservoir system. Doctoral Dissertation No. WA 95-2, Asian Institute of Technology, Bangkok, Thailand.
Reznicek, K. K. and Simonovic, S. P. (1990). An improved algorithm for hydropower optimization, Water Resources Research, 26(2), 189–198.CrossRefGoogle Scholar
Reznicek, K. K. and Simonovic, S. P. (1992). Issues in hydropower modeling using the GEMSLP algorithm, Journal of Water Resources Planning and Management, 118(1), 54–70.CrossRefGoogle Scholar
Roefs, T. G. and Bodin, L. D. (1970). Multireservoir operation studies. Water Resources Research, 6(2), 410–420.CrossRefGoogle Scholar
Rogers, D. F., Plante, R. D., Wong, R. T. and Evans, J. R. (1991). Aggregation and disaggregation techniques and methodology in optimization. Operations Research, 39(4), 553–582.CrossRefGoogle Scholar
Saad, M. and Turgeon, A. (1988). Application of principal component analysis to long-term reservoir management. Water Resources Research, 24(7), 907–912.CrossRefGoogle Scholar
Saad, M., Turgeon, A. and Stedinger, J. R. (1992). Censored-data correlation and principal component dynamic programming. Water Resources Research, 28(8), 2135–2140.CrossRefGoogle Scholar
Saad, M., Turgeon, A., Bigras, P. and Duquette, R. (1994). Learning disaggregation technique for the operation of long-term hydroelectric power systems. Water Resources Research, 30(11), 3195–3202.CrossRefGoogle Scholar
Shane, R. M. and Gilbert, K. C. (1982). TVA hydro scheduling model: practical aspects. Journal of Water Resources Planning and Management, 108(1), 21–36.Google Scholar
Shiati, K. (1991). Salinity management in river basins: modelling and management of the salt-affected Jarreh Reservoir. Doctoral Dissertation, Wageningen Agricultural University, the Netherlands.
Shrestha, D. L. (1987). Optimal hydropower system configuration considering operational aspects, M.Eng. Thesis, Asian Institute of Technology, Bangkok, Thailand.
Shrestha, D. L., Bogardi, J. J. and Paudyal, G. N. (1990). Evaluating alternative state space discretization in stochastic dynamic programming for reservoir operation studies. In Simonovic, S. P.et al. (eds.), Proceedings of the International Conference on Water Resources Systems Application, University of Manitoba, Canada, pp. 378–387.Google Scholar
Simonovic, S. P. (2000). A shared vision for management of water resources. Water International, 25(1).CrossRefGoogle Scholar
Simonovic, S. P. and Orlob, G. T. (1981). Optimization of New Melons Reservoir operation for water quality management. In Proceedings of International Conference on Environmental Systems Analysis and Management, International Federation for Information Processing, Rome, Italy.Google Scholar
Simonovic, S. P. and Orlob, G. T. (1984). Risk–reliability programming for optimal water quality control. Water Resources Research, 20(6), 639–646.CrossRefGoogle Scholar
Sinotech Engineering Consultants Inc. (1985). Technical Report of the Operational Rules of Feitsui Reservoir. Sponsored by the Taiwan Power Company.
Stedinger, J. R., Sule, B. F. and Loucks, D. P. (1984). Stochastic dynamic programming models for reservoir operation optimization. Water Resources Research, 20(11), 1499–1505.CrossRefGoogle Scholar
Su, S. Y. and Deininger, R. A. (1974). Modeling the regulation of Lake Superior under uncertainty of future water supplies. Water Resources Research, 10(1), 11–25.CrossRefGoogle Scholar
Tai, F. K. and Goulter, I. C. (1987). A stochastic dynamic programming based approach to the operation of a multireservoir system. Water Resources Bulletin, 23(3), 371–377.CrossRefGoogle Scholar
Takeuchi, K. (2002). Future of reservoirs and their management criteria. In Bogardi, J. J. and Kundzewicz, Z. W. (eds.), Risk, Reliability, Uncertainty, and Robustness of Water Resources Systems, Cambridge, UK: Cambridge University Press, pp. 190–198.CrossRefGoogle Scholar
Teixeira, A. S. and Marino, M. A. (2002). Coupled reservoir operation–irrigation scheduling by dynamic programming. Journal of Irrigation and Drainage Engineering, 128(2), 63–73.CrossRefGoogle Scholar
Tejada-Guibert, J. A., Johnson, S. A. and Stedinger, J. R. (1993). Comparison of two approaches for implementing multireservoir operation policies derived using stochastic dynamic programming. Water Resources Research, 29(12), 3969–3980.CrossRefGoogle Scholar
Tejada-Guibert, J. A., Johnson, S. A. and Stedinger, J. R. (1995). The value of hydrologic information in stochastic dynamic programming models of a multireservoir system. Water Resources Research, 31(10), 2571–2579.CrossRefGoogle Scholar
