Abstract
This paper presents a novel approach to real time automatic flood control in a managed river network that is subject to uncertain inflows. The proposed approach uses multiple models to represent inflows ranging from low to high flow. Optimal model selection is achieved in a minimum mean square error sense using a bank of Kalman filters to identify the most likely inflow characteristic. There are no a-priori probabilities assigned to the individual models. Model Predictive Control is used for water level controller design. Our Adaptive Multi Model Predictive Control (AMMPC) method is proposed as an alternative to existing techniques that also use multiple inflow models but with a-priori inflow model probabilities, either weighted or equally likely. The performance of the approach is demonstrated using a simulated river-reservoir model as well as using data collected at the Wivenhoe Dam during the 2011 floods in Queensland, Australia.
Similar content being viewed by others
References
Aldrighetti E (2007) Computational hydraulic techniques for the Saint Venant equations in arbitrarily shaped geometry. PhD thesis, University of Trento, Italy
Athans M, Castagon D, Dunn KP, Greene CS, Lee WH, Sandell NR, Willsky AS (1977) The stochastic control of the f-8c aircraft using a multiple model adaptive control (MMAC) method—part I: equilibrium flight. IEEE Trans Automat Contr AC-22(5):768–779
Blanco TB, Willems P, Moor BD, Berlamont J (2007) Flood prevention of the Demer using model predictive control. In: 17th IFAC world congress
Blanco TB, Willems P, Chiang PK, Haverbeke N, Berlamont J, Moor BD (2010) Flood regulation using nonlinear model predictive control. Control Eng Pract 18:1147–1157
Block PJ, Filho FAS, Sun L, Kwon HH (2009) A streamflow forecasting framework using multiple climate and hydrological models. J Am Water Resour Assoc 45:828–843
Breckpot M, Blanco TB, Moor BD (2010a) Flood control of rivers with model predictive control. In: American control conference
Breckpot M, Blanco TB, Moor BD (2010b) Flood control of rivers with nonlinear model predictive control and moving horizon estimation. In: 49th IEEE conference on decision and control (CDC)
Burt CM, Mills RS, Khalsa RD, Ruiz CV (1998) Improved proportional-integral (pi) logic for canal automation. J Irrig Drain Eng 124:53–57
Chaudhry MH (2008) Open channel flow. Springer, Berlin
Cheng C, Wang W, Xu D-m, Chau K (2008) Optimizing hydropower reservoir operation using hybrid genetic algorithm and chaos. Water Resour Manag 22:895–909
Chowdhury S, Sharma A (2009) Multisite seasonal forecast of arid river flows using a dynamic model combination approach. Water Resour Res 45:1–16
Devineni N, Sankarasubramanian A, Ghosh S (2008) Multimodel ensembles of streamflow forecasts: role of predictor state in developing optimal combinations. Water Resour Res 44:1–22
Ekeren HV, Negenborn R, Overloop PV, Schutter BD (2010) Hybrid model predictive control using time-instant optimization for the Rhine–Meuse Delta. Tech. rep., Delft Center for Systems and Control
Evans R, Li L, Mareels I, Okello N, Pham M, Qiu W, Saleem SK (2011) Real-time optimal control of river basin networks. In: Preprints of the 18th IFAC world congress
Foo MFL (2012) Modelling and control design of river systems. PhD thesis, National ICT Australia, Department of Electrical and Electronic Engineering, The University of Melbourne
Foo M, Bedjaoui N, Weyer E (2010a) Segmentation of a river using the saint venant equations. In: 2010 IEEE international conference control applications (CCA)
Foo M, Ooi SK, Weyer E (2010b) Modelling of river for control design. In: IEEE international conference on control applications—part of 2010 IEEE multi-conference on systems and control
