Multi-objective Optimization of Water Resource Systems of Jarreh and Marun Dams Using NSGA-II Algorithm

Document Type : Research Paper


1 Former M. Sc. Student of Irrigation and Drainage, Department of Water Engineering, Razi University, Kermanshah, Iran

2 Associate Professor, Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran


Irregular withdrawals from water resources followed by the increase of the area of under cultivation lands and the construction of Marun and Jarahi Dams on upstream rivers of the Shadegan Wetland have led to severe hydrological changes as well as increased salinity of the wetland inflow in some periods. The aim of this study is to develop a simulator-optimizer coupling model for proper planning and management of resource allocation to the upstream of Shadegan Wetland. In addition to maximizing the supply of basin demands during the operation period, this model tries to decrease the salinity of inflow to Shadegan Wetland. Due to the importance of the wetland as a seasonal habitat for birds and also one of the important tourist attractions and Importance of Protecting the Ecosystem, the development of a quantitative-qualitative optimization model for optimal use of available water resources is the aim of this study. First, based on current conditions, the prepared model is developed as a reference scenario for a future 30-year period (2021 to 2050). To achieve the best system efficiency in terms of quality and quantity, the optimization is performed by means of the NSGA-II algorithm. The results indicate that the optimizer model performs appropriately in supplying various demands and also decreasing the salinity of the inflow to Shadegan Wetland compared to the reference scenario so that in addition to supplying the demands with more than 92% reliability in the whole system, it is expected that the salinity of the river at the entrance to Shadegan Wetland to be reduced by about 50%., especially in low water months. The coupling model proposed in this research is applicable for other study areas with quantitative-qualitative exploitation approach and is able to detect critical points of rivers in terms of quantity and quality. This model has also the capability of providing optimal solutions for improving river conditions as well as downstream ecosystems.


