Using Shuffled Frog-Leaping Algorithm (SFLA) And Geospatial Information System (GIS) To Help Optimally Operation of The Dam Reservoir (Case Study: Dorudzan Dam Reservoir)

Document Type : Research Article


1 Graduate Student, Engineering and Water Resources Management, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran

2 Assistant Professor, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran


Freshwater resources are limited in the world and long-term exploitation will cause aridity or drought. Iran is geographically located in the dry and semi-arid region of the world, with an average rainfall of about one-third the world average. In this regard, increased competition for water, the need for food for the growing population and the increase in aridity in many regions, require the use of management practices to prevent water crisis and the resulting impacts. On the other hand, the consequences of successive droughts have increased the importance of proper water resources management. Considering the momentous role of reservoirs in supplying water needs for different sectors of consumption, optimal utilization of them is one of the important solutions to the problems of water resources and the lack of appropriate distribution of time and space. In this research, a Shuffled Frog-Leaping Algorithm is proposed as a meta-heuristic method for solving optimization problems in water resource systems, and a Geospatial Information System is used to optimize the operation of the Dorudzan Dam reservoir. The combination of these two to solve the dam reservoir optimization problem was first carried out in the country in this paper. The result of the research in the area indicated that the algorithm is well able to optimize and allocate the reservoir water downstream in such a way that 99.9% of the need for the downstream of the Dorudzan dam during the studied period, was provided for. Also, the combination of this algorithm with the Geospatial Information System provides an opportunity for a more precise examination of optimization results.


Main Subjects

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Volume 6, Issue 4
January 2020
Pages 983-991
  • Receive Date: 21 April 2019
  • Revise Date: 06 August 2019
  • Accept Date: 06 August 2019
  • First Publish Date: 22 December 2019