Thomas, H. A. and Fiering, M. B. (1962). Mathematical synthesis of streamflow sequences for the analysis of river basins by simulation. In Mass, A.et al. (eds.), Design of Water Resources Systems, Cambridge, MA: Harvard University Press, pp. 459–493.CrossRefGoogle Scholar
Tilmant, A., Vanclooster, M., Duckstein, L. and Persoons, E. (2002). Comparison of fuzzy and nonfuzzy optimal reservoir operation policies, Journal of Water Resources Planning and Management, 128(6), 390–398.CrossRefGoogle Scholar
Trott, W. J. and Yeh, W.W-G. (1973). Optimization of multiple reservoir systems. Journal of the Hydraulics Division, ASCE, 99(HY10), 1865–1884.Google Scholar
Turgeon, A. (1980). Optimal operation of multireservoir power systems with stochastic inflows. Water Resources Research, 16(2), 275–283.CrossRefGoogle Scholar
Turgeon, A. (1981). A decomposition method for the long-term scheduling of reservoirs in series. Water Resources Research, 17(6), 1565–1570.CrossRefGoogle Scholar
Turgeon, A. (1982). Incremental dynamic programming may yield nonoptimal solutions. Water Resources Research, 18(6), 1599–1604.CrossRefGoogle Scholar
Umamahesh, N. V. and Chandramouli, S. (2004). Fuzzy dynamic programming model for optimal operation of a multipurpose reservoir. In Herath, S., Pathirana, A. and Weerakoon, S. B. (eds.), Proceedings of the International Conference on Sustainable Water Resources Management in the Changing Environment of the Monsoon Region, Vol. II, November, Sri Lanka, pp. 552–557.Google Scholar
UN (1992). Agenda 21. United Nations Conference on Environment & Development, Rio de Janerio, Brazil, 3 to 14 June 1992. www.un.org/esa/sustdev/documents/agenda21/english/Agenda21.pdf.
Vasiliadis, H. V. and Karamouz, M. (1994). Demand-driven operation of reservoirs using uncertainty-based optimal operation policies. Journal of Water Resources Planning and Management, 120(1), 101–114.CrossRefGoogle Scholar
Vedula, S. and Kumar, D. N. (1996). An integrated model for optimal reservoir operation for irrigation of multiple crops. Water Resources Research, 32(4), 1101–1108.CrossRefGoogle Scholar
Verhaeghe, R. J. and Tholan, N. (1983). Illustrative Examples of Optimization Techniques for Quantitative and Qualitative Water Management. Report on Investigation, Report R999-8. Delft Hydraulics Laboratory, the Netherlands.
WCED (World Commission on Environment and Development) (1987). Our Common Future. New York: Oxford University Press.
World Commission on Dams (2000). Dams and Development: A New Framework for Decision-Making. The Report of the World Commission on Dams. London: Earthscan Publications Ltd.
World Water Assessment Programme (2003). Water for People Water for Life: The United Nations World Water Development Report. UNESCO Publishing and Bernan Association.
WSSD (2002). Johannesburg Plan of Implementation. World Summit on Sustainable Development, August 26–September 4, 2002, Johannesburg, South Africa. www.un.org/esa/sustdev/documents/WSSD_POI_PD/English/WSSD_PlanImpl.pdf.
Wurbs, R. A. (1993). Reservoir-system simulation and optimization models. Journal of Water Resources Planning and Management, 119(4), 455–472.CrossRefGoogle Scholar
Yakowitz, S. (1982). Dynamic programming applications in water resources. Water Resources Research, 18(4), 673–696.CrossRefGoogle Scholar
Yeh, W. W-G. (1985). Reservoir management and operation models: a state-of-the-art review. Water Resources Research, 21(12), 1797–1818.CrossRefGoogle Scholar
Yekom Consulting Engineers (1980). Shapur and Dalaki Project Feasibility Report, Jarreh Storage Dam. Vol.1: Engineering.
Young, G. K. (1967). Finding reservoir operation rules. Journal of the Hydraulics Division, ASCE, 93(HY6), 297–321.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • References
  • K. D. W. Nandalal, University of Peradeniya, Sri Lanka, Janos J. Bogardi
  • Book: Dynamic Programming Based Operation of Reservoirs
  • Online publication: 14 August 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511535710.008
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • K. D. W. Nandalal, University of Peradeniya, Sri Lanka, Janos J. Bogardi
  • Book: Dynamic Programming Based Operation of Reservoirs
  • Online publication: 14 August 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511535710.008
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • K. D. W. Nandalal, University of Peradeniya, Sri Lanka, Janos J. Bogardi
  • Book: Dynamic Programming Based Operation of Reservoirs
  • Online publication: 14 August 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511535710.008
Available formats
×