Fu G, Butler D, Khu ST (2008a) Comparison of control strategies for multiobjective control of urban wastewater systems. In: 4th biennial meeting of iEMSs proceedings: international congress on environmental modelling and software. International Environmental Modelling and Software Society, pp 1347–1352
Fu G, Butler D, Khu ST (2008b) Multiple objective optimal control of integrated urban wastewater systems. Environ Model Softw 23(2):225–234
Gomez M, Rodellar J, Mantecon JA (2002) Predictive control method for decentralized operation of irrigation canals. Appl Math Model 26:1039–1056
Government of India Central Water Commission (2005) Real time integrated operation of reservoirs—reservoir operation directorate
Jakeman AJ, Hornberger GM (1993) How much complexity is warranted in a rainfall-runoff model? Water Resour Res 29:2637–2649
Kearney M, Dower PM, Cantoni M (2011) Model predictive control for flood mitigation: a Wivenhoe dam case study. In: Australian control conference
Lakshmanan V, Gourley JJ, Flamig Z, Giangrande S (2009) A simple data-driven model for streamflow prediction. In: AMS annual meeting, Phoenix
Li L, Okello N, Pham M, Saleem SK, Qiu W, Evans R, Mareels I (2011) Model predictive control of murray-darling basin networks. In: Control and decision conference
Marinaki M, Papageorgiou M (2005) Optimal real time control of sewer networks. Springer, New York
Ooi SK, Weyer E (2001) Closed loop identification of an irrigation channel. In: Proceedings of the 40th IEEE conference on decision and control
Ooi SK, Weyer E (2008a) Control design for an irrigation channel from physical data. Control Eng Pract 16:1132–1150
Ooi SK, Weyer E (2008b) Control design for an irrigation channel from physical data. Control Eng Pract 16:1132–1150
Overloop PJV, Weijs S, Dijkstra S (2008) Multiple model predictive control on a drainage canal system. Control Eng Pract 16(5):531–540
Puig V, Cembrano G, Romera J, Quevedo J, Aznar B, Ramon G, Cabot J (2009) Predictive optimal control of sewer networks using coral tool: application to Riera Blanca catchment in Barcelona. Water Sci Technol 60:869–878
Puig V, Romera J, Quevedo J, Cardona CM, Salterain A, Ayesa E, Irizar I, Castro A, Lujan M, Charbonnaud P, Chiron P, Trouvat JL (2011) Optimal predictive control of water transport systems: Arrêt-darré/arros case study. Water Sci Technol 60:2125–2133
Ruiz VM, Ramirez LJ (1998) Predictive control in irrigation canal operation. In: IEEE international conference on systems, man, and cybernetics
Schuurmans J, Schuunnans W, Berger H, Meulenberg M, Brouwe R (1997) Control of water levels in the meuse river. J Irrig Drain Eng 123:180–184
SEQwater (2011a) January 2011 flood event-report on the operation of Somerset Dam and Wivenhoe Dam. Tech. rep., SEQwater
SEQwater (2011b) Manual of operational procedures for flood mitigation at Wivenhoe Dam and Somerset Dam
Wang L (2009) Model predictive control system design and implementation using Matlab, 1 edn. Springer-Verlag London Limited
Wang D, Salas J (1991) Forecasting streamflow for colorado river systems. Tech. rep., Colarado Water Resouces Research Institute
Wang L, Young PC (2005) Model predictive control design using non-minimal state space model. In: IFAC
Weyer E (2001) System identication of an open water channel. Control Eng Pract 9:1289–1299
Weyer E (2008) Control of irrigation channels. IEEE Trans Control Syst Technol 16:664–675
Wu CL, Chau K (2010) Data driven models for monthly streamflow time series predic. Eng Appl Artif Intell 23:1350–1367
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Delgoda, D.K., Saleem, S.K., Halgamuge, M.N. et al. Multiple Model Predictive Flood Control in Regulated River Systems with Uncertain Inflows. Water Resour Manage 27, 765–790 (2013). https://doi.org/10.1007/s11269-012-0214-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-012-0214-y