1. آذری آ. آخوندعلی ع.م. رادمنش ف. و حقیقی ع. (1393) مدیریت کیفیت و آلودگی رودخانه در شرایط بهره‌برداری تلفیقی منابع آب سطحی و زیرزمینی (بازه سد دز تا بند قیر). هفتمین همایش ملی و نمایشگاه تخصصی مهندسی محیط زیست، دانشگاه تهران، تهران، ایران.
2. اکبرپور م. ابراهیمی ک. و هورفر ع. (۱۳۹۲) بهره‌برداری تلفیقی از منابع آب سطحی و زیرزمینی با رویکرد کمی و کیفی (مطالعه موردی دشت یزد- اردکان). پنجمین کنفرانس مدیریت منابع آب ایران، تهران، انجمن علوم و مهندسی منابع آب ایران، دانشگاه شهید بهشتی، تهران، ایران.
3. بازرگان لاری م. کراچیان ر. صدقی ح. فلاح نیا م. عابد علم دوست ا. و نیکو، م. (1389). تدوین قوانین احتمالاتی برای بهره‌برداری بهینه کمی- کیفی از منابع آب سطحی و زیرزمینی در زمان واقعی (کاربرد ماشین‌های بردار پشتیبان). آب و فاضلاب. (4) 21: 69-54.
4. رضوی طوسی س.ل. و محمدولی سامانی ج. (1392) اولویت‌بندی مدیریتی تعدادی از حوضه‌های آبریز کشور با استفاده از روش‌های فرایند تحلیل شبکه‌ای (ANP) و الگوریتم ترکیبی جدید براساس ANP-TOPSIS فازی. مدیریت آب و آبیاری، (2) 3: 75-90.
5. غزالی م. روزبهانی ع. هنر ت. و محمدی ف. (1394) اولویت‌بندی سناریوهای تخصیص آب سد زاینده رود به مصرف‌کنندگان مختلف؛ با رویکرد مدل‌های خبرۀ تصمیم‌گیری چند شاخصه. مدیریت آب و آبیاری، (1) 5: 97-113.
6. مهر آذر آ. مساح بوانی ع. مشعل م. و رحیمی خوب ح. (1395) مدل‎سازی یکپارچة سیستم‎های منابع آب، کشاورزی و اقتصادی-اجتماعی دشت هشتگرد با رویکرد دینامیک سیستم‎ها. مدیریت آب و آبیاری، (2) 6: 263-280.
7. Ahmadianfar, I., Adib, A., & Salarijazi, M. (2015). Optimizing multireservoir operation: hybrid of bat algorithm and differential evolution. Journal of Water Resources Planning and Management. 142 (2): 50150-10.
8. Arthington, A., Stuart, B., Robert, J. N., & LeRoy, P. (2006). The Challenge of Providing Environmental Flow Rules to Sustain River Ecosystems. Ecological Applications. 16: 1311-18.
9. Azari, A., Hamzeh, S., & Naderi, S. (2018). Multi-Objective Optimization of the Reservoir System Operation by Using the Hedging Policy. Water Resources Management. 32 (6): 2061-78.
10. Cai, W., Zhang, L., Zhu, X., Zhang, A., Yin, Y., & Wang, H. (2013). Optimized Reservoir Operation to Balance Human and Environmental Requirements: A Case Study for the Three Gorges and Gezhouba Dams, Yangtze River Basin, China. Ecological Informatics. 18: 40-48.
11. Cardwell, H., Jager, H. I. & Sale, M.J. (1996). Designing Instream Flows to Satisfy Fish and Human Water Needs. Water Resources Planning and Management. 22 (5): 356-363.
12. Carpitella, S., Brentan, B., Montalvo, I., Izquierdo, J., & Certa, A. (2019). Multi-criteria analysis applied to multi-objective optimal pump scheduling in water systems. Water Supply. 19 (8): 2338-2346.
13. Chen, D., Chen, Q., Leon, A. S., & Li, R. (2016). A Genetic Algorithm Parallel Strategy for Optimizing the Operation of Reservoir with Multiple Eco-Environmental Objectives. Water Resources Management. 30 (7): 2127-2142.
14. Chen, Q., Chen, D., Han, R., Li, R., Ma, J., & Blanckaert, K. (2012). Optimizing the Operation of the Qingshitan Reservoir in the Lijiang River for Multiple Human Interests and Quasi-Natural Flow Maintenance. Environmental Sciences. 24 (11): 1923-28.
15. Chen, D., Huang, G., Chen, Q., & Jin, F. (2010). Implementing Eco-Friendly Reservoir Operation by Using Genetic Algorithm with Dynamic Mutation. International Conference on Intelligent Computing for Sustainable Energy and Environment, International Conference on Life System Modeling and Simulation, Heidelberg, Berlin, 509-516.
16. Homa, E. S., Vogel, R. M., Smith, M. P., Apse, C. D., Huber-Lee, A., & Sieber, J. (2005). An Optimization Approach for Balancing Human and Ecological Flow Needs. World Water and Environmental Resources Congress., 1-12.
17. Hu, M., Huang, G. H., Sun, W., Ding, X., Li, Y. P., & Fan, B. (2016). Optimization and Evaluation of Environmental Operations for Three Gorges Reservoir. Water Resources Management. 30 (10): 3553-76.
18. Jackson, R. B., Carpenter, S. R., Dahm, C. N., Mcknight, D. M., Naiman, R. J., Postel, S. L., & Running, S. W. (2001). Water in a Changing World. Ecological Applications. 10 (3): 689-710.
19. Jager, H. I., & Smith, B. T. (2008). Sustainable Reservoir Operation: Can We Genarate Hydropower And Preserve Ecosystem Values. River Research and Applications. 24 (3): 340-352.
20. King, J., Brown, C., & Sabet, H. (2003). A Scenario-Based Holistic Approach to Environmental Flow Assessments for Rivers. River Research and Applications. 19 (5-6): 619-39.
21. LeRoy, P. N., Allan, J. D., Bain, M. B., Karr, J. R., Prestegaard, K. L., Richter, B. D., Sparks, R. E., & Stromberg, J. C. (1997). The Natural Flow Regime A Paradigm for River Conservation and Restoration. BioScience. 47 (11): 769-784.
22. Li, R., Chen, Q., & Duan, C. (2011). Ecological Hydrograph Based on Schizothorax Chongi Habitat Conservation in the Dewatered River Channel between Jinping Cascaded Dams. Science China Technological Sciences. 54 (S1): 54-63.
23. Luo, J., Chen, C., & Xie, J. (2014). Multi-Objective Immune Algorithm with Preference-Based Selection for Reservoir Flood Control Operation. Water Resources Management. 29 (5): 1447-1466.
24. Mao, J., Zhang, P., Dai, L., Dai, H., & Hu, T. (2016). Optimal Opeartion of a Multi-Reservoir System for Environmental Water Demand of a River-Connected Lake. Hydrology Research. 47 (S1): 206-224.
25. Nikolic, V. V., & Simonovic, S. P. (2015). Multi-Method Modeling Framework for Support of Integrated Water Resources Management. Environmental Processes. 2(3): 461-483.
26. Rafiee Anzab, N., Mousavi, S.J., Rousta, B.A., & Kim, J.H. (2016). Simulation Optimization for Optimal Sizing of Water Transfer Systems. In: Proceedings of the 2nd International Conference on Harmony Search Algorithm (ICHSA2015). 382: 365-375.
27. Shiau, J., & Wu, F. (2004). Assessment Of Hydrologic Alterarions Caused By CHI-CHI Diversion Weir In CHOU-SHUI Creek , Taiwan : Opporyunities For Restoring Natural Flow Conditions. River Research and Applications. 20 (4): 401-412.
28. Shiau, J., & Wu, F. (2007). Pareto‐optimal solutions for environmental flow schemes incorporating the intra‐annual and interannual variability of the natural flow regime. Water Resources Research. 43 (433): 1-12
29. Sieber, J., & Purkey, D. (2015). User guide for WEAP. Stockholm Environment Institute, U.S. Center.
30. Suen, J., & Eheart, J. W. (2006). Reservoir Management to Balance Ecosystem and Human Needs : Incorporating the Paradigm of the Ecological Flow Regime. Water Resources Research. 42 (3): 1-9.
31. Tennant, D.L. (1976). Instream flow regimens for fish, wildlife, recreation and related environmental resources. Fisheries. 1 (4): 6-10.
32. Tisdell, J. (2010). Acquiring Water for Environmental Use in Australia : An Analysis of Policy Options. Water Resources Management. 24 (8): 1515-1530.
33. Wang, R., & Lu, X. (2009). Quantitative Estimation Models and Their Application of Ecological Water Use at a Basin Scale. Water Resour Manage. 23 (7): 1351-1365.
34. Whiting, P. J. (2002). Streamflow Necessary for Environmental Maintenance. Annual Review of Earth and Planetary Sciences. 30 (1): 181-206.
35. Zeinali, M., Azari, A., & Heidari, M.M. (2020). Multi-objective optimization for water resource management in low flow areas based on a coupled surface water-groundwater model. Water Resources Planning and Management. 146 (5): 040200-20.