Technical Papers
Jan 18, 2013

Planning the Optimal Operation of a Multioutlet Water Reservoir with Water Quality and Quantity Targets

Publication: Journal of Water Resources Planning and Management
Volume 140, Issue 4

Abstract

The integration of quality and quantity issues in the management of water resources systems is key to meet society’s long-term needs for freshwater while maintaining essential ecological services and economic benefits. Current water management practices are mostly targeted towards quantitative uses, and quality is usually addressed separately as an independent problem. One of the reasons for the lack of integration lies in the inadequacy of optimization techniques nowadays available to cope with the large, distributed, simulation models adopted to characterize the coupled ecological and biochemical processes in water bodies. In this paper we propose a novel approach based on the conjunctive use of a batch-mode Reinforcement Learning algorithm and a one-dimensional (1D) coupled hydrodynamic-ecological model to design the optimal operation of a multipurpose water reservoir accounting for both quantity and quality targets. We consider up to five operating objectives, including both in-reservoir and downstream water quality parameters, and design efficient operating policies conditioned upon not only the current storage but also water characteristics, such as temperature and total suspended solids at different depths. The approach is applied to a real world case study in Japan consisting of a water reservoir, Tono Dam, equipped with a selective withdrawal structure and used for flood protection, irrigation and recreational purposes. Results show that a potential control over in-reservoir and downstream water quality can be gained without impairing the hydraulic capacity of the reservoir by effectively exploiting—through the operating policy—the operational flexibility provided by the selective withdrawal structures.

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Acknowledgments

The work was funded by the Tono Dam construction office, Japan Ministry of Land, Infrastructure, Transport and Tourism. Matteo Giuliani was partially supported by Fondazione Fratelli Confalonieri. The authors would like to thank Giovanni Garbarini and Alessandra Galli for their contribution in developing the numerical analysis. This paper forms CWR reference 2648 AC.

