Optimization of Reservoir Operation for Real-Time Flood Control with Emphasis on Forecast Uncertainty: A case study of Dez Reservoir

Document Type : Research Paper


1 Department of hydrology and water resources, Faculty of Water Science Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

2 Faculty of Water Science and Engineering, Shahid Chamran University, Ahvaz, Iran

3 School of Computing, Electronic and Mathematics, Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK


This study presents a novel approach for real-time flood control by optimizing operation of a reservoir during the flood. However, the fundamental operational challenge of using this method is to determine optimized decisions of the reservoir management before the occurrence of flood, and optimal use of the pre-release to reduce the flood damages. In addition to this optimization challenge, since the timely forecasts are derived by employing the probabilistic methods, they would always associate with uncertainty. As a result, quantifying and considering these uncertainties in the flood control would result in reducing the risk of flood damage that can be evaluated by minimizing the expected value of the damage. Timely and continuous forecasting of inflow and reservoir operation management will be implemented before the occurrence of flood until it ends. In order to address the above challenges, a novel simulation-optimization methodology, by taking into account uncertainty, is developed; and illustrated on a case study of Dez reservoir, as a highly important reservoir system in south-west of Iran, to optimize the performance of this reservoir, during the floods. Accordingly, a new water resource management has been proposed and tested. The results derived from the proposed method, indicate a significant reduction in the peak release from the reservoir and the improved operation of the Dez reservoir in controlling the flood at real-time, which will reduce damages in the downstream area.


  1. Basirzadeh, H. “Real Time Optimization Flood Control in Reservoir, Case Study: Karkheh Dam Reservoir”, Report of Research Project in Khuzestan Water and Power Authority, 2006.
  2. Acanal, N., & Haktanir, T. “Five stage flood routing for gated reservoirs by grouping floods into five different categories according to their return periods”, Hydrological Sciences Journal, 1999, 44(2), 163–172.
  3. Haktanir, T., Citakoglu, H. & Acanal, N. . “Fifteen-stage operation of gated spillways for flood routing management through artificial reservoirs”, Hydrological Sciences Journal, 2013, 58(5), 1013-1031.
  4. Karbowski, A., Malinowski, K., & Niewiadomska-Szynkiewicz, E., “A hybrid analytic/ rule-based approach to reservoir system management during flood” www.elsevier.com/locate/dsw, Decision Support Systems, 2005, 38, 599– 610.
  5. Samani, H. M. V., & Rezazadeh, K. “ Flood Control by Dam Reservoirs and Optimization of Gated Spillways Operation, Case Study: Karun and Dez Dam System” Report of Research Project in Khuzestan Water and Power Authority, 2004, No. 81407.84
  6. Zargar, M. , Samani, H. M. V., & Hghighi, A., “Optimization of Gated Spillways Operation for Flood Risk Management in Multi-Reservoir Systems”, Natural Hazards, 2016, 82,299–320.
  7. Malekmohammadi, B., “The Optimization Model of Reservoir Operation Based on Flood Risk Management”, Water Resources Regional Conference, (Isfahan 2006).
  8. Yimeng, S. & Fei-lin, Z., Juan C. & Jinshu, Li. “Risk analysis for reservoir real-time optimal operation using the scenario tree-based stochastic optimization method”, Water 2018, 10(5):606.
  9. Salarijazi, M., Akhondali, A. M., Adib, A. & Daneshkhah, A.. "Bivariate Flood Frequency Analysis Using the Copula Functions." 2015, 29-38.
  10. Daneshkhah, A., Remesan, R., Chatrabgoun, O., & Holman, I. P. "Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model." Journal of Hydrology, 2016, 540: 469-487.
  11. Bedford, T., Wilson, K. J., & Daneshkhah, A. “Assessing parameter uncertainty on coupled models using minimum information methods”, Reliability Engineering & System Safety, 2014, 125, 3-12.
  12. Daneshkhah, Alireza, Golamali Parham, Omid Chatrabgoun, and M. Jokar. "Approximation multivariate distribution with pair copula using the orthonormal polynomial and Legendre multiwavelets basis functions." Communications in Statistics-Simulation and Computation, 2016, 45 (2) : 389-419.
  13. Daneshkhah, A., & Bedford, T. “Sensitivity analysis of a reliability system using Gaussian processes”, Advances in mathematical modeling for reliability, 2008, 46-54.
  14. Daneshkhah A, Hosseinian-Far A, Chatrabgoun O. “Sustainable maintenance strategy under uncertainty in the lifetime distribution of deteriorating assets”. In Strategic Engineering for Cloud Computing and Big Data Analytics 2017 (pp. 29-50). Springer, Cham.
  15. Beven, K. J. & Freer, J . “Equifinality, data assimilation and uncertainty estimation in mechanistic modeling of complex environmental systems using the GLUE methodology” Journal of Hydrology, 2001, 249, 11.29
  16. Bianucci, P., Sordo-Ward, A. J.I.Perez, J.I., Garcia-Palacios, J. & Garrote, G. “Risk-based methodology for parameter calibration of a reservoir flood control model”, Natural Hazards and Earth System Sciences, 2013, 13, 965-981.
  17. Juan Chen, P., Man-lin, W., & Fei lin, Z.u, , “A risk- based model for real-time flood control operation of a cascade reservoir system under emergency conditions”, Water 2018,10,167
  18. Yu-Wen, Ch., Jui-Pin, T., and Liang-Cheng, Ch., , “The development of a real-time flooding operation modelin the Tseng-Wen Reservoir”, Hydrology Research, 2014, 45.3, 490
  19. Malde, S. Wyncoll, D., Oakley, J., Tozer, N., & Gouldby, B. “Applying emulators for improved flood risk analysis”, Flood Risk 2016- 3rd European Conference on Flood Risk Management.
  20. Myo Lin N, Tian X, Rutten M, Abraham E, Maestre JM, van de Giesen N. “Multi-Objective Model Predictive Control for Real-Time Operation of a Multi-Reservoir System”. Water. 2020 :12(7):1898.
  21. Cuevas-V., Sordo-Ward A., H.García-Palacios J., Bianucci P., Garrote L. .“ Probabilistic Model for Real-Time Flood Operation of a Dam Based on a Deterministic Optimization Model”, Water 2020, 12, 3206.
  22. Zhang J, Cai X, Lei X, Liu P, Wang H. Real-time reservoir flood control operation enhanced by data assimilation. Hydrology and Earth System Sciences Discussions. 2020 Jul 27:1-37.
  23. Smith J. Q., & Daneshkhah A. On the robustness of Bayesian networks to learning from non-conjugate sampling. International Journal of Approximate Reasoning. 2010 1;51(5):558-72.