References

Baltar, A., and Fontane, D. (2008). “Use of multiobjective particle swarm optimization in water resources management.” J. Water Resour. Plann. Manage., 257–265.
Bohan, J., and Grace, J. (1973). “Selective withdrawal from man-made lakes.”, U.S. Army Corps of Engineers, Waterways Experiment Station, Vicksburg, MS.
Castelletti, A., Antenucci, J. P., Limosani, D., Quach Thi, X., and Soncini-Sessa, R. (2011). “Interactive response surface approaches using computationally intensive models for multiobjective planning of lake water quality remediation.” Water Resour. Res., 47(9), W09534.
Castelletti, A., Galelli, S., Ratto, M., Soncini-Sessa, R., and Young, P. C. (2012). “A general framework for dynamic emulation modelling in environmental problems.” Environ. Modell. Software, 34, 5–18.
Castelletti, A., Galelli, S., Restelli, M., and Soncini-Sessa, R. (2010). “Tree-based reinforcement learning for optimal water reservoir operation.” Water Resour. Res., 46(9), W09507.
Castelletti, A., Pianosi, F., and Soncini-Sessa, R. (2008). “Water reservoir control under economic, social and environmental constraints.” Automatica, 44(6), 1595–1607.
Chaves, P., and Kojiri, T. (2007). “Deriving reservoir operational strategies considering water quantity and quality objectives by stochastic fuzzy neural networks.” Adv. Water Resour., 30(5), 1329–1341.
Dandy, G., and Crawley, P. (1992). “Optimum operation of a multiple reservoir system including salinity effects.” Water Resour. Res., 28(4), 979–990.
Davis, J., Holland, J., Schneider, M., and Wilhelms, S. (1987). “SELECT: A numerical, one-dimensional model for selective withdrawal.”, U.S. Army Corps of Engineers, Waterways Experiment Station, Vicksburg, MS.
Dhar, A., and Datta, B. (2008). “Optimal operation of reservoirs for downstream water quality control using linked simulation optimization.” Hydrol. Process., 22(6), 842–853.
Dortch, M. (1997). “Water quality considerations in reservoir management.” Water Resour. Update, 108, 32–42.
Ernst, D., Geurts, P., and Wehenkel, L. (2005). “Tree-Based batch mode reinforcement learning.” J. Machine Learn. Res., 6, 503–556.
Evans, R. (1994). “Empirical evidence of the importance of sediment resuspension.” Hydrobiologia, 284(1), 5–12.
Ferris, J., and Lehman, J. (2007). “Interannual variation in diatom bloom dynamics: Roles of hydrology, nutrient limitation, sinking, and whole lake manipulation.” Water Res., 41(12), 2551–2562.
Fontane, D., Labadie, J., and Loftis, B. (1981). “Optimal control of reservoir discharge quality through selective withdrawal.” Water Resour. Res., 17(6), 1594–1604.
Galelli, S., Giuliani, M., and Soncini-Sessa, R. (2011). “Dealing with many-criteria problems in water resources planning and management.” 18th IFAC World Congress, International Federation of Automatic Control (IFAC), Vienna, Austria.
Gelda, R., and Effler, S. (2007). “Simulation of operations and water quality performance of reservoir multilevel intake configurations.” J. Water Resour. Plann. Manage., 78–86.
Geurts, P., Ernst, D., and Wehenkel, L. (2006). “Extremely randomized trees.” Mach. Learn., 63(1), 3–42.
Hanna, R. B., and Saito, L. (2001). “Simulated limnological effects of the Shasta Lake temperature control device.” Environ. Manage., 27(4), 609–626.
Hanna, R. B., Saito, L., Bartholow, J. M., and Sandelin, J. (1999). “Results of simulated temperature control device operations on in-reservoir and discharge water temperatures using CE-QUAL-W2.” Lake Reservoir Manage., 15(2), 87–102.
Hashimoto, T., Stedinger, J., and Loucks, D. (1982). “Reliability, resilience, and vulnerability criteria for water resource system performance evaluation.” Water Resour. Res., 18(1), 14–20.
Hayes, D., Labadie, J., Sanders, T., and Brown, J. (1998). “Enhancing water quality in hydropower system operations.” Water Resour. Res., 34(3), 471–483.
Hipsey, M., Romero, J., Antenucci, J., and Hamilton, D. (2006). “Computational aquatic ecosystem dynamics model: CAEDYM, v 2.3 science manual.” Centre for Water Research, Univ. of Western Australia, Crawley, WA.
Hodges, B., and Dallimore, C. (2001). “Estuary and lake computer model, ELCOM, science manual, code version 1.5.0.” Centre for Water Research, Univ. of Western Australia, Crawley, WA.
Huang, Y., Huang, G., Liu, D., Zhu, H., and Sun, W. (2012). “Simulation-based inexact chance-constrained nonlinear programming for eutrophication management in the Xiangxi Bay of Three Gorges Reservoir.” J. Environ. Manage., 108, 54–65.
Ikebuchi, S., and Kojiri, T. (1992). “Multiobjective reservoir operation including turbidity control.” Water Resour. Bull., 28(1), 223–231.
International Lake Environment Committee (ILEC). (2005). Managing lakes and their basins for sustainable use: A report for lake basin managers and staleholders, Kusatsu, Japan.
Imerito, A. (2007). “Dynamic reservoir simulation model: DYRESM science manual.” Centre for Water Research, Univ. of Western Australia, Crawley, WA.
Kerachian, R., and Karamouz, M. (2006). “Optimal reservoir operation considering the water quality issues: A stochastic conflict resolution approach.” Water Resour. Res., 42(12), W12401.
Khan, N., Babel, M., Tingsanchali, T., Clemente, R., and Luong, H. (2012). “Reservoir optimization-simulation with a sediment evacuation model to minimize irrigation deficits.” Water Resour. Manage., 26(11), 3173–3193.
Kollat, J., and Reed, P. (2007). “A framework for visually interactive decision-making and design using evolutionary multi-objective optimization (VIDEO).” Environ. Modell. Software, 22(12), 1691–1704.
Koutsoyiannis, D., and Economou, A. (2003). “Evaluation of the parameterization-simulation-optimization approach for the control of reservoir systems.” Water Resour. Res., 39(6), 1170–1187.
Kuo, J., Hsieh, P., and Jou, W. (2008). “Lake eutrophication management modeling using dynamic programming.” J. Environ. Manage., 88(4), 677–687.
Labadie, J. (2004). “Optimal operation of multireservoir systems: State-of-the-art review.” J. Water Resour. Plann. Manage., 93–111.
Lee, C., and Guy, F. (2013). “Assessing the potential of reservoir outflow management to reduce sedimentation using continuous turbidity monitoring and reservoir modelling.” Hydrol. Process., 27(10), 1426–1439.
Nandalal, K., and Bogardi, J. (1995). “Optimal operation of a reservoir for quality-control using inflows and outflows.” Water Science Technol., 31(8), 273–280.
Nece, R. (1970). “Register of selective withdrawal works in United States.” J. Hydraul. Div., 96(9), 1841–1872.
Orlob, G., and Simonovic, S. (1982). “Reservoir operation for water quality control.” Experience in operation of hydrosystems, T. Unny and E. McBean, eds., Water Resources Publications, Littleton, CO, 263–285.
Ostfeld, A., and Salomons, S. (2005). “A hybrid genetic-instance based learning algorithm for CE-QUAL-W2 calibration.” J. Hydrol., 310(1–4), 122–142.
Powell, W. (2007). Approximate dynamic programming: Solving the curses of dimensionality, Wiley, Hoboken, NJ.
Rachelson, E., Schnitzler, F., Wehenkel, L., and Ernst, D. (2011). “Optimal sample selection for batch-mode reinforcement learning.” Proc., 3rd Int. Conf. on Agents and Artificial Intelligence (ICAART 2011), Institute for Systems and Technologies of Information Control and Communication, Setubal, Portugal.
Sherman, B. (2000). “Scoping options for mitigating cold water discharges from dams.”, CSIRO Land and Water, Canberra, Australia.
Smith, D., Wilhelms, S., Holland, J., Dortch, M., and Davis, J. (1987). “Improved description of selective withdrawal through point sinks.”, U.S. Army Corps of Engineers, Waterways Experiment Station, Vicksburg, MS.
Tsitsiklis, J., and Van Roy, B. (1996). “Feature-Based methods for large scale dynamic programming.” Mach. Learn., 22(1–3), 59–94.
Vermeyen, T. (1999). “Summary of the Shasta dam temperature control device and how it is working.” Water Operat. Maintain. Bull., 187, 9–17.
Vermeyen, T., DeMoyer, C., Delzer, W., and Kubly, D. (2003). “A survey of selective withdrawal systems.”, Water Resources Services, Water Resources Research Laboratory, U.S. Bureau of Reclamation, Denver.
Westphal, K., Vogel, R., Kirshen, P., and Chapra, S. (2003). “Decision support system for adaptive water supply management.” J. Water Resour. Plann. Manage., 165–177.
Yajima, H., Kikkawa, S., and Ishiguro, J. (2006). “Effect of selective withdrawal system operation on the long-and short-term water conservation in a reservoir.” Ann. J. Hydraul. Eng., 50, 1375–1380 (in Japanese).

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Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 140Issue 4April 2014
Pages: 496 - 510

History

Received: Jul 31, 2012
Accepted: Jan 16, 2013
Published online: Jan 18, 2013
Discussion open until: Jun 18, 2013
Published in print: Apr 1, 2014

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Authors

Affiliations

Andrea Castelletti [email protected]
M.ASCE
Assistant Professor, Dept. Electronics, Information, and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci, 32, 20133 Milano, Italy; and Adjunct Professor, Centre for Water Research, Univ. of Western Australia, Crawley 6009, Australia (corresponding author). E-mail: [email protected]
Hiroshi Yajima
Associate Professor, Dept. Management of Social Systems and Civil Engineering, Tottori Univ., Koyama, Tottori 680-8552, Japan; and Adjunct Senior Research Fellow, Centre for Water Research, Univ. of Western Australia, Crawley 6009, Australia.
Matteo Giuliani
Ph.D. Student, Dept. Electronics, Information, and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci, 32, 20133 Milano, Italy.
Rodolfo Soncini-Sessa
Professor, Dept. Electronics, Information, and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci, 32, 20133 Milano, Italy.
Enrico Weber
Research Associate, Dept. Electronics, Information, and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci, 32, 20133 Milano, Italy.

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